ANOMALOUS REACTIVITY IN ARCHITECTED AND NATURAL SILICEOUS MATTER FOR A LOW CARBON ENERGY TRANSITION A Dissertation Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Hassnain Asgar May 2022 © 2022 Hassnain Asgar ANOMALOUS REACTIVITY IN ARCHITECTED AND NATURAL SILICEOUS MATTER FOR A LOW CARBON ENERGY TRANSITION Hassnain Agar, Ph. D. Cornell University 2022 The need to meet our energy and resource needs while limiting detrimental impacts on climate and environment motivate efforts to harness subsurface geologic environments for fluid recovery and storage. However, the subsurface environments are characterized by a wide range of chemical and physical heterogeneities that can influence the properties of thermodynamics, flow, and reactivity in these formations which can limit our ability to develop predictive controls over the fate of injected fluids such as carbon dioxide. Significant knowledge gaps exist in our understanding of the chemical and morphological evolution of materials at relevant subsurface conditions and the reactivity of fluids at solid interfaces. It is now possible to address this challenge due to advances in cross-scale synchrotron-based advanced characterization approaches and our ability to architect materials that are analogous to natural occurring minerals. In this thesis, fundamental insights into the assembly of siliceous materials and alumino-silicates using operando X-ray scattering measurements are discussed. The role of silica in inducing hydrogel formation for enhancing permeability in subsurface environments and the influence of quartz interfaces on directing the assembly of surfactants are investigated. The influence of amorphous silica dissolution and reprecipitation on the non-monotonic evolution of porosity in silica-rich shales and the role of siliceous nanochannels in directing the formation of stable calcium carbonate are elucidated. Approaches to determine interfacial reactivity involving alumino-silicates (e.g., sodium montmorillonite) and water using scattering and spectroscopy measurements and the alignment with predictions from reactive molecular dynamics simulations are discussed. These studies shed fundamental insights into the basic science underlying the reactivity of siliceous materials in diverse subsurface environments. BIOGRAPHICAL SKETCH Hassnain Asgar is a Ph.D. candidate in the School of Civil and Environmental Engineering at Cornell University since August 2019. He received an MS degree in Civil and Environmental Engineering from Cornell University in May 2020 and an MS degree in Engineering from Central Michigan University in December 2017. In 2015, he received his B.Sc. Metallurgy and Materials Engineering from University of the Punjab, Lahore, Pakistan with distinction (Gold Medal). His Ph.D. research was recognized by the U.S. Department of Energy, Energy Frontiers Research Center, Multi-Scale Fluid Solid Interactions in Architected and Natural Materials (MUSE) as “Outstanding Graduate Student Research”. He published 16 peer-reviewed journal articles and 8 conference presentations as of April 2022. Two manuscripts from his Ph.D. work are currently under review in peer-reviewed journals. His research interests include developing a cross-scale understanding of coupled chemo-morphological changes in materials in reactive environments, creating geo-architected siliceous materials as analogs to natural materials, and investigating chemical transformations of alumino- silicates, siliceous, carbonate, and clay-bearing materials. He served as a symposium organizer during the annual meetings of the American Chemical Society (ACS). He also served on the editorial board of the Department of Energy – Energy Frontier Research Center’s (DOE-EFRC) newsletter from May 2020 – May 2021. Hassnain will continue his research activities as a postdoctoral researcher in Dr. Greeshma Gadikota’s research group at Cornell University. The work presented in this dissertation is published or under review as mentioned in the following citations: Chapter 2. H. Agsar, V. Semeykina, M. Hunt, S. Mohammed, I. Kuzmenko, I. Zharov, and G. Gadikota, Thermally-Induced Morphological Evolution of Spherical Silica Nanoparticles using in-operando X-ray Scattering Measurements, Colloids and Surfaces v A: Physicochemical and Engineering Aspects, 2020, 586, 124260 Chapter 3. H. Agsar, S. Seifert, I. Kuzmenko, M. Bartl, and G. Gadikota, Mechanistic Insights into the Colloidal Assembly of Mesoporous Silica using in-operando Cross- Scale X-ray Scattering and Spectroscopic Mmeasurements, Materialia, 2020, 12, 100764 Chapter 4. H. Agsar, J. Jiaqi, J. Miller, I. Kuzmenko, I. Zharov, and G. Gadikota, Contrasting Thermally-Induced Structural and Microstructural Evolution of Alumino- Silicates with Tubular and Planar Arrangements: Case Study of Halloysite and Kaolinite, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2021, 613, 126106 Chapter 5. H. Agsar, J. Ilavsky, and G. Gadikota, Designing CO2-Responsive Multifunctional Nanoscale Fluids with Tunable Hydrogel Behavior for Subsurface Energy Recovery, Energy and Fuels, 2019, 33(7), 5988-5995 Chapter 6. H. Agsar, S. Mohammed, S. Seifert, and G. Gadikota, Structure and Shape of Surface-Mediated Assembly of Surfactants, Energy and Fuels, 2021, 35(24), 20206- 20215 Chapter 7. H. Agsar, S. Mohammed, A. Socianu, J. Kaszuba, P. D. Shevchenko, and G. Gadikota, Dissolution and Reprecipitation of Amorphous Silica in Silica Rich Shales Induces Non-Monotonic Evolution of Porosity in Acidic Reactive Environments, under review in ACS Earth and Space Chemistry Chapter 8. M. G. Muraleedharan, H. Agsar, S. H. Hahn, N. Dasgupta, G. Gadikota, and A. C. T van Duin, Interfacial Reactivity and Speciation Emerging from Na- Montmorillonite Interactions with Water and Formic Acid at 200 °C: Insights from Reactive Molecular Dynamics Simulations, Infrared Spectroscopy, and X-ray Scattering Measurements, ACS Earth and Space Chemistry, 2021, 5(5), 1006-1019 vi Chapter 9. H. Agsar, S. Mohammed, and G. Gadikota, Confinement Induces Stable Calcium Carbonate Formation in Silica Nanopores under review in Nanoscale vii Dedicated to my mother. viii ACKNOWLEDGMENTS First, I would like to extend my deepest gratitude to my advisor, Dr. Greeshma Gadikota, for her continuous support, valuable time, and insightful counsel throughout my doctoral studies. Her ability to ask the right scientific questions at the right time, infectious energy, and willingness to push scientific boundaries greatly inspired me and helped me flourish as a researcher. Her timely feedback, thoughtful comments, and recommendations were invaluable in developing new methods to probe fluid-solid interactions and creating new knowledge of anomalous reactivity involving siliceous materials. For all these efforts and her unwavering support beyond research, I am thankful to Dr. Greeshma Gadikota. I would also like to thank my dissertation committee members: Dr. John D. Albertson and Dr. Derek Warner for their valuable suggestions in shaping this dissertation. I am grateful to the leadership collaborators, and technical staff in the Energy Frontier Research Centers (EFRC) Multi-Scale Fluid-Solid Interactions in Architected and Natural Materials (MUSE) supported by the U.S. Department of Energy (DOE). The scientific opportunities from MUSE platform have enabled me to grow professionally and personally. I am thankful for the support and extensive discussions with the collaborators at different institutions including Dr. Darryl Butt (University of Utah (UoU)), Dr. Michael H. Bartl (UoU), Dr. Milid Deo (UoU), Dr. Jan Miller (UoU), Dr. Adri van Duin (Penn State University), Dr. Ilya Zharov (UoU), and Dr. John Kaszuba (University of Wyoming). A warm thank is extended to the support and help provided by Dr. Ivan Kuzmenko, Dr. Jan Ilavsky, Dr. Soenke Seifert, Dr. Olaf Borkiewicz, and Mr. Pavel D. Shevchenko at the Advanced Photon Source (APS) in Argonne National Laboratory (ANL) during the synchrotron-based measurements. I would also like to acknowledge the characterization facilities at Cornell Center for Materials Research (CCMR). ix I certainly appreciate the timely help of the group members in Gadikota Research Group: Dr. Sohaib Mohammed, Tianhe Yin, Xun Gao, Prince Ochonma, Allison Hohenshil, and Erin Huang. A warm thank you to my colleagues and the staff in the School of Civil and Environmental Engineering at Cornell University for their support during my doctoral studies. I would like to thank my friends for their cooperation and support during my Ph.D. journey, especially Danish Shahzad, Hassan Ilyas, Mubasher Nawaz, Mustafa Akram, Hafiz Waqas Ali, Syed Nabeel Ahmed, Zeeshan Ali, Shahryar Khan, Dr. Andleeb Rehman, Abdur Rehman, Nitish Kumar Vaja, and Mahwish Javed Khan. I also feel indebted to extend my sincerest gratitude to Usman Riaz and Umair Hussain Shah for their unconditional support and friendship during my journey in the United States. Lastly and most importantly, I am extremely grateful for the unwavering support and encouragement of my parents and siblings throughout my life. I am appreciative of the happiness that my nieces: Areeba Hassan and Hareem Hassan, and my nephews: Zayan Ali and Mohammad Ali Hassan bring to me through their radiant smiles during uncertain times. x TABLE OF CONTENTS BIOGRAPHICAL SKETCH ............................................................................................ v TABLE OF CONTENTS ................................................................................................ xi LIST OF FIGURES ........................................................................................................ xv LIST OF TABLES ...................................................................................................... xxix LIST OF ABBREVIATIONS ..................................................................................... xxxi 1 INTRODUCTION .................................................................................................... 1 2 THERMALLY-INDUCED MORPHOLOGICAL EVOLUTION OF SPHERICAL SILICA NANOPARTICLES USING IN-OPERANDO X-RAY SCATTERING MEASUREMENTS ....................................................................................................... 10 2.1 INTRODUCTION ........................................................................................... 10 2.2 MATERIALS AND METHODS ..................................................................... 13 2.2.1 Synthesis of SiO2 Nanoparticles ............................................................... 13 2.2.2 Experimental Setup and Characterization ................................................ 13 2.3 RESULTS AND DISCUSSION ...................................................................... 17 2.3.1 Evolution of Pore Morphology during the Calcination Process ............... 17 2.3.2 Evolution of Pore Morphology during the Sintering Process .................. 25 2.4 CONCLUSIONS ............................................................................................. 31 2.5 SUPPLEMENTARY MATERIAL.................................................................. 33 3 MECHANISTIC INSIGHTS INTO THE COLLOIDAL ASSEMBLY OF MESOPOROUS SILICA USING IN-OPERANDO CROSS-SCALE X-RAY SCATTERING AND SPECTROSCOPIC MEASUREMENTS ................................... 40 3.1 INRODUCTION .............................................................................................. 40 3.2 MATERIALS AND METHODS ..................................................................... 43 3.3 RESULTS AND DISCUSSION ...................................................................... 47 3.3.1 Characterization of SBA-15 Particles Synthesized with and without the Addition of Nitrate Salt .......................................................................................... 47 3.3.2 Evolution of the Si-bearing Functional Groups during the Synthesis of SBA-15 50 3.3.3 Dynamic Evolution in the meso-Scale Features of Silica ........................ 54 3.4 CONCLUSIONS ............................................................................................. 64 3.5 SUPPLEMENTARY MATERIAL.................................................................. 66 4 CONTRASTING THERMALLY-INDUCED STRUCTURAL AND MICROSTRUCTURAL EVOLUTION OF ALUMINO-SILICATES WITH TUBULAR AND PLANAR ARRANGEMENTS: CASE STUDY OF HALLOYSITE AND KAOLINITE ......................................................................................................... 78 xi 4.1 INTRODUCTION ........................................................................................... 78 4.2 MATERIALS AND METHODS ..................................................................... 82 4.3 RESULTS AND DISCUSSION ...................................................................... 85 4.3.1 Structural Changes during Thermal Treatment of Halloysite .................. 85 4.3.2 Morphological Changes during Thermal Treatment of Halloysite Nanotubes ............................................................................................................... 90 4.3.3 Comparison of Structural and Morphological Changes in Kaolinite and Halloysite ................................................................................................................ 98 4.4 CONCLUSIONS ........................................................................................... 102 4.5 SUPPLEMENTARY MATERIAL................................................................ 103 5 DESIGNING CO2-RESPONSIVE MULTI-FUNCTIONAL NANO-SCALE FLUIDS WITH TUNABLE HYDROGEL BEHAVIOR FOR SUBSURFACE ENERGY RECOVERY ............................................................................................... 106 5.1 INTRODUCTION ......................................................................................... 106 5.2 MATERIALS AND METHODS ................................................................... 110 5.2.1 Synthesis of SiO2-PAA nanofluids ........................................................ 110 5.2.2 Experimental Setup and Characterization .............................................. 110 5.3 RESULTS AND DISCUSSION .................................................................... 113 5.3.1 CO2 Uptake Capacity ............................................................................. 113 5.3.2 Mechanism of CO2 Absorption .............................................................. 114 5.3.3 Morphological Changes during CO2 Capture ......................................... 122 5.4 CONCLUSIONS ........................................................................................... 124 5.5 SUPPLEMENTARY MATERIAL................................................................ 125 6 STRUCTURE AND SHAPE OF SURFACE-MEDIATED ASSEMBLY OF SURFACTANTS .......................................................................................................... 129 6.1 INTRODUCTION ......................................................................................... 129 6.2 MATERIALS AND METHODS ................................................................... 133 6.3 RESULTS AND DISCUSSION .................................................................... 137 6.3.1 Organization of Micelles in Bulk Fluids and at Quartz Interfaces ......... 137 6.3.2 Energetics and Aggregation Behavior of Micelles ................................. 145 6.4 CONCLUSIONS ........................................................................................... 149 6.5 SUPPLEMENTARY MATERIAL................................................................ 150 6.5.1 Section S6.1. Details about the X-ray Scattering Modeling ................... 154 7 DISSOLUTION AND REPRECIPITATION OF AMORPHOUS SILICA IN SILICA RICH SHALES INDUCES NON-MONOTONIC EVOLUTION OF POROSITY IN ACIDIC REACTIVE ENVIRONMENTS ......................................... 158 xii 7.1 INTRODUCTION ......................................................................................... 158 7.2 MATERIALS AND METHODS ................................................................... 162 7.3 RESULTS AND DISCUSSION .................................................................... 167 7.3.1 Chemical Evolution in Shale Samples ................................................... 167 7.3.2 Fate of Leached Species ......................................................................... 175 7.3.3 Changes in Nanoscale Pore Morphology of Shales ............................... 177 7.3.4 Evolution of Microscale Porosity via in-situ Microtomography ............ 184 7.4 CONCLUSIONS ........................................................................................... 187 7.5 SUPPLEMENTARY MATERIAL................................................................ 189 7.5.1 Section S7.1. Details about ATR-FTIR data modeling .......................... 189 7.5.2 Section S2. Details about Models used to Process Combined Ultra-Small & Small Angle X-ray Scattering (USAXS/SAXS) Data ...................................... 192 7.5.3 Section S7.3 Weight Changes & Micron Scale Morphology in Unreacted and Reacted Shale Samples .................................................................................. 197 8 INTERFACIAL REACTIVITY AND SPECIATION EMERGING FROM Na- MONTMORILLONITE INTERACTIONS WITH WATER AND FORMIC ACID AT 200 °C: INSIGHTS FROM REACTIVE MOLECULAR DYNAMICS SIMULATIONS, INFRARED SPECTROSCOPY, AND X-RAY SCATTERING MEASUREMENTS ..................................................................................................... 200 8.1 INTRODUCTION ......................................................................................... 200 8.2 MATERIALS AND METHODS ................................................................... 203 8.2.1 Experimental Methods and Materials ..................................................... 203 8.2.2 ReaxFF/Reactive Molecular Dynamics Simulations .............................. 205 8.3 RESULTS AND DISCUSSION .................................................................... 208 8.3.1 Speciation Behavior ................................................................................ 208 8.3.2 Precipitation of Solids at the Interlayer .................................................. 212 8.3.3 Differences in the Reactivities of Facets, Edges, and Interlayers .......... 216 8.4 CONCLUSIONS ........................................................................................... 229 8.5 SUPPLEMENTARY MATERIAL................................................................ 232 8.5.1 Materials ................................................................................................. 232 8.5.2 Quantum Chemical Calculations and Force Field Development ........... 232 9 CONFINEMENT INDUCES STABLE CALCIUM CARBONATE FORMATION IN SILICA NANOPORES ........................................................................................... 251 9.1 INTRODUCTION ......................................................................................... 251 9.2 MATERIALS AND METHODS ................................................................... 256 9.2.1 Synthesis of Silica Nanochannels (SNCs) .............................................. 256 xiii 9.2.2 Formation of Calcium Carbonate in Confinement ................................. 258 9.2.3 Investigation of Ion Hydration and Transport Behavior using Molecular- Scale Simulations ................................................................................................. 259 9.3 RESULTS AND DISCUSSION .................................................................... 261 9.3.1 Synthesis of Silica Nanochannels (SNCs) .............................................. 261 9.3.2 Formation of Calcium Carbonates in Silica Nanochannels (SNCs) ....... 263 9.3.3 Influence of Ion Hydration and Transport on Calcium Carbonate Formation ............................................................................................................. 266 9.4 CONCLUSIONS ........................................................................................... 270 9.5 SUPPLEMENTARY MATERIAL................................................................ 272 10 CONCLUSIONS AND OUTLOOKS .................................................................. 277 11 REFERENCES ..................................................................................................... 284 xiv LIST OF FIGURES Figure 2.1 Representative ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental curve of SiO2 nanoparticles. The curve is divided into three different regions which were modeled to obtain the information about the physical features of interest. 15 Figure 2.2 Ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental data represent changes in the microstructural features of SiO2 nanoparticles during heating to calcination temperature (a) and during calcination at 600 °C (b). ................. 18 Figure 2.3 Particle size volume fraction distributions of silica nanoparticles approximated in the q-range of 0.002-0.03 Å-1 on heating to calcination temperature (a-1) and during the calcination process (a-2). The changes in the pore morphology in the q-range of 0.03- 0.7 Å-1 as represented by the characteristic radius of gyration (Rg) (black curve) and the power-law slope (red curve) during the temperature ramp to achieve the calcination temperature (b-1) and at the calcination temperature (b-2). The error bars on Rg values and power-law slopes correspond to 3% of error in calculated values. The insets in (a-1) and (a-2) represent the corresponding scanning electron micrographs. ......................... 20 Figure 2.4 Pore size distributions and cumulative pore volumes of untreated (a), and calcined (b) silica nanoparticles. SiO2 nanoparticles were prepared by the modified Stöber method and calcined at 600 °C for 4 hours. ................................................................... 22 Figure 2.5 Changes in the Si-OH and Si-O-Si features for SiO2 nanoparticles heated to different temperatures and calcined at 600 °C measured using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR). Bands around 795 cm-1, 950 cm-1, and 1054 cm-1 correspond to Si-O-Si (sym.), Si-OH, and Si-O-Si (asym.) vibrations, respectively. With an increase in temperature, the Si-O-Si asymmetric band broadens while Si-OH vibration band ~950 cm-1 appears to be diminished in the calcined sample as a result of dehydroxylation of silica. ............................................................. 23 Figure 2.6 The pair distribution function (PDF) curves calculated from total X-ray scattering data during the in-operando heating of silica nanoparticles to calcination temperature (600 °C). Inset shows the schematic of dehydroxylation process i.e., breakage of silanol (Si-OH) bonds and formation of new siloxane (Si-O-Si) bridges. . 25 Figure 2.7 Ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental data represent changes in the microstructural features of calcined SiO2 nanoparticles during heating to sintering temperature (a) and during sintering at 1050 °C (b). .......... 26 Figure 2.8 Particle size volume fraction distributions of calcined silica nanoparticles on heating to the sintering temperature (a-1) and during the sintering process (a-2) approximated in the q-range of 0.002-0.03 Å-1. The changes in the pore morphology in the q-range of 0.03-0.7 A-1 as represented by the characteristic radius of gyration (Rg) (black curve) and the power-law slope (red curve) during the temperature ramp to achieve sintering temperature (b-1) and at the sintering temperature (b-2). The error bars on Rg and power-law values correspond to 3% of error in calculated values. The inset in (a-2) represent the corresponding scanning electron micrograph. .......................................... 27 xv Figure 2.9 Pore size distribution and cumulative pore volume of sintered SiO2 nanoparticles. SiO2 nanoparticles were prepared by modified Stöber method, calcined at 600 °C for 4 hours and sintered at 1050 °C for 4 hours. ................................................ 28 Figure 2.10 Comparison of changes in the Si-OH and Si-O-Si features for untreated, calcined and sintered SiO2 nanoparticles measured using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR). Bands around 795 cm-1, 950 cm- 1, and 1054 cm-1 correspond to Si-O-Si (sym.), Si-OH, and Si-O-Si (asym.) vibrations, respectively. With an increase in temperature, the Si-O-Si asymmetric band broadens while Si-OH vibration band ~950 cm-1 diminishes completely as a result of sintering at 1050 °C. .......................................................................................................................... 30 Figure 2.11 Schematic representation of chemo-morphological changes that occurring during sintering of silica nanoparticles. As a result of heating to calcination temperature (600 °C), primary dehydroxylation of -OH groups from silanol (Si-OH) bonds generate siloxane (Si-O-Si) bridges (change from I to II). Heating the calcined nanoparticles to sintering temperature (1050 °C) results in secondary dehydroxylation, which starts after 800 °C where Si-O-Si bridges could form inside the pores (III). ................................... 31 Figure 2.12 Figure S2.1 Representative ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental data for untreated (a), calcined (b), and sintered (c) SiO2 nanoparticles. Red lines represent the simulated scattering patterns. The simulated data were obtained using 3 levels of fits using the Modeling II tool in Irena package.179 For low q-region (<0.001 Å-1); unified fit, medium q-range (0.001 – 0.03 Å-1); size distribution and high q-region (0.03 – 0.7 Å-1); unified fit models were used. .............. 33 Figure 2.13 Figure S2.2 Changes in the power-law slope values during the temperature ramp to calcination temperature (a-1), at the calcination temperature (a-2), during the temperature ramp to sintering temperature (b-1) and during the heating at the sintering temperature (b-2). The error bars correspond to 3% of error in the calculated values. .. 34 Figure 2.14 Figure S2.3 Changes in the weight of the silica nanoparticles with temperature during calcination and sintering using Thermogravimetric Analyses (TGA). During the calcination step, SiO2 nanoparticles which were obtained by modified Stöber process were heated to 600 °C at the ramp rate of 5 °C/min followed by isothermal heating for 4 hours. The calcined particles were then cooled to room temperature and heated to 950 °C (sintering temperature) at the ramp rate of 5 °C/min. ........................................ 35 Figure 2.15 Figure S2.4 The pair distribution function (PDF) curves calculated from total X-ray scattering data during the in-operando heating of silica nanoparticles to calcination temperature (600 °C). ..................................................................................................... 36 Figure 2.16 Figure S2.5 N2 adsorption-desorption isotherms for untreated (a) and treated at 150 °C (b), 300 °C (c), 400 °C (d), 500 °C (e), calcined (f), and sintered (g) SiO2 nanoparticles. .................................................................................................................. 37 Figure 2.17 Figure S2.6 Pore size distribution and cumulative pore volume for SiO2 nanoparticles treated at 150 °C (a), 300 °C (b), 400 °C (c), and 500 °C (d). The xvi calculations were performed using the DFT model in Quantachrome software using Silica as adsorbate at 77K (liquid N2) and cylindrical/sphere silica pores were modelled on the adsorption isotherm. ....................................................................................................... 38 Figure 2.18 Figure S2.7 Surface areas of different SiO2 nanoparticle samples calculated from the adsorption isotherm using the nonlocal density functional theory (NLDFT) model in Quantachrome software using Silica as adsorbate at 77K (liquid N2) and from the modeling of cylindrical/sphere silica pores. ............................................................. 39 Figure 3.1 (a) Identification of the functional groups using Attenuated Total Reflection- Fourier Transform Infrared spectroscopy (ATR-FTIR) measurements, and (b) meso-scale structure determination using Small Angle X-Ray Scattering (SAXS) measurements in mesoporous silica, SBA-15 synthesized without (M-1) and with magnesium nitrate salt (M-2). .............................................................................................................................. 48 Figure 3.2 Pore size distribution curves (a) and N2 adsorption-desorption isotherms for mesoporous M-1 (b-1) and M-2 (b-2), respectively. M-1 and M-2 represent mesoporous silica, SBA-15 synthesized without and with magnesium nitrate salt. ........................... 49 Figure 3.3 Evolution of the functional groups during the synthesis of mesoporous silica, SBA-15 in the (a-1) absence (M-1) and (b-1) presence of nitrate ions (M-2). The time evolution of the functional groups based on the normalized integrated peak areas in mesoporous silica, SBA-15 in the (a-2) absence (M-1) and (b-2) presence (M-2) of nitrate ions is shown. ................................................................................................................. 53 Figure 3.4 Evolution in the characteristic d (100) peak in mesoporous silica, SBA-15 synthesized in the (a) absence (M-1) and (b) presence (M-2) of nitrate salt using in- operando Small Angle X-Ray Scattering (SAXS) measurements. Comparison of the normalized integrated peak intensity of the d (100) peak is shown in (c). ..................... 56 Figure 3.5 Estimated radius of gyration (Rg) values for M-1 and M-2 between the q-range of 0.2 – 0.8 Å-1 obtained from the transmission SAXS measurements. ......................... 57 Figure 3.6 Morphologies of as-prepared (a-1) M-1 and (b-1) M-2 and, (a-2) M-1 and (b- 2) M-2 aged for three weeks represented using Scanning electron micrographs (SEM). M-1 and M-2 represent mesoporous silica, SBA-15 synthesized without and with magnesium nitrate salt. ................................................................................................... 58 Figure 3.7 Evolution in the characteristic d (100) peak in mesoporous silica, SBA-15 synthesized in the (a-1) absence (M-1) and (b-1) presence (M-2) of nitrate salt using in- operando Grazing Incidence - Small Angle X-Ray Scattering (GI-SAXS) measurements. The morphologies of (a-2) M-1 and (b-2) M-2 are captured using Scanning electron micrographs (SEM). ....................................................................................................... 61 Figure 3.8 Avrami plots for (a) M-1 and (b) M-2 determined from GI-SAXS data. M-1 and M-2 represent mesoporous silica, SBA-15 synthesized without and with magnesium nitrate salt, respectively. ................................................................................................. 63 xvii Figure 3.9 Figure S3.1 Schematic of experimental setup during in-situ transmission small angle X-ray scattering (SAXS) (a) and in-situ grazing incidence small angle X-ray scattering (GI-SAXS) (b) measurements. ....................................................................... 70 Figure 3.10 Figure S3.2 Small Angle X-ray Scattering (SAXS) curves at different time intervals (points) and fitted models (solid line) for M-1 (a) and M-2 (b) samples. ....... 71 Figure 3.11 Figure S3.3 ATR-IR spectra of raw materials used during the synthesis of M- 1, and M-2 mesoporous materials. In case of TEOS and water, the background was air. However, for M-1 (pre TEOS) and M-2 (pre TEOS) water was taken as the background. ........................................................................................................................................ 72 Figure 3.12 Figure S3.4 Deconvoluted ATR-IR spectra during the synthesis of M-1 at different times between the range of 1250 – 1000 cm-1. ................................................ 73 Figure 3.13 Figure S3.5 Deconvoluted ATR-IR spectra during the synthesis of M-2 at different times between the range of 1250 – 1000 cm-1. ................................................ 74 Figure 3.14 Figure S3.6 Integrated peak areas for Si-O-Si vibrations ~1079 cm-1 calculated from Figure S4 and Figure S5 for M-1 (a) and M-2 (b), respectively. ......... 75 Figure 3.15 Figure S3.7 GI-SAXS experimental data for micelle scattering from M-1 and fitted core-shell model. ................................................................................................... 76 Figure 3.16 Figure S3.8 Full Width Half Maximum (FWHM) values for (100) peak for M-1 (a) and M-2 (b), respectively, calculated from GI-SAXS data. The error bars correspond to the 5% of error in calculated values. ....................................................... 77 Figure 4.1 Morphology of (a) planar kaolinite and (b) tubular halloysite aluminosilicates as viewed by a scanning electron microscope. Schematic comparison of kaolinite and halloysite structures is shown in (c). .............................................................................. 79 Figure 4.2 Influence of temperature on weight changes of halloysite as determined by thermogravimetric analysis. Stage I corresponds to the loss of interlayer water. Stage II represents the halloysite structure without interlayer water present. Stage III represents the dehydroxylation of the halloysite structure. Stage IV represents the structure of halloysite after complete dehydroxylation. .................................................................... 86 Figure 4.3 Changes in the interlayer basal spacing as a function of temperature in the q range of 0.4 - 1 Å-1 determined from Small Angle X-ray Scattering (SAXS). .............. 87 Figure 4.4 Changes in the structural arrangement of halloysite clay during thermal treatment determined using Wide-Angle X-Ray Scattering (WAXS) measurements. The panels at the bottom show the comparison of WAXS curves with halloysite with interlayer basal spacing at 7 Å and 10 Å. ....................................................................... 88 Figure 4.5 Changes in the characteristic halloysite peaks where (a-1) and (b-1) represent hkl reflections of (042) and (060), respectively, as measured using Wide-Angle X-Ray xviii Scattering (WAXS) measurements. The integrated peak intensities normalized with respect to the maximum values are presented in (a-2) and (b-2). .................................. 89 Figure 4.6 Changes in the combined slit-smeared USAXS/SAXS experimental curves of halloysite nanotubes during thermal treatment. .............................................................. 91 Figure 4.7 Radii of gyration (Rg) and power-law slopes estimated via unified fit models for scattering from pores (0.001 – 0.02 Å-1) (a) and nanotubes (0.02 – 0.5 Å-1) (b). ..... 93 Figure 4.8 3D pore network of consolidated halloysite characterized by nano XCT at the voxel resolution of 32 nm (a) and pore size (diameter) in 3D pore network represented by computed local thickness (b). ......................................................................................... 94 Figure 4.9 N2 adsorption-desorption isotherms for halloysite treated at 90 °C (a) and halloysite treated at 700 °C (b). The pore size distribution as calculated from the BJH model on desorption isotherms (c). ................................................................................ 97 Figure 4.10 Comparison of structural changes in kaolinite and halloysite subjected to in- operando heat treatment. The evolution in interlayer basal spacing d001 (a) and (001) peak intensities (b) are presented as a function of temperature. The kaolinite data was adopted from Gadikota et al.49 ................................................................................................... 100 Figure 4.11 Schematic representation of the evolution in the structure of kaolinite and halloysite during thermal treatment. ............................................................................. 101 Figure 4.12 Figure S4.1 Representative Ultra-Small and Small Angle X-ray Scattering (USAXS/SAXS) experimental data for halloysite sample at 25 °C (a), 125 °C (b), 400 °C (c), 500 °C (d), 625 °C (e), and 800 °C (f). Red lines represent the simulated scattering patterns. The simulated data were obtained using 3 levels of unified fit models for the q values < 0.001 Å-1 and in the ranges of 0.001 – 0.02 Å-1, and 0.02 – 0.5 Å-1, respectively. ...................................................................................................................................... 103 Figure 4.13 Figure S4.2 Power-law slopes estimated for q values < 0.001 Å-1 in the Ultra- Small Angle X-ray Scattering (USAXS) region using the unified fit model. .............. 104 Figure 4.14 Figure S4.3 Functional groups in kaolinite (a) and halloysite (b) as identified using ATR-IR spectroscopy. The insets show the zoomed-in spectra between the range of 375-3550 cm-1 for -OH stretching vibrations. .......................................................... 105 Figure 5.1 Illustration of CO2 uptake by aqueous amine (a) to produce the intermediate zwitterion (b) production of carbamate ion and the ion pair, and (c) regeneration of amine during hydrolysis of carbamate ion to produce bicarbonate ion. ................................. 109 Figure 5.2 Schematic of the experimental setup for measuring CO2 uptake. ............... 111 Figure 5.3 Comparison of the breakthrough curves of CO2 absorption in PAA and SiO2- PAA fluids. Figure in the inset represents CO2 absorption capacity (mmol/mL) for these fluids. ............................................................................................................................ 114 xix Figure 5.4 Identification of the functional groups present in (a) 1000 ppm PAA and (b) SiO2-PAA nanofluids before and after CO2 loading using ATR-FTIR spectra. .......... 117 Figure 5.5 Changes in the functional groups present in CO2 loaded-PAA fluids with increasing temperature determined using ATR-FTIR measurements. ......................... 118 Figure 5.6 Changes in the functional groups present in CO2-loaded SiO2-PAA bearing nanofluids with increasing temperature determined using ATR-FTIR measurements. ...................................................................................................................................... 119 Figure 5.7 Proposed mechanism for CO2 uptake in (a) PAA and (b) nanofluids containing PAA tethered to SiO2 nanoparticles. Hydrogel formation in nanofluids containing PAA tethered to SiO2 nanoparticles is more prominent compared to fluids containing PAA as shown in (c). Solutions containing PAA or PAA tethered to 1 wt% SiO2 nanoparticle were exposed to CO2 partial pressures of 1 atm for 20 minutes. ................................. 121 Figure 5.8 Time-resolved USAXS/SAXS measurements of nanofluids containing 1 wt% of PAA tethered to SiO2 nanoparticles (inset: SAXS curves of 1000 ppm PAA) (a) and the corresponding changes in the power law slopes determined in the q range < 10-2 Å-1 (b). Estimated error of the power law slope is 3% of the average value. .................... 122 Figure 5.9 Figure S5.1 Clear 1000 ppm PAA solution in DI water (a) turns cloudy on adding 1 wt.% SiO2 nanoparticles (b). ......................................................................... 125 Figure 5.10 Figure S5.2 ATR-FTIR spectra of starting PAA solution and 50 nm SiO2 nanoparticles suspension. ............................................................................................. 126 Figure 5.11 Figure S5.3 ATR-FTIR spectra of starting SiO2-PAA, SiO2-PAA-CO2, SiO2- PAA-CO2 nanofluids purged with N2 (SiO2-PAA-CO2-N2) and SiO2-PAA-CO2 diluted with excess water (left) and physical changes in nanofluids (right). N2 (99.99%) was purged at 1 atm for 30 minutes. .................................................................................... 127 Figure 5.12 Figure S5.4 USAXS/SAXS curves and the fitted models of SiO2-PAA nanofluids exposed to CO2 as a function of time. ........................................................ 128 Figure 6.1 Schematic representation of a surfactant molecule and self-assembled core- shell micelle (a) and X-ray scattering experimental setup (b). ..................................... 134 Figure 6.2 Schematic representation of models used for modeling the X-ray scattering data. A cut through at the equatorial axis (a), and a cross-section through the rotational axis (b) for prolate core-shell ellipsoid model and core-shell cylindrical model (c). ... 135 Figure 6.3 Organization of CTAB molecules in (a) the bulk fluids and (b) in fluids interacting with quartz surfaces using Small-Angle X-ray Scattering (SAXS) and Grazing-Incidence Small-Angle X-Ray Scattering (GI-SAXS), respectively. ............ 138 Figure 6.4 Organization of mixture of CTAB + P123 molecules in (a) the bulk fluids and (b) in fluids interacting with quartz surfaces using Small-Angle X-ray Scattering (SAXS) xx and Grazing-Incidence Small-Angle X-Ray Scattering (GI-SAXS), respectively....... 139 Figure 6.5 Representative GISAXS patterns for CTAB + P123 (a) in bulk and (b) on Quartz surface. The dotted white line indicates the portion of Yoneda Wing, along which the horizontal cut is made to obtain the 1D curves. ..................................................... 141 Figure 6.6 The self-assembly of CTAB (a-1), the mixture of CTAB and P123 (b-1) in bulk fluid, and CTAB (a-2), the mixture of CTAB and P123 (b-2) in fluids interacting with the quartz surface. The snapshots are taken during the last 1 ns of the simulation time. CTAB and P123 molecules are shown in CPK drawing method impplemented in VMD software. ............................................................................................................. 142 Figure 6.7 Schematic representation of the organization of CTAB micelles in (a) the bulk fluid and (b) the fluids in contact with the quartz surface. Figures (c) and (d) represent CTAB + P123 micelles in the (c) bulk fluid and (d) the fluids in contact with the quartz surface. These structures are inferred from X-ray scattering data. ............................... 143 Figure 6.8 The electrostatic and Lennard-Jones intermolecular interactions of CTAB- CTAB in the bulk fluids and the fluids in contact with the quartz surface in the absence and presence of P123 molecules. .................................................................................. 146 Figure 6.9 The aggregation number of CTAB and P123 in the bulk fluids and the fluids in contact with the quartz surface as a function of the simulation time. ...................... 147 Figure 6.10 Density profiles of fluidic components in solutions bearing (a) CTAB alone and (b) CTAB and P123 molecules as a function of the distance from the quartz surface. ...................................................................................................................................... 148 Figure 6.11 Figure S6.1 Snapshots show the initial configurations of (a) CTAB in bulk solvent, (b) CTAB and solvent on quartz surface, (c) CTAB + P123 in bulk solvent and (d) CTAB + P123 and solvent on quartz surface. CTAB, P123 and quartz atoms are shown using VDW drawing method the solvent atoms are showen in Licorice drawing method implemented in VMD software. ................................................................................... 150 Figure 6.12 Figure S6.2 Total energy convergence of the quartz unit cell as a function of the cutoff energy (top) and K-points mesh (bottom). A cutoff energy of 420 eV and a K- point mesh of 6×6×6 have been used to oprimize the quartz unit cell. ........................ 151 Figure 6.13 Figure S6.3 The total energy profile governed from DFT energy optimization. The total energy is converged in 14 steps. The insets show the initial configuration and the optimized configurations of the quartz unit cell. .................................................... 152 Figure 6.14 Figure S6.4 Schematic representation of the core-shell ellipsoid model with a cut through at the equatorial axis (a), and a cross-section through the rotational axis (b). ...................................................................................................................................... 155 Figure 6.15 Figure S6.5 Schematic representation of the core-shell cylindrical model. ...................................................................................................................................... 156 xxi Figure 6.16 Figure S6.6 Structure factor (S(q)) contributions calculated based on the volume fraction and effective radius of hard spheres during data modeling. .............. 157 Figure 7.1 Schematic of (a) different Qn coordination in silicate species, (b) evolution of nanoscale porosity upon interaction with 1M HCl, and (c) X-ray tomography setup used during the temporal evolution of microscale porosity during reaction with 1M HCl. . 166 Figure 7.2 Attenuated Total Reflection Infrared (ATR-IR) spectra for Silica Rich – Carbonate/Clay Lean (Mowry shale) (a), Silica, Carbonate & Clay Bearing (Frontier shale) (b), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) (c) samples before and after reaction with 1M HCl. ................................................................................... 168 Figure 7.3 Delineation of Q1-Q4 contributions from Silica using deconvoluted ATR-IR spectra for Silica Rich – Carbonate/Clay Lean (Mowry shale) (a-1, a-2), Silica, Carbonate & Clay Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) (c-1, c-2) unreacted and reacted with 1M HCl, respectively. ............ 169 Figure 7.4 Contributions of Q1-Q3 and Q4 species in unreacted and reacted (1M HCl) Silica Rich – Carbonate/Clay Lean (Mowry shale), Silica, Carbonate & Clay Bearing (Frontier shale), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) samples from the estimated band areas. .............................................................................................. 171 Figure 7.5 Identification of different phases in Silica Rich – Carbonate Lean (Mowry shale) (a-1, a-2), Silica & Carbonate Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate Rich (Niobrara shale) (c-1, c-2) samples before and after reaction with 1M HCl, respectively, determined using the wide-angle X-ray scattering (WAXS) measurements. .............................................................................................................. 173 Figure 7.6 Concentration of different leachates from shales samples upon reaction with 1M HCl (1 g powder per 100 mL solution) at room temperature for 2 hours. ............. 176 Figure 7.7 Cumulative pore volumes and pore size distributions of Silica Rich – Carbonate/Clay Lean (Mowry shale) (a-1, a-2, a-3), Silica, Carbonate & Clay Bearing (Frontier shale) (b-1, b-2, b-3), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) (c-1, c-2, c-3) samples before and after reaction with 1M HCl, respectively, determined using Barrett-Joyner-Halenda (BJH) method applied on the desorption isotherm. ..... 178 Figure 7.8 Combined USAXS/SAXS curves for (a-1) Silica Rich – Carbonate/Clay Lean, (b-1) Silica, Carbonate & Clay Bearing, and (c-1) Silica Lean – Carbonate/Clay Lean samples. The corresponding pore size distributions obtained from fitting the USAXS/SAXS curves are presented in panles (a-2), (b-2), and (c-2). ........................ 181 Figure 7.9 Fractal dimensions of unreacted and reacted shale samples estimated from combined USAXS/SAXS data at two different length scales. Population 1 and population 2 represent the scattering from pore having dimensions 2 – 200 nm and larger than 200 nm, respectively. ........................................................................................................... 183 Figure 7.10 X-ray microtomography images of core sample drilled out of (Silica Rich – xxii Carbonate/Clay Lean) Mowry shale sample. The darker (black) spots (a-1) indicate the total porosity in the sample. Pore channels connected via 6 pixels (a-2), and 26 pixels (a- 3) are also presented. The diameter of the core presented is 2.64 mm and the pixel size is 1.3 µm. Porosity estimated from pixel (%) as a function of reaction time estimated from the X-ray tomography image analysis (b). The changes in the channel positions at 50 minutes and 75 minutes indicate that the local porosity evolves as the reaction proceeds, governed by the mobilization of precipitated particles. The highlighted regions in (a-2) indicate the changes in the flow channels originating from the movement of precipitated fine particles. ................................................................................................................ 185 Figure 7.11 Schematic representation of changes in the porosity of shale sample during reaction with 1M HCl. The carbonate/clay phases are present in the silica rich matrix (a), the porosity of sample increases upon dissolution of these phases within first 25 minutes of reaction (b), precipitation of silica-based species causes the porosity to decrease as the reaction proceeds (c), and increased roughness at the pore-solid/fracture-solid interface caused by the precipitation. .......................................................................................... 187 Figure 7.12 Figure S7.1. X-ray diffraction patterns (a), and infrared (IR) spectra (b) of crystalline (Quartz) and amorphous (Silica 60) samples. Deconvoluted IR spectra of quartz (c) and silica 60 (d) between the wavenumbers of 850 cm-1 and 1250 cm-1. .... 189 Figure 7.13 Figure S7.2. Concentration of leachates of minor species from shales samples upon reaction with 1M HCl (1 g powdered sample per 100 mL solution) at room temperature for 2 hours. ............................................................................................... 191 Figure 7.14 Figure S7.3. Combined USAXS-SAXS curves and the fitted models during (a) pore size distribution fitting and (b) unified fitting to obtain fractal dimensions. .. 194 Figure 7.15 Figure S7.4. N2 adsorption-desorption isotherm for Silica Rich – Carbonate Lean (Mowry shale) (a-1, a-2), Silica & Carbonate Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate Rich (Niobrara shale) (c-1, c-2) samples before and after reaction with 1M HCl, respectively. ............................................................................. 195 Figure 7.16 Figure S7.5. Thermogravimetric analysis (TGA) of Silica Rich – Carbonate Lean (Mowry shale) (a), Silica & Carbonate Bearing (Frontier shale) (b), and Silica Lean – Carbonate Rich (Niobrara shale) (c) samples before and after reaction with 1M HCl. ...................................................................................................................................... 198 Figure 7.17 Figure S7.6. Scanning electron micrographs (SEMs) of Silica Rich – Carbonate Lean (Mowry shale) (a-1, a-2), Silica & Carbonate Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate Rich (Niobrara shale) (c-1, c-2) samples before and after reaction with 1M HCl, respectively. ............................................................. 199 Figure 8.1 Snapshot of the simulated initial configuration of the molecular simulation showing Na-montmorillonite, water and formic acid molecules at 473 K and 1 bar. .. 208 Figure 8.2 Comparison of (a) experimental and (b) computed IR spectra for unreacted Na-montmorillonite (Na-MM), Na-MM reacted in water, water and formic acid ratio of xxiii 1:1, and in formic acid with a purity of 98-100% at 200 °C and 1 atm for a reaction time of 2 hours. ..................................................................................................................... 209 Figure 8.3 Mechanisms involved in the formation of sodium bicarbonate (NaHCO3) near the interlayer of Na-montmorillonite where (a) represents the interactions between Na+ ion and the oxygen of H2CO3, followed by the formation of intermediate species, Na-- H2CO3 as shown in (b). This intermediate species dissociates to produce NaHCO3 and proton, as shown in (c). (d) Na+ ion attacks the oxygen of OH group of NaHCO3 resulting in (e) Na2CO3 formation. .............................................................................................. 213 Figure 8.4 Changes in the interlayer basal spacing of Na-montmorillonite after reacting with water, HCOOH, and, 1:1 mixture of HCOOH and water at 200 °C and 1 atm for 2 hours using Ultra-Small Angle Scattering/Small Angle X-Ray Scattering (USAXS/SAXS) measurements. .................................................................................. 214 Figure 8.5 Evidence of the formation of Na2CO3, NaOH, and HCOONa due to reaction of Na-montmorillonite with water, 1:1 mixture of water and formic acid, and formic acid (98-100%)) at 200 °C and 1 atm for a reaction time of 2 hours using Wide Angle X-Ray Scattering (WAXS) measurements. .............................................................................. 215 Figure 8.6 The concentration of hydroxyl ions as a function of time at the edge, interlayer, and facet of Na-montmorillonite for various fluidic environments such as a 1:1 mixture of water and formic acid, formic acid, and water. ........................................................ 220 Figure 8.7 NaOH concentrations as a function of reaction time at the edge, interlayer, and facets of Na-montmorillonite in various fluidic environments such as a 1:1 mixture of water and formic acid, formic acid, and water. ........................................................ 221 Figure 8.8 CO concentrations as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid and formic acid are shown. ........................................................................................................................... 222 Figure 8.9 Mechanisms involved in CO formation due to surface water catalysis where (a) represents the interactions between the water adsorbed on the surface and the formic acid molecule, (b) represents proton abstraction from C-H bond of formic acid to water and from water to oxygen resulting from hydrogen bonding (c) represents the formation of intermediate species: CO-H2O, and (d) shows the formation of CO and H2O molecules. ...................................................................................................................................... 223 Figure 8.10 CO2 concentrations as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid and formic acid are shown. ........................................................................................................................... 224 Figure 8.11 Mechanisms of CO2 formation resulting from the oxidation of CO catalyzed at Na-montmorillonite surfaces where (a) shows the adsorption of CO on the surface site, (b) represents the formation of intermediate species CO*, (c) represents the formation of intermediate species, H--CO2, and (d) represents the formation of CO2 and a proton. 225 xxiv Figure 8.12 CO 2-3 concentrations as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid and formic acid are shown. (Zero error bar indicates that all three simulation runs yielded same concentrations). ............................................................................................................ 226 Figure 8.13 Mechanisms involved in the formation of CO 2-3 species from HCOO - adsorbed at the interlayer of Na-montmorillonite by binding to the Al or Si site where (a) represents the simultanous attack of one dangling O of montmorillonite on C of HCOO- and weakening of C=O double bond followed by the formation of -C-O-Al/Si bridge as shown in (b), and the formation of CO 2- 3 which remains in adsorbed state and is neutralized by protons or Na+ ions as represented by (c). ............................................ 227 Figure 8.14 Carbonic acid (H2CO3) concentration as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid. ...................................................................................................................................... 227 Figure 8.15 Figure S8.1 Comparisons of ReaxFF to QM values for constraining of (a) Na-O-C angle and (b) Na-C off-diagonal. .................................................................... 233 Figure 8.16 Figure S8.2 ReaxFF and QM comparison of vibrational frequencies of NaHCO3 molecule. ....................................................................................................... 234 Figure 8.17 Figure S8.3 Different C-O bond stretching and compression for NaHCO3 vibrational frequencies. ................................................................................................ 235 Figure 8.18 Figure S8.4 Physisorption of formic acid and water on Na-montmorillonite surface. (a) Less dense adsorption layer at t = 0 ps, (b) dense adsorption layer at t = 2.5 ps, and the zoomed in image of adsorbed layer (right). ............................................... 236 Figure 8.19 Figure S8.5 Angle distribution in (a) Si-O-Si and (b) Si-O-Al linkages before and after reacting with water, as calculated from ReaxFF simulations. ....................... 237 Figure 8.20 Figure S8.6 The concentration of water (H2O) and formic acid (HCOOH) molecules with a ratio of 1:1 at the edge, interlayer, and facet of sodium montmorillonite are represented. The physisorbed state of the molecules is shown at t = 0. The concentrations of these molecules at reaction times of 0.2, 0.4, and 0.6 ns are shown.238 Figure 8.21 Figure S8.7 Concentrations of H+, HCHO, CHO- and H2 as a function of time for various environments. ............................................................................................. 239 Figure 8.22 Figure S8.8 Mechanisms involved in the reaction of sodium ions with hydroxyl ions to produce sodium hydroxide molecules where (a) represents the surface oxygen atom of a strained Si-O-Si bond at the elevated temperature, (b) represents the protonation of the surface site and Na+/proton exchange in water, and (c) represents reactive/non-reactive diffusion of NaOH to bulk fluid. ............................................... 240 Figure 8.23 Figure S8.9 Sodium leaching by charge neutralization (sodium hydroxide formation) (a) hydroxyl ion near surface attacks surface Na+ cation, (b) NaOH formation, xxv (c) reactively/non-reactive diffusion of NaOH to bulk fluid. ....................................... 241 Figure 8.24 Figure S8.10 Deconvolution of ATR-IR spectra in the range of 1800-1300 cm-1 for Na-Montmorillonite (a) unreacted, and reacted with (b) H2O, (c) HCOOH and (d) 1:1 mixture of H2O and HCOOH. The R-squared (R 2) values corresponding to the coefficient of determination (COD) for each deconvolution fit, representing the goodness of fits, are also reported. ............................................................................................... 242 Figure 8.25 Figure S8.11 Deconvolution of ATR-IR spectra in the range of 3800-2650 cm-1 for Na-Montmorillonite (a) unreacted, and reacted with (b) H2O, (c) HCOOH and (d) 1:1 mixture of H2O and HCOOH. The R-squared (R 2) values corresponding to the coefficient of determination (COD) for each deconvolution fit, representing the goodness of fits, are also reported. ............................................................................................... 243 Figure 8.26 Figure S8.12 Sodium leaching by charge neutralization (sodium formate formation) (a) attack on surface Na+ cation by formate ion (b) HCOONa formation (c) reactive/non-reactive diffusion of HCOONa to bulk fluid. .......................................... 244 Figure 8.27 Figure S8.13 HCOONa concentration as a function of time in different regions (edge, interlayer, and facet) of Na-montmorillonite for various fluid environments (water + formic acid (1:1) and formic acid). ................................................................ 245 Figure 8.28 Figure S8.14 Carbon monoxide formation reaction. (a) Bond stretching in HCOOH molecule, (b) formation of intermediate species (CO, OH-, H+), and (c) formation of CO and water. .......................................................................................... 246 Figure 8.29 Figure S8.15 NaHCO3 concentration as a function of time in different regions (edge, interlayer, and facet) of Na-montmorillonite for water + formic acid (1:1) environment. ................................................................................................................. 247 Figure 8.30 Figure S8.16 Na2CO3 concentration as a function of time in different regions (edge, interlayer, and facet) of Na-montmorillonite for water + formic acid (1:1) environment. ................................................................................................................. 248 Figure 8.31 Figure S8.17 Carbonic acid (H2CO3) dissociation to bicarbonate ions (HCO - 3 ) and proton (H+) where (a) represents O-H bond stretch in H2CO3, and (b) represents the formation of HCO -3 and H + ions. ................................................................................. 249 Figure 8.32 Figure S8.19 Dissociation of bicarbonate ion (HCO -3 ) into carbonate ion (CO 2-3 ) and proton (H +) where (a) represent the O-H bond stretch in H2CO3, and (b) represents the formation of CO 2-3 and H + ions. ............................................................ 250 Figure 9.1 Schematic representation for (a) synthesis of silica nanochannels in alumina membranes, and (b) the formation of solid carbonates in silica nanochannels. (c) Radial distribution functions (RDFs) for Ca2+-Ocarbonate species ‘at the pore surface’ and ‘pore center’ obtained from molecular dynamics simulations, and the corresponding snapshots of the simulations. ........................................................................................................ 256 xxvi Figure 9.2 Schematic representation of steps involved in the synthesis of silica nanochannels (SNCs) inside the alumina membrane. .................................................. 258 Figure 9.3 Snapshots of the initial configurations of (a) bulk and (b) confined CaCO3 solutions in cylindrical silica nanopores with diameter of 3.7 nm. Calcium and carbonate atoms are shown in VDW drawing method while water and silica atoms are shown in Lines drawing method implemented in VMD software. .............................................. 260 Figure 9.4 (a) Silica nanochannels (SNCs) formed inside the alumina membrane as viewed using Scanning Electron Microscopy (SEM) after the dissolution of alumina membrane using 10 wt.% H3PO4. (b) High-resolution imaging of SNCs using Transmission Electron Microscope (TEM). (c) The pore size distribution of SNCs determined using N2 adsorption-desorption measurements. ........................................ 262 Figure 9.5 (a) Identification of stable calcite phases inside silica nanochannels (SNCs) acquired at different time intervals using X-ray Diffraction (XRD). (b) Crystallite sizes determined using Scherrer equation. (c) Schematic representation of calcite structure and growing (104) and (214) plane projected along the [441] zone axis.547 ....................... 264 Figure 9.6 Radial distribution function [g(r)] as a function of radius. (a) Calcium (Ca2+)- water oxygen (OW) in bulk fluid. Inset: water in the first coordination shell of Ca 2+ ion. (b) Ca2+-carbonate oxygen (OR) in bulk fluid. Inset: carbonate in the first coordination shell of Ca2+ ion. (c) Ca2+- OW in confinement (silica nanochannel). (d) Ca 2+- OR in confinement. Insets in (c & d): Ca2+ and CO 2-3 ions in the pore center and at pore surface. ...................................................................................................................................... 267 Figure 9.7 Coordination number [n(r)] as a function of radius. (a) Calcium (Ca2+)-water oxygen (OW) in bulk fluid. (b) Ca 2+-carbonate oxygen (OR) in bulk fluid. (c) Ca 2+- OW in confinement (silica nanochannel). (d) Ca2+- OR in confinement. ................................. 269 Figure 9.8 Figure S9.1. Estimation of weight changes using thermogravimetric analysis (TGA). (a) Changes in the weight loss of the as-received anodic alumina membrane (AAM) and silica nanochannels (SNCs) prepared using the sol-gel approach. Weight loss at 250 °C corresponds to CTAB removal from SNCs. (b) Changes in the weight associated with the dissociation of calcium carbonate formed in SNCs. ..................... 272 Figure 9.9 Figure S9.2. Loading of Ca2+ and CO 2-3 containing solutions in silica nanochannels. Schematic representation of sample preparation approach for carbonate formation inside silica nanochannels and organization of the formed carbonate crystals. ...................................................................................................................................... 273 Figure 9.10 Figure S9.3. Characterization of the as-received Anodic Alumina Membrane (AAM). (a) The amorphous structure of the as-received anodic alumina membrane (AAM) determined using XRD. (b) Morphology of as-received membrane imaged using SEM. ............................................................................................................................. 274 Figure 9.11 Figure S9.4. X-ray diffraction (XRD) patterns of different polymorphs of calcium carbonate. Identification of different planes in polymorphs of calcium carbonate xxvii (CaCO3) as reported in the American Mineralogist Crystal Structure Database (AMCSD). (a) XRD pattern of calcite. (b) Aragonite. (c) vaterite. The referred AMCSD datasets are also mentioned. ............................................................................................................. 275 xxviii LIST OF TABLES Table 3.1 Lattice parameters, pore sizes, wall thicknesses, surface areas, and pore volumes for M-1 and M-2. Lattice parameters were calculated from the first peaks (q(100)) in SAXS curves. Pore size distributions, surface area and pore volumes were determined from N2 adsorption-desorption isotherms. The wall thickness was calculated by subtracting the average pore size from lattice parameter. .............................................. 50 Table 3.2 Table S3.1. Functional groups present on as-synthesized M-1 and M-2 ....... 66 Table 3.3 Table S3.2. Small Angle X-ray Scattering (SAXS) parameters ..................... 67 Table 3.4 Table S3.3. Ratios of observed q values for as-synthesized SAXS curves of M- 1 and M-2 ....................................................................................................................... 68 Table 3.5 Table S3.4 Parameters used while performing Core-Shell model fitting on M- 1 GI-SAXS experimental data for micelles .................................................................... 69 Table 4.1 A summary of similarities between the structural transformations in kaolinite and halloysite during thermal treatment ......................................................................... 81 Table 5.1 IR band assignments for different observed functional groups. ................... 115 Table 6.1 Parameters extracted from SAXS and GI-SAXS modeling of data. ............ 140 Table 6.2 Calculation of Number of Aggregates (Nagg) from structure factor (S(q)) parameters. .................................................................................................................... 145 Table 6.3 Table S6.1 The forcefield parameters used to model the quartz surface, and water molecules. ........................................................................................................... 153 Table 7.1 Estimated chemical compositions of Frontier, Niobrara, and Mowry shale samples used in the study. ............................................................................................ 164 Table 7.2 Specific surface areas, pore volumes, and pore sizes for unreacted and reacted shale samples were determined using the BJH method from N2 desorption isotherms. ...................................................................................................................................... 180 Table 7.3 Table S7.1. Classification of different silicate units and corresponding non- bridging oxygens (NBOs).406 ........................................................................................ 190 Table 7.4 Table S7.2. Densities and X-ray scattering length densities (SLDs) for different components present in the shale samples. .................................................................... 194 Table 7.5 Table S7.3. Bands in the IR spectra.412–414 ................................................... 196 Table 8.1 Summary of interfacial and speciation reactions observed in ReaxFF/MD simulations. ................................................................................................................... 229 Table 9.1 The number of water oxygen (OWater) and carbonate oxygens (OCarbonate) in the xxix first coordination shell of Ca2+. Error bars represent the standard deviation from the mean values of three different simulations. ........................................................................... 267 Table 9.2 The self-diffusion coefficient (10-5 cm2/sec) of Ca2+, CO 2-3 and water in bulk and in confined systems. Error bars represent the standard deviation from the mean values of three different simulations. ....................................................................................... 268 Table 9.3 Table S9.1. The forcefields parameters of the atoms in silica pores, water molecules, and ions are obtained from the references listed in Ref. column. .............. 276 xxx LIST OF ABBREVIATIONS AAM Anodic Alumina Membrane ACC Amorphous Calcium Carbonate AMCSD American Mineralogist Crystal Structure Database ANL Argonne National Laboratory APS Advanced Photon Source ATR-FTIR Attenuated Total Reflection Fourier Transform Infrared Spectroscopy BET Brunauer−Emmett−Teller CCMR Cornell Center for Materials Research CGT Crystal Growth Theory CNG Classical Nucleation Growth COD Coefficient of Determination CTAB Cetyl Trimethyl Ammonium Bromide DFT Density Functional Theory DOE Department of Energy EFRC Energy Frontier Research Center EM Electron Microscopy xxxi FESEM Field Emission Scanning Electron Microscopy FWHM Full Width Half Maximum GC Gas Chromatography GI-SAXS Grazing Incidence Small Angle X-ray Scattering GROMACS GROningen Machine for Chemical Simulation HCP Hexagonal Close Packed ICP Inductively Coupled Plasma IUPAC International Union of Pure and Applied Chemistry LAMMPS Large-Scale Atomic/Molecular Massively Parallel Simulator MC Monte Carlo MD Molecular Dynamics NBO Non-Bridging Oxygen NIST National Institute of Standards and Technology NLDFT Non-Local Density Functional Theory OPLS-AA Optimized Potentials for Liquid Simulations – All Atom ORS Object Research System PDF Pair Distribution Function PME Particle Mesh Ewald xxxii RDF Radial Distribution Function ReaxFF Reactive Force Field SANS Small Angle Neutron Scattering SAXS Small Angle X-ray Scattering SEM Scanning Electron Microscopy SLD Scattering Length Density SNC Silica Nanochannel SPC/E Extended Simple Point Charge model TE Track Etch TEM Transmission Electron Microscopy TEOS Tetraethoxysilicate TGA Thermogravimetric Analysis TOC Total Organic Content USAXS Ultra-Small Angle X-ray Scattering WAXS Wide Angle X-ray Scattering XCT X-ray Computed Tomography XRD X-ray Diffraction xxxiii 1 INTRODUCTION The need to rapidly stabilize rising temperatures while meeting our energy and resource needs require advances in sustainable subsurface energy technologies such as carbon storage,1,2 and nuclear waste storage.3 Unconventional approaches to harness tight gas and shale reservoirs4 for recovering metals or storing fluids require us to shed fundamental insights into the reactive interactions in these environments. Furthermore, fundamental fluid-solid interactions can unlock the potential of geothermal energy to generate up to billions of watts of electrical power.5 However, utilizing the subsurface for storage offers many technical and scientific challenges due to the complexities in these environments, particularly related to the chemical and morphological heterogeneities in subsurface reservoirs. Reactive interactions such as dissolution and crystallization of new phases alter pore spaces, permeability, and flow paths. During the past decade, the US Department of Energy (DOE) has emphasized understanding the rock structures of subsurface reservoirs, particularly the morphology of nanopores, their permeability, and reactivity.5 Therefore, to harness the full potential of the subsurface environments, a fundamental understanding of how the morphologies in the subsurface environment evolve and the feedback effects of reactivity on morphology is essential. This calibrated understanding is essential for developing predictive controls on the fate and transport of stored fluids in subsurface environments. Thus, the scientific grand challenge is to develop tunable controls on the role of reactivity and changes in pore morphology, and fate and transport of stored species at representative subsurface conditions.6–10 The design of geo-architected materials with controlled pore morphologies can help to develop a reproducible understanding of these behaviors. These materials, with repeatable and 1 controlled heterogeneity and structure, can also be used as model materials to study various fluid and materials properties.11–13 Siliceous materials in unconventional subsurface reservoirs primarily consist of silicates and aluminosilicates with abundant micro- and mesopores. At these extremely small length scales of pores, the known understanding of the properties of thermodynamics,6,13–19 transport,6–10,20,21 and reactivity6,22–24 of bulk fluids differs significantly from those of confined fluids. Developing fundamental insights into the role of confinement requires us to develop materials with well-controlled pore architectures and particle morphologies. Among several approaches to produce geo-architected siliceous materials, sol-gel colloidal synthesis is widely used to architect materials having ordered pore structures, such as SBA-15, MCM-41, and MCM-48.25,26 To develop mechanistic controls on the synthesis of these materials via colloidal approaches and delineate the effects of chemical or thermal perturbations, advances in experimental methods to probe the evolution of matter in real-time is necessary. However, the architecture of these materials with specific pore and particle morphologies requires us to tune the experimental conditions to understand the chemical27,28 and structural29–32 changes during the formation of mesoporous silica interfaces. Moreover, the thermal perturbations can cause changes in pore morphologies of silica particles formed from colloidal approaches. Understanding these changes is crucial for achieving tunable controls over the morphology of the nanoscale confinements in siliceous materials to investigate the effects of confinement on fluid properties related to transport,6–10,20 thermodynamics,6,15,16,18,19 and reactivity.22–24,33–36 Furthermore, clays having predominant layered aluminosilicate skeleton with hierarchical morphologies have also 2 been used for applications related to carbon,37–44 and radioactive nuclear waste storage.3,45 In this context, halloysite and kaolinite are among the widely studied aluminosilicates having similar chemical compositions (Al2Si2O5(OH)4). 46–50 The major difference between both clays is noted in their morphologies, where kaolinite has platelet sheets46,49 while halloysite is made of rolled sheets to form tubular particles with the diameter of inner hollow tube ~10 – 15 nm.47,48,50–53 To investigate the effects of nanoscale confinement, understanding the structural and microstructural evolution in these materials is essential, which can then inform how understanding interfaces with similar chemistries but different morphologies influences fluid properties. In the context of carbon storage in subsurface environments or utilizing the subsurface chemistry to extract resources from unconventional reservoirs54,55 assisted by carbon dioxide,56–58 the development of material systems is crucial. Such material systems, with tunable properties to achieve desired results, can use carbon dioxide and absorb small gaseous molecules in the chains of task-specific functional groups. However, the use of such systems in the subsurface-related chemistries (siliceous interfaces) remains less explored. Moreover, understanding the thermodynamics and kinetics of self-assembly of macromolecules, analogous to additives used during resource recovery and heavy hydrocarbons, at subsurface interfaces is of technical interest to develop efficient systems. These macromolecules tend to assemble in a range of nanoscale morphologies, depending on the surrounding environments.59–71 The morphologies and structures of these assembled molecules can significantly influence the properties of fluids in the subsurface and need to be understood. The storage of carbon dioxide in subsurface reservoirs is proposed in the 3 unconventional reservoirs (shales)1,72–79 after the extraction of hydrocarbons. The extraction is usually done via hydraulic fracturing80, and often to circumvent the requirements of high-pressures needed for hydraulic fracturing, acid fracturing (acidizing) is applied to increase the permeability of the reservoirs.81–84 This pre- treatment can alter the mineralogy of the reservoir by dissolving different phases. Shales mainly comprise siliceous phases (silica), clay-bearing phases, and carbonaceous phases. Clay and carbonaceous phases in these reservoirs are further impacted by acid treatment. The dissolution of these phases can further result in unanticipated changes in the chemistry and morphologies of pores in the reservoirs, which can have long-term implications on the fate of stored carbon dioxide. Therefore, it is essential to delineate the feedback effects of reactivity on the morphological and mineralogical evolution in these siliceous interfaces to develop better controls on the formation of carbonate phases within these reservoirs. Further, the fluid-solid interactions in aluminosilicate clay minerals are of importance to develop a basic understanding of the evolution of mineralogy in subsurface-related chemistries. Swelling clays with exchangeable cations, such as montmorillonite clays are of interest since these are found as the weathering products of intermediate and mafic rocks.85,86 In this context, reactions of montmorillonite clays in aqueous and organic environments are of particular interest since various forms of organic matter including aliphatic and aromatic hydrocarbons, carboxylic acids, and alcohols can exist in these formations.87,88 Moreover, the hierarchical 2D structure of montmorillonite clays and the presence of interlayer cations can result in different chemical interactions at the edge, facet, or basal plane in these clays.89 The reactions between montmorillonite clays and water or organic acids can lead to the formation of 4 carbonates, which may precipitate in the interlayers of these clays.90,91 The formation of these species contributes to morphological and structural alteration in clays in subsurface reservoirs,90–94 which are important to be understood before considering these as potential resources to permanently store CO2 or other fluids. Permanent storage of CO2 via carbon mineralization in subsurface environments95–97 including in reactive formations rich in basalt98 and olivine99 can limit the need to monitor the fate of mobile CO2. However, estimating the actual time scales of carbon mineralization in these formations is still a challenge due to the anomalous reactivity induced by nanoconfinement in subsurface reservoirs.100,101 Some of the key challenges lie in estimating the rates of carbon mineralization and uncertainties associated with the formation of specific carbonate phases due to nanoscale confinement of fluids in pores smaller than 20 nm102 in the olivine and basalt. To understand these mechanisms and delineate the confinement-mediated carbon mineralization behavior, model materials, representative of subsurface environments, need to be developed and the fate of formed carbonates in these materials needs to be investigated. Recent advances in non-invasive cross-scale advanced characterization tools and computational models now enable us to probe thermally or chemically induced transformations in the structure and morphology of natural and representative architected materials.46,49,103–110 Given the knowledge gaps, and scientific and technical challenges in developing calibrated understandings of the phenomenon in the subsurface, the research objectives of this dissertation are four-fold: (i) design and understanding of structural and microstructural evolution in architected and natural siliceous materials, (ii) functionalize siliceous materials for tunable rheological behavior via CO2 capture, (iii) elucidate the 5 self-assembly of macromolecules at siliceous interfaces, and (iv) probe the influence of nanoscale confinement on the formation of specific carbonate phases in architected siliceous nanochannels. The contents of this dissertation are organized into different chapters as discussed below. Chapter 2 discusses the thermally induced morphological evolution of geo- architected spherical silica nanoparticles (220 ± 30 nm in diameter) using in-operando Ultra-Small and Small Angle X-Ray Scattering (USAXS/SAXS) measurements during calcination (600 °C) and sintering (1050 °C) processes. Upon calcination, the pore radii remained in the range of 2.15 nm – 2.35 nm and the particle diameters in the range of 220 ± 30 nm. Sintering these calcined silica nanoparticles to temperatures up to 1050 °C reduced the pore size from 2.2 ± 0.1 nm to ∼1.8 ± 0.2 nm. These changes corresponded to the formation of siloxane (Si-O-Si) bridges resulting from dehydroxylation. Chapter 3 reports the structural and chemical transformations associated with the formation of mesoporous silica particles, SBA-15 using in-operando SAXS, Grazing Incidence-Small Angle X-ray Scattering (GI-SAXS), and Attenuated Total Reflection – Fourier Transform Infrared Spectroscopy (ATR-FTIR) measurements. The effect of magnesium nitrate salt on the polymerization of Si-O-Si species during the formation of mesoporous silica is investigated. The “salting-in” effect or enhanced solubility of polymers, induced by salts accelerates the polymerization and nucleation of silica particles. The aging of silica particles in the synthesis solution results in plate-like morphologies in the absence of nitrate salt and spherical morphologies in the presence of nitrate salt. 6 Chapter 4 investigates the chemo-morphological evolution of nanotubular aluminosilicate (halloysite) and contrasts the results with those for planar aluminosilicate (kaolinite). Four distinct stages in the structural evolution are identified between the temperature range of 25 °C to 875 °C using in-operando USAXS/SAXS and Wide-Angle X-ray Scattering (WAXS) measurements. Major structural changes correspond to the removal of interlayer/adsorbed water in stage I, the existence of the halloysite structure without interlayer water in stage II, dehydroxylation of halloysite in stage III, and the conversion of ordered halloysite to amorphous meta-halloysite in stage IV. Heating halloysite to 875 °C results in a slight widening of the nanotubes as the average pore radius increases from 6.4 nm to 6.6 nm. Heating also resulted in an increase in wall thickness of the nanotubes from ∼120 nm to 161 nm. The interlayer basal spacing in halloysite changes from 9.8 Å to 7.2 Å after the removal of interlayer water. In contrast, the interlayer spacing in kaolinite collapses on heating which reduces the nanoscale porosity. The pore sizes in halloysite nanotubes are also confirmed using N2 adsorption- desorption and nano-X-ray computed tomography (nano-XCT) measurements. Chapter 5 discusses the development of multifunctional nanofluids constructed from silica (SiO2) nanoparticles and poly(allylamine) (PAA), amine-bearing polymer chains with a high affinity for CO2. A 2-fold increase in CO2 absorption in SiO2–PAA nanofluids compared to the pure polymer was noted. Upon CO2 absorption, the weakly interacting polymeric chains around the nanoparticles formed relatively compact hydrogels. Time-resolved USAXS/SAXS scattering measurements showed the transition from swollen branched polymers to Gaussian coils with increased exposure to CO2. Further, CO2–induced hydrogel formation in aqueous fluids bearing 1 wt % SiO2–PAA 7 nanofluids occurred at room temperature, unlike in fluids bearing 1 wt % PAA. These observations point to the feasibility of forming hydrogels at lower temperatures and pressures using novel nanofluids as opposed to using the pure polymer. Chapter 6 probes the organization of cetyltrimethylammonium bromide (CTAB) micelles in the absence and presence of the Pluronic P123 block copolymer and quartz substrate using transmission and grazing-incidence SAXS measurements and classical molecular dynamics (MD) simulations. In the absence of the quartz interface, CTAB with and without P123 molecules assemble as ellipsoid core-shell micelles. The presence of a quartz substrate causes the micelles to elongate, which is noted by the emergence of a power-law slope in the low q region (<0.02 Å–1). Moreover, in the presence of both P123 and the quartz substrate, the micelle shape changes from the ellipsoid core-shell to cylindrical core-shell, and a significantly higher number of aggregates are formed. The higher number of aggregates and faster aggregation kinetics are linked to the organization of the solvent structures as noted from the MD simulations. Chapter 7 investigates the feedback chemical effects associated with the interactions of 1M hydrochloric acid on the mineralogy and morphology of shales having varying compositions of carbonates, clays, and silica. The dissolution of Si-bearing phases such as clays is noted to be accompanied by precipitation of amorphous SiO2 species, where the effect is significant in silica-rich and carbonate/clay lean shale, compared to silica, carbonate, and clay-bearing, and silica-lean and carbonate/clay-rich shales. Moreover, significant increases in the pore volume and surface area are noted in reacted shales with high content of clays and carbonates. Non-monotonic changes in the porosity of silica-rich and carbonate/clay lean due to the initial mobilization of silica 8 followed by reprecipitation are noted using in-situ X-ray microtomography experiments. Chapter 8 reports the speciation behavior of water–formic acid mixtures on sodium montmorillonite (Na-MM) interfaces at 473 K and 1 atm using ReaxFF reactive MD simulations in conjunction with IR spectroscopy and USAXS/SAXS/WAXS measurements. The experimental IR spectra of unreacted and reacted mixtures are accurately reproduced by ReaxFF/MD. The speciation reactions of carbonate, formate and hydroxide groups are investigated to delineate the differences in reactivities and catalytic effects of Na-MM clay edges, facets, and interlayers owing to their local chemical environments. Chapter 9 reports the preferential formation of stable calcium carbonate in nanosized silica channels (dia. = 3.7 nm) over metastable aragonite and vaterite phases. From MD simulations, we note relatively fewer waters of hydration and a higher number of carbonate ions surrounding calcium ion (Ca2+) in confinement compared to bulk fluid. These conditions suggest the formation of stable carbonates, which is favorable for the permanent storage of CO2 especially in silica-rich reservoirs. Finally, the key outcomes of the performed studies and recommendations for future work are summarized and presented in Chapter 10. 9 2 THERMALLY-INDUCED MORPHOLOGICAL EVOLUTION OF SPHERICAL SILICA NANOPARTICLES USING IN-OPERANDO X-RAY SCATTERING MEASUREMENTS The contents of this chapter have been published as a journal article: H. Asgar, V. Semeykina, M. Hunt, S. Mohammed, I. Kuzmenko, I. Zharov, and G. Gadikota, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2020, 586, 124260 2.1 INTRODUCTION Our known understanding of the properties of thermodynamics,6,13–19 transport,6– 10,20,21 and reactivity6,22–24 of bulk fluids differs significantly from that of confined fluids. These fundamental differences in fluid properties in bulk and confined environments can be harnessed to design novel pathways for separations,111–115 and the targeted recovery116,117 or storage of fluids118–120 in natural and engineered environments. To advance a calibrated understanding of these differences, developing design controls on pore architectures is essential. Specifically, our ability to harness and in some cases, transform the morphology of siliceous and carbonaceous materials has yielded several advancements in subsurface and engineered processes. Specific examples include harnessing silica-rich rocks such as sandstone for carbon storage,121–128 recovery of hydrocarbons from carbonate-bearing rocks,129–131 developing novel carbon132–135 or silica-based materials136–139 for gas separations and conversions, and advancing the next generation of electronic materials and electrochemical systems.140–144 Another challenge that needs to be overcome in the targeted design of porous materials is to develop an alternative approach to the repeated and iterative synthesis of materials till the target morphology and chemistry is achieved. Instead, in-operando analyses of the chemical and morphological features allow us to identify the underlying phenomena and design scientifically informed pathways to tune the morphologies and 10 chemistries of porous materials. This research vision has guided the use of non-invasive in-operando characterization approaches to elucidate the development of pore structures in architected siliceous materials. In this study, Stöber silica synthesized through ammonia-catalyzed sol-gel process145–150 is one of the material systems of interest for determining fluid properties in confinement. Extensive research efforts have enabled tunable controls on the morphologies of silica nanoparticles by changing the aqueous chemistry151–159 and by heating.160,161 Briefly, reactions 2.1 – 2.4 are involved in the synthesis of monodisperse silica nanoparticles using the Stöber process with tetraethoxysilicate (TEOS) as silica precursor.162–166 The synthesis reaction begins with the hydrolysis of ethoxy group to form Si(OC2H5)4-x (OH)x intermediate species, where the hydroxyl group substitutes the ethoxy groups in TEOS as given in reaction (2.1). The ammonia present in the solution acts as a basic catalyst and provides the hydroxyl anions to initiate the reaction. The hydrolysis reaction is followed by the condensation reaction. The condensation reaction could follow the two schemes. The reaction of hydroxyl groups in Si(OC2H5)4-x (OH)x intermediate with either the ethoxy groups of other TEOS, called alcohol condensation, or hydroxyl group of another hydrolysis intermediate, known as water condensation, to form Si-O-Si bridges. Both condensation reactions are presented in reactions (2.2) and (2.3), respectively. The overall reaction explaining the synthesis of silica nanoparticles from Stöber process is shown in reaction (2.4). Si(OC2H5)4 + xH2O → Si(OC2H5)4-x (OH)x + xC2H5OH (2.1) ≡Si-OC2H5 + HO-Si≡ → ≡Si-O-Si≡ + C2H5OH (2.2) ≡Si-OH + HO-Si≡ → ≡Si-O-Si≡ + H2O (2.3) The overall reaction is: 11 Si(OC2H5)4 + 2H2O → SiO2 + 4C2H5OH (2.4) While there is extensive understanding of how the solid silica nanoparticles are formed starting from colloidal systems,149–159,167–170 there is a limited understanding of how the microstructures of silica nanoparticles evolve during the calcination and sintering of these materials. Understanding these behaviors will allow us to utilize these silica nanoparticles as building blocks to construct geo-architected materials with repeatable heterogeneity to represent naturally occurring materials. Sintering is one of the steps involved in designing geo-architected materials.171,172 To deconstruct the dynamic morphological changes as they occur in these materials, the following research questions need to be addressed: (1) How do the pore sizes dynamically change during the calcination and sintering of silica nanoparticles prepared using the Stöber process? (2) What are the corresponding chemical changes associated with the evolving morphological features? To elucidate thermally induced morphological changes that occur in these materials, we harness in-operando synchrotron based Ultra-Small Angle X-ray Scattering (USAXS) and Small Angle X-Ray Scattering (SAXS) techniques in combination (described as USAXS/SAXS).89,104,107 This approach allows us to map the morphological features from sub-nanometer range to a few microns (~6 µm).173,174 The changes in the pore size distribution and surface area were also measured using N2 adsorption. The relatively fast scans to the order of three to five minutes allow us to capture the in- operando changes in the morphological features. The chemical changes as a result of the thermal treatment are determined using Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR). In this study, we evaluate the hypothesis that 12 sintering of silica nanoparticles yields smaller and compact pores. The experimental approach and the results are discussed in the following sections. 2.2 MATERIALS AND METHODS 2.2.1 Synthesis of SiO2 Nanoparticles Monodisperse silica particles with a diameter of 220 ± 30 nm were prepared by the modified Stöber method. Briefly, 11 ml of tetraethoxysilicate (TEOS, Alfa Aesar, 99+ %) was added to 114 ml of absolute ethanol (Decon Labs) under rigorous stirring at room temperature (~20 °C) in a 500 ml flat-bottomed flask. In a separate flask, a mixture of 7 ml of ammonia (VWR Chemical, 28 wt.% aqueous solution, ACS grade), 72 ml of deionized water, and 46 ml of ethanol was prepared. The latter solution was added to the former mixture rapidly and stirring constantly for 24 hours. Silica nanoparticles were separated from the solution via centrifugation at the acceleration force of 5000×g. Finally, the nanoparticles were washed with deionized water until neutral pH was reached. The silica nanoparticles were dried in a vacuum oven for 24 hours at room temperature. 2.2.2 Experimental Setup and Characterization The in-operando USAXS/SAXS measurements were performed to determine the morphological changes during the thermal treatment of silica nanoparticles. The measurements were performed at Sector 9-ID at Advanced Photon Source (APS) in Argonne National Laboratory (ANL), Argonne, IL using the original Bonse-Hart double- crystal setup.175,176 During the measurements, the total X-ray flux, energy, and wavelength at the sample position were ~1013 photon cm-2 s−1, 21.0 keV, and 0.59 Å, respectively. Instrument calibrations were performed using silver behenate.177 Nika178 and Irena179 macros embedded in the IgorPro software (Wavemetrics, Lake Oswego, OR) were used for data reduction and analysis. The in-operando measurements were 13 performed in the Linkam TS1500 heating stage (Linkam Scientific Instruments Ltd., Tadworth, UK) and completed in two steps. In the first step, the pelletized sample was heated up to the calcination temperature (600 °C) with a temperature ramp of 5 °C/min and then isothermally heated for 4 hours. In the second step, following the calcination, the sample was cooled down to 35 °C and then reheated to 1050 °C with a ramp of 5 °C/min following the isothermal sintering at 1050 °C. To capture the hierarchical morphological features in these materials, the USAXS/SAXS data were modeled using the “Modeling II” tool in Irena package.179 For this purpose, three levels of fittings were performed in three different q regions, where q = (4π/λ)sin(θ/2) and λ is the wavelength of incident X-ray and θ is the scattering angle.180 In the low q-region (<0.002 Å-1), which represents the scattering response of larger microstructural features to the order of several hundred nanometers or a few micrometers, unified fit model was employed. This model is based on the approach proposed by Beaucage.181,182 The fit in each level can be described by a Guinier regime and a power- law regime. Although the model assumes spherical and centrosymmetric shape of particles,182 it can be applied to a range of scatterer shapes, like spheres, rods, lamellae, and cylinders, based on its formulation in terms of radius of gyration (Rg) and free power- law slope. In the second region, the medium q-range of 0.002 – 0.03 Å-1, the intensity profile was dominated by the scattering from the individual nanoparticles. The scattering profiles in this region were fitted by utilizing the size-distribution model in modeling II.179 Finally, in the high q-region (0.03 – 0.7 Å-1), unified fit model181,182 was employed. In the low q part of this region, a plateau is observed which defines a Guinier regime, therefore the size of the scatterers (in this case, the micropores and fractals) were also approximated 14 along with the power-law profile. Figure 2.1 is a schematic representation of these morphological features that correspond to the combined USAXS/SAXS data. Figure 2.1 Representative ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental curve of SiO2 nanoparticles. The curve is divided into three different regions which were modeled to obtain the information about the physical features of interest. The changes in the short- and long-range bond order in silica nanoparticles that correspond to the observed microstructural features were probed using the pair distribution function (PDF) analysis from total X-ray scattering measurements. These data were acquired during the in-operando thermal treatment of silica nanoparticles up to 15 600 °C. The total scattering experiments were performed at Sector 11 of APS at Argonne National Laboratory using beamline 11-ID-B. The total scattering from the sample was recorded at an amorphous silicon-based area detector, 2048 × 2048 pixel Perkin-Elmer183 with a sample-to-detector distance of ~16 cm. Calibrations for sample to detector distance, beam energy, beam center and nonorthogonality were performed using a cerium dioxide (CeO2) standard (NIST diffraction intensity standard set 467a). 184 The measurements were performed with an X-ray energy and wavelength of 58.6 keV and 0.2113 Å, respectively. After background and Compton scattering corrections, the PDFs were obtained using the xPDFsuite software.185 To evaluate changes in the chemical bonding during thermal treatment processes, infrared (IR) spectra were acquired in an Attenuated Total Reflection (ATR) mode using an Attenuated Total Reflection-Fourier Transform Infrared spectrometer (ATR-FTIR, NicoletTM iSTM 10, Waltham, MA) for samples treated at different temperatures (100, 150, 200, 300, 400, 500 600, 1050 °C). The spectra were collected in the range of 4000−650 cm−1 with total number of 32 scans for each run. The changes in the weight % of the silica nanoparticles during heat treatment were evaluated up to 600 °C and 955 °C for calcination and sintering, respectively, with a ramp rate of 5 °C/min in an N2 environment (purged at 25 mL/min) using a Thermogravimetric Analyzer (TGA, TA Instruments, Q550, New Castle, DE). Additionally, the pore size distribution and specific surface areas of silica nanoparticles were determined using the nonlocal density functional theory (NLDFT, Quantachrome NOVAtouch Analyzer, Boynton Beach, FL) by 77 K N2 adsorption. These measurements coupled with the X-ray scattering data provided detailed insights into the evolution of the pore morphology during the 16 calcination and sintering processes. Untreated, calcined, and sintered silica nanoparticles were also imaged using a scanning electron microscope (Hitachi S3400 VP-SEM). 2.3 RESULTS AND DISCUSSION 2.3.1 Evolution of Pore Morphology during the Calcination Process The synthesis of model architected materials from spherical silica nanoparticles is a two-step process in which the particles are calcined at temperatures of 600 °C followed by sintering. The rationale for this approach is that calcination removes the functional groups such as ethoxy groups, and adsorbed water and NH3 that may remain after the colloidal synthesis of these materials.186 Sintering of these materials then could yield the interlinked nanoparticles with the micropore morphology representative of the geo-architected materials. The limited understanding of the in-operando evolution of the morphologies of these materials motivates the use of non-invasive cross-scale characterization of the morphologies of these materials using Ultra Small and Small Angle X-Ray Scattering (USAXS/SAXS) measurements. The USAXS/SAXS experimental data during the calcination process is presented in Figure 2.2. During the ramp to calcination temperature (Figure 2.2 (a)), the intensity of the scattering curves (at q > 10-1 Å-1) increases with temperature suggesting an increase in the number of scattering objects in this q regime.187 17 Figure 2.2 Ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental data represent changes in the microstructural features of SiO2 nanoparticles during heating to calcination temperature (a) and during calcination at 600 °C (b). However, during the isothermal heating at 600 °C, the calcination step, no significant changes in the scattering curves were noted. Additionally, the peak in the higher q-region at q = 1.45 Å-1 which corresponds to the (100) atomic plane in SiO2 and d-spacing of 4.32 Å remained almost unchanged during the calcination stage.157 As explained earlier, the experimental USAXS/SAXS data were modeled using the Modeling II tool in Irena program.179 Representative fits for different SiO2 nanoparticle samples are presented in Figure S2.1. To describe briefly, in the low q-region (<0.002 Å- 18 1), where no Guinier plateau regime is observed, the power-law exponents were obtained by setting the G value to zero187 and keeping the power-law exponent as a free fitting parameter. It can be seen from Figure 2.2 that scattering in this region does not change significantly and no appreciable changes in the power-law values were noted as presented in Figure S2.2. Therefore, the information from this region is not discussed further. In the medium q-region (0.002 – 0.03 Å-1), the effect of thermal treatment on the size of individual nanoparticles was approximated by particle size distribution model. Gaussian type distribution was used to fit the model while utilizing the form factor of spheroid (aspect ratio = 1). In addition to the form factor, a structure factor for hard spheres was also incorporated in the approximation to fit the scattering profiles in the low q regime of this region. Particle radius and volume fraction were set as free parameters for approximation in this range. Finally, the unified fit model was used to approximate the scattering features in the high q-region (0.03 – 0.7 Å-1). The plateau in this regime was fitted with a Guinier fit and the following higher q-range was approximated by the power- law exponent. The radius of gyration (Rg) obtained from the Guinier regime provided insights into the sizes of the nanometer sized pores in the nanoparticles while the power- law exponent provided information about the fractals present at the pore-solid interface.181,182 Additional details regarding Modeling II and complementary microstructural modeling fits are described by Ilavsky and Jemian176,179,187 and Lee and co-workers.174 The particle size volume fraction distribution and power-law slopes obtained from the modeling of experimental data during the calcination step are presented in Figure 2.3. 19 The average size (radius) of nanoparticles slightly decreased from 127 nm to 122 nm during heating to calcination Figure 2.3 (a-1). The spherical morphologies of these particles are noted from the SEM images of the untreated and calcined silica particles shown in the insets of Figures 2.3 (a-1) and (a-2), respectively. Figure 2.3 Particle size volume fraction distributions of silica nanoparticles approximated in the q-range of 0.002-0.03 Å-1 on heating to calcination temperature (a- 1) and during the calcination process (a-2). The changes in the pore morphology in the q- range of 0.03-0.7 Å-1 as represented by the characteristic radius of gyration (Rg) (black curve) and the power-law slope (red curve) during the temperature ramp to achieve the calcination temperature (b-1) and at the calcination temperature (b-2). The error bars on Rg values and power-law slopes correspond to 3% of error in calculated values. The insets in (a-1) and (a-2) represent the corresponding scanning electron micrographs. Analyses of the morphological features in the q-region of 0.03 – 0.7 Å-1 showed 20 that the representative pore dimension of the spherical particles is to the order of 2.3 nm and does not change significantly during the calcination process. Further, the power law slopes determined from the unified fit tool show that the changes in the pore-solid interfaces decreases from 2.9 to 2.35 on heating from 35 °C to 600 °C, which corresponds to dehydroxylation.186,188–190 These mass fractal features are representative of pore-solid features in analogous siliceous materials.191 The USAXS/SAXS experimental data were compared with N2 adsorption- desorption measurements for untreated, calcined and SiO2 nanoparticles treated at 150, 300, 400, and 500 °C. The measured N2 adsorption-desorption isotherms are presented in Figure S2.5. The N2 adsorption isotherms were modeled to obtain the pore size distribution and cumulative pore volumes for the SiO2 nanoparticles using the NLDFT model in Quantachrome software using silica as the adsorbent by 77 K N2 adsorption. The NLDFT modeling provided information about the micro- and mesopores (up to 16 nm) in the nanoparticles. The pore size distribution and cumulative pore volume data are presented in Figure 2.4 for untreated and calcined SiO2 nanoparticles and Figure S2.5 for nanoparticles treated at 150, 300, 400, and 500 °C. The dominance of the pores with radii to the order of 2 nm is consistent with the USAXS/SAXS analyses. It can be noted in Figure 2.4 and Figure S2.6 that the amount of micropores slightly decrease during and after calcination, whereas the cumulative pore volume almost remained constant. The surface areas of the samples were also obtained from the NLDFT model and are reported in Figure S2.7. It was noted that the surface area of the particles decreased from 22.184 m2/g to 19.282 m2/g as a result of calcination. 21 Figure 2.4 Pore size distributions and cumulative pore volumes of untreated (a), and calcined (b) silica nanoparticles. SiO2 nanoparticles were prepared by the modified Stöber method and calcined at 600 °C for 4 hours. The chemical changes that correspond to these morphological features were determined using ATR-FTIR spectra analyses. The morphological changes that correspond to temperatures in range of 25 - 600 °C are associated with the dehydroxylation of SiO2 nanoparticles as indicated by the changes in Si-OH bond around 950 cm-1 in the ATR-FTIR spectra (Figure 2.5). Moreover, the changes in the Si-OH bond observed in IR spectra were related with the % weight changes due to dehydroxylation during calcination as determined by TGA measurements (Figure S2.2). 22 A weight loss of about 8.5% was noted for silica nanoparticles as a result of heating to 600 °C. Figure 2.5 Changes in the Si-OH and Si-O-Si features for SiO2 nanoparticles heated to different temperatures and calcined at 600 °C measured using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR). Bands around 795 cm-1, 950 cm-1, and 1054 cm-1 correspond to Si-O-Si (sym.), Si-OH, and Si-O-Si (asym.) vibrations, respectively. With an increase in temperature, the Si-O-Si asymmetric band broadens while Si-OH vibration band ~950 cm-1 appears to be diminished in the calcined sample as a result of dehydroxylation of silica. We also performed total X-ray scattering experiments to obtain the pair distribution functions (PDFs) of silica nanoparticles during the calcination process. The PDF of a material describes its distribution and density of atomic distances.192,193 PDF can be obtained directly from the total X-ray scattering data by applying a Fourier transform on the reduced structure function S(Q), where Q is the scattering vector. The 23 structure function is related to the PDF (G(r)) directly by: ∞ 𝐺(𝑟) = 4𝜋𝑟 (𝜌(𝑟) − 𝜌 2𝑜) = ⁄𝜋 ∫ 𝑄[𝑆(𝑄) − 1] sin(𝑄𝑟) 𝑑𝑄 (2.5) 0 where r is the interatomic distance, ρ(r) is the microscopic pair density and ρo is the average atomic density of the material.193,194 The PDFs of SiO2 nanoparticles on heating to the calcination temperature of 600 °C are shown in Figure 2.6. The complete dataset for in-operando PDFs is presented in Figure S2.4. In Figure 2.6, the oscillations before the Si-O peak and the two small peaks between the Si-O and O-O peaks are the termination ripples, a common feature in experimental PDF data, which appears as a consequence of limited q range and instrumental contributions.192 In Figure 2.6, we noted that the peak originating from the Si-O interactions observed around 1.61 Å shifted to a slightly smaller bond distance of 1.59 Å after heating to 600 °C. Similarly, the peak for Si-Si interactions noted at 3.08 Å initially became broader during heating and eventually shifted to relatively small value of 2.98 Å. It is well understood that the surface of silica contains silanol (Si-OH) groups186,190 which can be removed upon thermal treatment at temperatures higher than 400 °C through a process called dehydroxylation. During this process, the one OH group and one hydrogen from the adjacent silanol bonds break away to form water as a result of a condensation reaction thus, giving rise to a siloxane Si-O-Si bridge.186 The schematic representing this process is shown in the inset of Figure 2.6 These chemical changes could be a reason of shift and broadening in the Si-O bond peak (Figure 2.6) with increasing temperature. This change in bond lengths for Si-O bond in the first shell could also affect the bond lengths for O-O and Si-Si as noted from our results. 24 Figure 2.6 The pair distribution function (PDF) curves calculated from total X-ray scattering data during the in-operando heating of silica nanoparticles to calcination temperature (600 °C). Inset shows the schematic of dehydroxylation process i.e., breakage of silanol (Si-OH) bonds and formation of new siloxane (Si-O-Si) bridges. 2.3.2 Evolution of Pore Morphology during the Sintering Process To investigate how sintering influences the morphology of the SiO2 nanoparticles, the USAXS/SAXS experiments were performed in two stages. In the first stage, USAXS/SAXS data were collected as the temperatures were ramped from 35 °C to 1050 °C at a rate of 5 °C/min (Figure 2.7). During heating to the temperature of 1050 °C (Figure 2.7 (a)), slight increase in the scattering intensity was observed in the q-range of 0.002 – 0.03 Å-1 until 917 °C. However, in the q-range of 0.03 – 0.7 Å-1, the scattering intensity was observed to be decreasing significantly after 780 °C. This reduction in the scattering intensity could be associated with the decreasing sizes and number of pores during the sintering process. Similar decreasing trends in the scattering intensity during 25 isothermal sintering at 1050 °C were observed for the first 90 minutes after which the scattering intensity almost became constant. Additionally, the diffraction peak at q = 1.45 Å-1 (4.32 Å) for (100) plane157 in SiO2 remained unchanged during the sintering process. Figure 2.7 Ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental data represent changes in the microstructural features of calcined SiO2 nanoparticles during heating to sintering temperature (a) and during sintering at 1050 °C (b). The modeled USAXS/SAXS data during the sintering process are presented in Figure 2.8. Moreover, the particle size volume distribution became narrow and relatively higher after 917 °C (Figure 2.8 (a-1)) with the peak center shifted from 125 nm to 120 nm during isothermal sintering at 1050 °C, the volume fraction distribution remained 26 narrow with the peak center shifted to 118 nm (Figure 2.8 (a-2)). This change in the particle size distribution could be related with the scattering intensity trends discussed earlier and observed in the q-range of 0.002 – 0.03 Å-1 (Figure 2.7). Figure 2.8 Particle size volume fraction distributions of calcined silica nanoparticles on heating to the sintering temperature (a-1) and during the sintering process (a-2) approximated in the q-range of 0.002-0.03 Å-1. The changes in the pore morphology in the q-range of 0.03-0.7 A-1 as represented by the characteristic radius of gyration (Rg) (black curve) and the power-law slope (red curve) during the temperature ramp to achieve sintering temperature (b-1) and at the sintering temperature (b-2). The error bars on Rg and power-law values correspond to 3% of error in calculated values. The inset in (a-2) represent the corresponding scanning electron micrograph. Furthermore, an increasing trend in values of power-law slope was observed after 27 917 °C during the heating step (see the red curve in Figure 2.8 (b-1)). The power-law slope changed slightly from 2.54 to 2.61 during heating from 35°C to 917 °C, however, it achieved the value of 2.73 after heating to 1050 °C. As a result of the isothermal sintering at 1050 °C, the power-law slope finally achieved the value of 2.88 (see the red curve in Figure 2.8 (b-2)). The values of power-law slopes indicated the presence of mass fractals at the pore-solid interface within the nanoparticles. This increase in the power- law slope for mass fractals indicated the emergence of relatively rougher interfaces.103,195 The Rg values, corresponding to the pore sizes, remained almost constant up to 800 °C and decreased on further heating to 1050 °C (see the black curve in Figure 2.8 (b-1)). Figure 2.9 Pore size distribution and cumulative pore volume of sintered SiO2 nanoparticles. SiO2 nanoparticles were prepared by modified Stöber method, calcined at 600 °C for 4 hours and sintered at 1050 °C for 4 hours. The N2 adsorption-desorption isotherms were also obtained for the sintered SiO2 nanoparticles and are presented in Figure 2.9. The adsorption isotherm was modeled to 28 obtain the pore size distribution and cumulative pore volume using the NLDFT model as explained earlier. It can be noted from Figure 2.4, Figure 2.9 and Figure S2.5 that the both the cumulative pore volume and number of micropores decrease significantly after the sintering process. Additionally, the surface area of sintered nanoparticles was measured to be 13.005 m2/g as compared to 22.184 m2/g and 19.282 m2/g for untreated and calcined nanoparticles, respectively. The dominance of pores with radius of ~ 2 nm was observed in N2 adsorption measurements, which agreed well with the X-ray scattering data. The changes in the pore sizes on heating above 800 °C corresponded to the complete dehydroxylation of SiO2 nanoparticles (> 800 °C). 186 The weight loss caused by dehydroxylation was also observed in the TGA curve of calcined nanoparticles during sintering (Figure S2.3). This observation was also confirmed by the IR spectrum of the sintered nanoparticles where the vibrations from Si-OH band completely diminished as a result of sintering (Figure 2.10). During the isothermal sintering stage at 1050 °C, the Rg values slightly increased in the first 100 minutes and then remained almost constant till the end of the stage (see the black curve in Figure 2.8 (b-2)). Based on the changes in the pore dimensions and the corresponding chemical phenomena,186,188–190 a mechanism for the changes in the pore-solid interfaces can be developed. Dehydroxylation of the silanol groups (Si-OH) present on the silica surface yield Si-O-Si siloxane bridges186,190 (see inset of Figure 2.6). Residual Si-OH groups persist after calcination as presented in the ATR-FTIR spectra (Figure 2.5) and TGA data (Figure S2.3). The removal of these residual groups occurs during the secondary dehydroxylation stage at the temperatures higher than 800 °C. 29 Figure 2.10 Comparison of changes in the Si-OH and Si-O-Si features for untreated, calcined and sintered SiO2 nanoparticles measured using Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR). Bands around 795 cm-1, 950 cm- 1, and 1054 cm-1 correspond to Si-O-Si (sym.), Si-OH, and Si-O-Si (asym.) vibrations, respectively. With an increase in temperature, the Si-O-Si asymmetric band broadens while Si-OH vibration band ~950 cm-1 diminishes completely as a result of sintering at 1050 °C. Governed by the breaking and formation of new bonds at high temperatures, the proposed mechanism is presented in the Figure 2.11. Briefly, during heating to sintering step at temperatures higher than 800 °C, the new siloxane bridges (Si-O-Si) forming inside the pores at the pore-solid interface as a result of secondary dehydroxylation could give rise to rougher pore-solid interfaces (as noted from the power-law slope (red curve shown in Figures 2.8 (b-1) and 2.8 (b-2)) and a decrease in the internal pore dimensions. These chemical changes could describe the abrupt decrease in the Rg values from 2.25 nm to 1.84 nm during the heating to sintering step after 800 °C. Furthermore, during the isothermal sintering at 1050 °C, a slight increase in the Rg value (1.98 nm) was noted 30 until the first 90 minutes and remained almost constant during the rest of the sintering stage and finally achieved the value of 2 nm at the end of sintering. This increase in the pore dimensions during the sintering process could be explained by the merging of different pores. Since the USAXS/SAXS signals represent the average scattering from scatterers (in this case pores), the increase in the Rg values could be associated with the increase in the average value. Figure 2.11 Schematic representation of chemo-morphological changes that occurring during sintering of silica nanoparticles. As a result of heating to calcination temperature (600 °C), primary dehydroxylation of -OH groups from silanol (Si-OH) bonds generate siloxane (Si-O-Si) bridges (change from I to II). Heating the calcined nanoparticles to sintering temperature (1050 °C) results in secondary dehydroxylation, which starts after 800 °C where Si-O-Si bridges could form inside the pores (III). 2.4 CONCLUSIONS We present an experimental methodology to elucidate thermally induced morphological evolution during the calcination and sintering of silica nanoaprticles, and the underlying chemical changes associated with these morphological features. The hierarchical morphological organization is captured using USAXS/SAXS measurements. The results of the pore size of the samples on sintering from USAXS/SAXS measurements were quantitatively in good agreement with those obtained from N2- 31 adsorption measurements (NLDFT method). Changes in the short-range bond order during the calcination process are determined using total X-ray scatteirng measurements. The underlying changes in the hydroxylation conditions of silica are captured using ATR- FTIR measurements. Based on the observations from these measurements, a chemo- morphological mechanism that corresponds to the thermal treatment of spherical silica nanoparticles is presented. On heating to the calcination temperature (600 °C), the power-law slope changed from around 2.9 to 2.45, indicating the transition of the pore-solid interface from rough to smooth as a result of dehydroxylation. However, during calcination at 600 °C, no significant changes at the pore-solid interface and Rg were observed, indicating the dehdroxylation of surface silanol groups during this step. Furthermore, during heating of calcined nanoparticles to sintering temperatures as high as 1050 °C, a decrease in the pore size was noted as the temperatures exceeded 800 °C. This decrease was attributed to the formation of Si-O-Si bridges inside the pores as a result of dehydroxylation. Isothermal sintering of the calcined nanoparticles at 1050 °C showed the emergence of slightly large size pore dimensions to the order of 2 nm from as compared to 1.8 nm pores noted at the beginning of sintering step. These morphological insights gleaned from rapid in- operando multi-scale scattering measurements are useful in advancing predictive controls on the synthesis of siliceous materials for a wide range of scientific and engineering applications. 32 2.5 SUPPLEMENTARY MATERIAL Figure 2.12 Figure S2.1 Representative ultra-small and small angle X-ray scattering (USAXS/SAXS) experimental data for untreated (a), calcined (b), and sintered (c) SiO2 nanoparticles. Red lines represent the simulated scattering patterns. The simulated data were obtained using 3 levels of fits using the Modeling II tool in Irena package.179 For low q-region (<0.001 Å-1); unified fit, medium q-range (0.001 – 0.03 Å-1); size distribution and high q-region (0.03 – 0.7 Å-1); unified fit models were used. 33 Figure 2.13 Figure S2.2 Changes in the power-law slope values during the temperature ramp to calcination temperature (a-1), at the calcination temperature (a-2), during the temperature ramp to sintering temperature (b-1) and during the heating at the sintering temperature (b-2). The error bars correspond to 3% of error in the calculated values. 34 Figure 2.14 Figure S2.3 Changes in the weight of the silica nanoparticles with temperature during calcination and sintering using Thermogravimetric Analyses (TGA). During the calcination step, SiO2 nanoparticles which were obtained by modified Stöber process were heated to 600 °C at the ramp rate of 5 °C/min followed by isothermal heating for 4 hours. The calcined particles were then cooled to room temperature and heated to 950 °C (sintering temperature) at the ramp rate of 5 °C/min. 35 Figure 2.15 Figure S2.4 The pair distribution function (PDF) curves calculated from total X-ray scattering data during the in-operando heating of silica nanoparticles to calcination temperature (600 °C). 36 Figure 2.16 Figure S2.5 N2 adsorption-desorption isotherms for untreated (a) and treated at 150 °C (b), 300 °C (c), 400 °C (d), 500 °C (e), calcined (f), and sintered (g) SiO2 nanoparticles. 37 Figure 2.17 Figure S2.6 Pore size distribution and cumulative pore volume for SiO2 nanoparticles treated at 150 °C (a), 300 °C (b), 400 °C (c), and 500 °C (d). The calculations were performed using the DFT model in Quantachrome software using Silica as adsorbate at 77K (liquid N2) and cylindrical/sphere silica pores were modelled on the adsorption isotherm. 38 Figure 2.18 Figure S2.7 Surface areas of different SiO2 nanoparticle samples calculated from the adsorption isotherm using the nonlocal density functional theory (NLDFT) model in Quantachrome software using Silica as adsorbate at 77K (liquid N2) and from the modeling of cylindrical/sphere silica pores. 39 3 MECHANISTIC INSIGHTS INTO THE COLLOIDAL ASSEMBLY OF MESOPOROUS SILICA USING IN-OPERANDO CROSS-SCALE X-RAY SCATTERING AND SPECTROSCOPIC MEASUREMENTS The contents of this chapter have been published as a journal article: H. Asgar, S. Seifert, I. Kuzmenko, M. Bartl, and G. Gadikota, Materialia, 2020, 12, 100764 3.1 INRODUCTION Developing mechanistic controls on the synthesis of colloidal materials requires us to advance experimental methods to probe the evolution of matter in real-time. Colloidal approaches to synthesize novel materials have gained widespread scientific attention since they allow us to design materials with specific pore and particle morphologies. In particular, the development of siliceous materials via colloidal approaches have received significant attention. Silica is abundant in earth materials and there is an emerging interest in understanding the thermodynamic6,12,13,16,18,19 and transport8–10,20,24 behavior of fluids in confinements, especially the Earth’s subsurface.5 To develop a calibrated understanding of anomalous thermodynamic and transport behavior of confined fluids, the development of model materials as surrogates for natural hierarchical materials has been proposed.11,196 One of the approaches to develop geo- architected siliceous materials is via colloidal synthesis.25,26 The morphologies of these ordered mesoporous materials are sensitive to the processing conditions including the temperature and solvent composition.197–201 Examples of these materials include SBA- 15, SBA-16, MCM-41, and MCM-48. These materials can be functionalized for applications in catalysis,202–205 delivery of bioproducts to the body,206,207 and filtration.208– 210 Directing the synthesis of novel materials with specific morphologies requires us to tune the experimental conditions. As an alternative to the conventional route of testing 40 several processing conditions, targeted in-operando measurements can reveal important mechanistic insights. Several research efforts have been dedicated to understanding the chemical27,28 and structural29–32 changes during the formation of ordered mesoporous silica. Moreover, the effect of electrolytes such as salts,26,211,212 silica precursors200 and other reagents201,213,214 and temperature215 have a significant influence on the morphologies of the silica particles produced via colloidal synthesis. The synthesis of these materials, when using non-ionic surfactants, is directly controlled by the amphiphilic molecules present in these structure directors or surfactants.201,213 Amphiphilic molecules used mostly for the ordered mesoporous silica synthesis are the block copolymers such as Pluronic triblock copolymers, which consist of polypropylene (PP) block sandwiched between two polyethylene (PE) blocks.216,217 In an aqueous solution, Pluronic polymers typically form micelles with a hydrophobic core of polypropylene (PP) block surrounded by a hydrophilic corona made up of polyethylene (PE) block.217–220 Water is present as the main part of corona but to some extent, it can also penetrate the core of micelles.219 It is known that the addition of electrolytes and temperature can affect the properties of Pluronic block copolymers.216,217,221,222 Moreover, the solubilities of these nonionic block copolymers are influenced by the presence of inorganic salts.26,211,223 The inorganic salts can either decrease or increase the solubility of organic solutes in the water based on a phenomena termed as the ‘salting-out’ and ‘salting-in’ effects, respectively.212 These effects are primarily governed by the anions in the inorganic salts, while the cations do not have a significant impact. The anions of the Hofmeister series are ordered below in terms of their effect on the solubility of organic solutes; SO 2-4 , HPO 2- - - - 4 , OH , F , HCOO 41 , CH COO-, Cl-, Br-, NO -, I-, SCN-, ClCO4-.26,212,2243 3 The anions to the left of Cl - have reduced solubility in macromolecules such as proteins (representing the “salting-out” effect), while those the right represent enhanced solubility (representing the “salting-in” effect), with the influence of Cl- being ambiguous.26,223,225 Ions influence the micellar arrangements219,226,227 leading to different morphologies of mesoporous silica.26,228–230 The formation of silica particles involves two stages. The first stage involves the formation of micelles containing a hydrophobic core of polypropylene (PP) surrounded by a hydrophilic corona made up of polyethylene (PE). The second stage involves the 2- D hexagonal ordering of the micelles and the formation of silica particles. The reactions below represent the hydrolysis and condensation reactions associated with the formation of mesoporous silica 11,231. Hydrolysis: ≡Si-OC2H5 + HO-H → ≡Si-OH + C2H5OH (3.1) Water condensation: ≡Si-OH + HO-Si≡ → ≡Si-O-Si≡ + H2O (3.2) Alcohol condensation: ≡Si-OH + H5C2O-Si≡ → ≡Si-O-Si≡ + C2H5OH (3.3) Prior in-situ Small Angle X-Ray Scattering (SAXS) studies showed that in- situ Small Angle X-Ray Scattering (SAXS) studies were modeled to represent the condensation and densification of silica.30 In-situ Small Angle Neutron Scattering (SANS) measurements showed that the salts influence the scattering intensity driven by changes in the composition of the wall.232 However, some scientific questions remain unanswered. These questions include: (i) How do we delineate the stages that involve the formation of micelles and the 2-D hexagonal ordering of the micelles to form silica particles? (ii) How do these stages vary when considering “salting-in” as an approach to direct the synthesis of colloidal silica? (iii) Does aging the silica particles change the 42 morphology of these materials? To address these questions, we investigated the phenomena that contributes to the densification and condensation of silica using in-situ small angle X-ray scattering (SAXS) and grazing incidence-small angle X-ray scattering (GI-SAXS). The chemical onset of silica matrix formation was identified using time- dependent ATR-IR measurements. We evaluate the hypothesis that anions that contribute to the “salting-in” effect such as NO - 3 accelerate the densification and condensation of mesoporous silica, SBA-15. Further, we evaluate the influence of aging on the morphology of mesoporous particles. SBA-15 particles have a hexagonal particle shape and a cylindrical pore structure. The influence of nitrate ions on the morphological changes of SBA-15 are probed. These investigations are designed to provide mechanistic insights into the densification and condensation behavior of mesoporous silica via colloidal synthesis. 3.2 MATERIALS AND METHODS The reagents used in this study are Pluronic® P123 (EG27PG61EG27), tetraethylorthosilicate (TEOS), magnesium nitrate hexahydrate (Mg(NO3)2.6H2O) purchased from Sigma Aldrich, and 1 N hydrochloric acid (HCl) acquired from Fisher Scientific. To synthesize SBA-15 particles, 47.74 mL of HCl, 8 g of P123 and 252 mL of water were stirred in a beaker at a rate of 600 rpm and temperature of 313 K. After the complete dissolution of the surfactant, 17 mL of TEOS was added to the solution and mixed for 24 hours, followed by filtration and air-drying at 90 °C for 48 hours. To investigate the influence of nitrate ions, Mg(NO3)2.6H2O was added to the solution of HCl, P123, and water to achieve a final molarity of 1 M. Therefore, the synthesis step was repeated by adding 17 mL of TEOS to the solution with salt while stirring at 600 rpm 43 and 313 K for 24 hours. Throughout this study, we refer to SBA-15 synthesized without the nitrate salt as “M-1” and SBA-15 synthesized with the nitrate salt is referred to as “M- 2”. To evaluate changes in the chemical bonding during the first 60 minutes of reaction, infrared (IR) spectra were acquired in an Attenuated Total Reflection (ATR) mode using an Attenuated Total Reflection-Fourier Transform Infrared spectrometer (ATR-FTIR, NicoletTM iS50, Waltham, MA). Slurry samples with 100 µL in volume were collected every three minutes for the ATR FT-IR analyses. The spectra were collected in the range of 4000−650 cm−1 with a total of 32 scans for each run at a resolution of 2 cm-1. The in-situ SAXS measurements were performed to determine the onset of silica matrix formation during the synthesis of mesoporous materials. The synthesis was performed in a beaker as mentioned above and the reaction solution was pumped through a quartz capillary (outer diameter 1.5 mm, thickness 0.2 mm) in a closed-loop system using a peristaltic pump. The schematic of the experimental setup used during the in-situ measurements is shown in Figure S3.1(a). The pumping rate of solution from solution bath to the capillary was set at 130 mL/min. During the measurements, the beam was centered in the middle of the vertically oriented quartz capillary. The transmission Small Angle X-Ray Scattering (SAXS) measurements were performed at sector 9-ID-C at Advanced Photon Source (APS) in Argonne National Laboratory (ANL).49,103,104,107,108,175,176,233 The scattering data were acquired within the scattering wave vector (q) range of 0.04 – 1.6 Å-1. q is related to the wavelength (λ) of incident X-ray and the scattering angle (θ) as: q = (4π/λ)sin(θ/2).180 X-ray wavelength during the measurements was 0.59 Å, which corresponds to an X-ray energy of 21.0 keV. Total X-ray photon flux received by the instrument was ~1013 photon mm-2 s−1 with the 44 beam size of 0.8 × 0.2 mm. The sample exposure time during each measurement was 30 s. The SAXS instrument was calibrated using silver behenate before the measurements.177 The 2D data collected by the instrument was reduced to 1D curves, represented as X-ray scattering intensity vs. scattering wave vector (I(q) vs. q(Å-1)), by using the Nika178 macro written in the IgorPro software (Wavemetrics, Lake Oswego, OR). The scattering from quartz capillary and respective solutions before the addition of TEOS was subtracted as background from the data. The in-situ measurements were performed up to 154 min for each sample. To obtain the detailed insights from the SAXS data, the fitting was performed using the “Small Angle Diffraction” tool in Irena package.179 The representative modeled curves are shown in Figure S3.2. For the in-situ Grazing Incidence - Small Angle X-ray Scattering (GI-SAXS) measurements, the batch reaction assembly was used (Figure S3.1 (b)). During the GI- SAXS measurements, the mesoporous materials were nucleated on a fused silica substrate. The in-situ cell for GI-SAXS measurements has a volume of 6 mL and thus, the amounts of materials added were adjusted accordingly. The description and schematic of the GI-SAXS cell is provided in a prior publication.234 For instance, 3.94 mL of water, 0.75 mL of HCl, and 0.125 g of P123 were added in the in-situ cell and the first measurement was taken without TEOS. In the next step, 0.27 mL of TEOS was injected into the cell through the inlets at the top of the cell. The injection was done remotely using a programmable syringe pump (Hamilton Microlab 600 series). The remote injection assisted us in robust data acquisition without losing any information at the early stage of reaction. The scattering data was acquired for 100 minutes. The measurements were taken in two steps. In the first step, 50 scans were taken every 40 seconds, while in the second 45 step, the interval between each scan was 4 minutes. The acquisition time for each scan was 1 second. A similar experiment was repeated with the solution bearing the nitrate salt. The GI-SAXS measurements were performed at sector 12 ID-C at APS. The scattered intensity during the measurements was collected on a 2-D Pilatus 2 M detector (Dectris Ltd., Baden, Switzerland). The GI-SAXS instrument was also calibrated for sample-to-detector distance using silver behenate [67]. The sample-to-detector distance during the measurements was 206 cm. The instrument was operated with the X-ray energy of 18 keV, corresponding to the X-ray wavelength of 0.68 Å. The GI-SAXS data were acquired in the q range of 0.006 – 0.74 Å-1. The X-ray beam was directed to the substrate at an incidence angle (αi) of 0.11°. The incident angle is lower than the critical angle for total external reflection at the given energy. The GI-SAXS data were cut along the horizontal 433 axis and 1D curves were obtained using an Igor based program. Finally, the powdered samples synthesized in the laboratory were investigated for pore size and N2 adsorption-desorption isotherms using the Brunauer−Emmett−Teller technique (BET, Quantachrome NOVAtouch Analyzer, Boynton Beach, FL). To evaluate the chemical species in the final product, the ATR-IR spectra of powders were also collected. The morphologies of particles formed during the syntheses were imaged using a scanning electron microscope (Zeiss LEO 1550 FESEM). These measurements coupled with the in-situ X-ray scattering and ATR-FTIR data provided detailed insights into the morphological and chemical evolution of SBA-15 in the presence and absence of the nitrate salt. 46 3.3 RESULTS AND DISCUSSION 3.3.1 Characterization of SBA-15 Particles Synthesized with and without the Addition of Nitrate Salt To evaluate the hypothesis that the chemistry and morphology of SBA-15 particles changes on the addition of nitrate salt, ATR-FTIR spectra and SAXS data of the synthesized M-1 and M-2 powders were collected. These data are shown in Figures 3.1 (a) and (b), respectively. The functional groups of solid SBA-15 particles remain unchanged when these particles are synthesized with and without the addition of nitrate salt. In the FTIR spectra, the bonds corresponding to Si-O-Si asymmetric, Si-OH, and Si- O-Si symmetric vibrations in the silica matrix are around 1045, 940, and 795 cm-1, respectively.235,236 Moreover, stretching vibrations from OH bands were noted between 3750 – 3300 cm-1, with additional vibrations from CH bonds from residual surfactant. Detailed assignments to these bands are presented in Table S3.1. These data show that the chemical composition of SBA-15 particles remains unchanged when the materials are synthesized with and without the nitrate salt (Figure 3.1 (a)). Analyses of the SAXS data showed that the characteristic dimensions of SBA-15 change when the material is synthesized using nitrate salt (Figure 3.1 (b)). The addition of nitrate salt shifted the peak representing the (100) plane to a relatively higher q value of 0.071 Å-1 from 0.064 Å-1, which corresponds to the d-spacing of 88.5 Å and 98.2 Å, respectively. The values of all the d-spacings corresponding to labeled peaks are presented in Table S3.2. The mesoporous lattice types in M-1 and M-2 were evaluated by calculating the ratios of q values of the first four peaks that appeared in the SAXS curves (Figure 3.3(b)). 47 Figure 3.1 (a) Identification of the functional groups using Attenuated Total Reflection- Fourier Transform Infrared spectroscopy (ATR-FTIR) measurements, and (b) meso-scale structure determination using Small Angle X-Ray Scattering (SAXS) measurements in mesoporous silica, SBA-15 synthesized without (M-1) and with magnesium nitrate salt (M-2). The calculated ratios for M-1 and M-2 are presented in Table S3.3. For both materials, we found that the mesopores were organized as a hexagonal (H1) lattice 221,222 since both followed ratios of 1 : √3 : √4 : √7. The lattice parameters ‘a0’ for M-1 and M- 2 were also calculated using the following equation. 2 × d a = (100)0 ⁄ (3.4) √3 where, d(100) = 2π/q(100). The values of ‘a’ for M-1 and M-2 were found to be 11.64 nm and 10.23 nm, respectively. Additional insights into the pore sizes were obtained from the BET N2 adsorption- desorption isotherms, measured at 77 K. The isotherms and pore size distribution of M-1 synthesized in the absence of salt and M-2 synthesized in the presence of nitrate salt are presented in Figure 3.2. The pore size distributions for both samples were determined using the BJH method applied to the desorption isotherm. M-1 exhibited a relatively wider pore-size distribution with an average pore diameter of 4.11 nm, while M-2 48 exhibited a narrow pore-size distribution having an average pore diameter of 3.65 nm (Figure 3.2 (a)). Moreover, the values of the lattice parameter ‘a0’ and average pore size were used to determine the wall thicknesses (a0 – pore size) in M-1 and M-2. 199 Figure 3.2 Pore size distribution curves (a) and N2 adsorption-desorption isotherms for mesoporous M-1 (b-1) and M-2 (b-2), respectively. M-1 and M-2 represent mesoporous silica, SBA-15 synthesized without and with magnesium nitrate salt. The pore wall thickness for M-1 and M-2 were found to be 7.5 nm and 6.6 nm, respectively. This decrease in the pore size and thinner walls in the presence of salt can be attributed to the salting-in effect of nitrate ions. The effect of anions on the size of P123 micelles in aqueous solution using small angle X-ray and neutron scattering has been studied by Manet and co-workers,226 who reported that the anions facilitating salting-out effects produce relatively larger micelles compared to the anions that facilitate the salting-in effects. Since NO -3 ions facilitate salting in effects, the decrease in the pore size of the final product of M-2 can be attributed to this effect. The N2 BET adsorption-desorption isotherms for M-1 and M-2 are presented in Figures 3.2 (b-1) and 3.2 (b-2), respectively. Typical type IV-a isotherms were exhibited by both the samples, having a hysteresis which indicates the presence of capillary condensation in the pores 237. However, the different types of hysteresis loops were 49 presented by both the samples. For instance, M-1 presented a type of H1 hysteresis, which is an indication of uniform mesopores having a delayed condensation on the adsorption branch. For M-2, type H2-(a) hysteresis was noted. This observation is associated with the cavitation-induced evaporation leading to narrower pore size distributions and smaller pores 199,208,237–239 compared to M-1. As evidence, the surface area of M-1 and M-2 are 375.5 m2/g and 370.7 m2/g, respectively. The pore volumes of M-1 and M-2 are 0.44 cc/g and 0.33 cc/g, respectively. The pore sizes of M-1 and M-2 are 4.1 nm and 3.6 nm in M- 1 and M-2, respectively. These parameters are summarized in Table 3.1. While the BET pore size measurements showed clear differences in the structure of SBA-15 synthesized with and without the nitrate salt, insights into the evolution of micellular organization leading to the structure of SBA-15 are reported in the following sections. Table 3.1 Lattice parameters, pore sizes, wall thicknesses, surface areas, and pore volumes for M-1 and M-2. Lattice parameters were calculated from the first peaks (q(100)) in SAXS curves. Pore size distributions, surface area and pore volumes were determined from N2 adsorption-desorption isotherms. The wall thickness was calculated by subtracting the average pore size from lattice parameter. Pore Wall Surface Pore Lattice Size Thickness Area Volume Parameter (nm) 2 Sample (nm) (nm) (m /g) (cc/g) ID (𝑎0 2 × d (BJH (𝑎 (N2 ( 0100) (BET) = ) Method) − 𝑝𝑜𝑟𝑒 𝑠𝑖𝑧𝑒) isotherm) √3 M-1 11.6 4.1 7.5 375.5 0.44 M-2 10.2 3.6 6.6 370.7 0.33 3.3.2 Evolution of the Si-bearing Functional Groups during the Synthesis of SBA-15 The formation of mesoporous silica is accomplished in two steps.231 The first step is the hydrolysis of silicate species (TEOS) by water which results in the formation of silanol (Si-OH) as presented by Reaction (3.1). Following the hydrolysis step is the 50 condensation reaction, which leads to the formation of Si-O-Si linkages, eventually leading to the formation of a well-ordered mesoporous structure. During the condensation reaction, the silanol species react with either another silanol or precursor silicates to form siloxanes (Si-O-Si). The formation of siloxane by the reaction of two silanols is termed as water condensation, while the reaction of silanol with silicates to produce siloxane is called alcohol condensation, as shown in Reactions (3.2) and (3.3), respectively. To capture these chemical changes during the formation of mesoporous M-1 and M-2 materials, the ATR-FTIR measurements were performed as the silica materials were synthesized. For these measurements, 100 µL of the solution was extracted from the reaction mixture and dropped on the ATR diamond crystal for FTIR analyses. The time interval between sample extraction from solution to dropping on ATR crystal was 30 s. Each ATR measurement took approx. 1 minute. The time reported in here corresponds to the beginning of each measurement. The solutions were well-mixed to ensure that the samples were representative of the solution composition. The FTIR spectra of M-1 and M-2 solutions before the addition of TEOS were taken as the background prior to the measurements. The ATR-FTIR spectra of TEOS, M- 1 (pre-TEOS), and M-2 (pre-TEOS) are presented in Figure S3.3. The pre-TEOS spectra of M-1 and M-2 were acquired with water as the background. In these IR spectra, the C- O-C and C=O stretching vibrations from Pluronic P123 were observed around ~1090 cm- 1 and ~1615 cm-1, respectively. 240 For M-2, a peak from asymmetric vibrations of NO -3 from Mg(NO3)2 was also noted at 1338 cm -1.241 During the synthesis, significant changes were noted between 1250 – 850 cm-1 in the IR spectra (Figure 3.3). Changes for the peaks corresponding to Si-OH (silanol) and 51 Si-O-Si (siloxane) were observed. To understand the underlying chemical transformations, the peaks in the range of 1250 – 1000 cm-1 were deconvoluted to better understand the underlying chemical transformations. This range was selected because the bands corresponding to the final silica product (Si-O-Si) lie within this range as indicated in several literature sources.27,28,242–246 The deconvoluted spectra at the major representative transformation stages were plotted and shown in Figures S3.4 and S3.5 for M-1, and M-2, respectively. The deconvolution was performed using the Levenberg Marquardt iteration algorithm using the Gauss model embedded in Origin Pro software (OriginLab Corp.). To compare the evolution of functional groups in both samples, the peaks around ~960 cm-1 for Si-OH (silanol) and ~1079 cm-1 for Si-O-Si (blue curves in deconvoluted spectra) in silica matrix were selected. Although multiple Si-O-Si vibration modes were identified during the peak deconvolution, the bands around 1079 cm-1 were selected as representative bands for siloxane vibrations. The integrated peak areas for Si-OH (~960 cm-1) and Si-O-Si (~1079 cm-1) were determined and the values were normalized by the maximum value. The normalized integrated peak areas for Si-OH and Si-O-Si are plotted in Figures 3.3 (a-2) and (b-2) for M-1 and M-2, respectively. In M-1, the C-O and C-C peaks from ethanol were observed in the first scan (0 minute) shown in Figure S3.4 (a), which is an indication of hydrolysis of silicate species by water. Similar behavior was exhibited by M-2 at 0 minutes, as presented in Figure S3.5 (a). Moreover, the actual integrated peak areas and associated errors for peaks around ~1079 cm-1 are shown in Figure S3.6. 52 Figure 3.3 Evolution of the functional groups during the synthesis of mesoporous silica, SBA-15 in the (a-1) absence (M-1) and (b-1) presence of nitrate ions (M-2). The time evolution of the functional groups based on the normalized integrated peak areas in mesoporous silica, SBA-15 in the (a-2) absence (M-1) and (b-2) presence (M-2) of nitrate ions is shown. Our hypothesis when analyzing the ATR-FTIR data was that the trends in the absorbance vary as transformations from the colloidal to solid phase occur, which was confirmed based on the data presented in Figure 3.3. Deconvolution of Si-O-Si peaks provided insights into the mechanisms governing the formation of silica particles. The first peak for Si-O-Si (~1079 cm-1) was noted after 21 minutes for M-1, while for M-2 it was noted after 12 minutes. Si-O-Si bands (~1079 cm-1) followed a similar trend as Si- OH band (~960 cm-1), which corresponds to the simultaneous hydrolysis of TEOS and condensation of silanol (Si-OH) to produce siloxane (Si-O-Si) linkages in the mesoporous silica matrix. The downward trend in the integrated peak area curves was attributed to the 53 separation of precipitated particles from the solution phase, with the solvent in contact with the ATR crystal. Further, additional vibration modes for Si-O-Si were also identified in the deconvoluted spectra of both M-1 (Figure S3.4) and M-2 (Figure S3.5). These peaks could be attributed to the co-existence of different internal and external Si-O vibrations between 1200 – 1000 cm-1, which has been reported to exist during the formation of mesoporous MCM-41.27 Additionally, the asymmetric Si-O band from unreacted TEOS was also noted for both the samples, which shifted from ~1125 cm-1 (0 minutes) to ~1200 cm-1 during the formation of the mesoporous matrix. The ATR-IR measurements have shown that in the presence of nitrate anions, the onset of siloxane formation was relatively early (12 minutes) when compared with the solution (21 minutes) without salt. This observation is consistent with the hypothesis that anions that facilitate “salting in” effects enabling higher solubility of the polymers and early onset of micellization.212,226 These studies show that early micellization facilitated by nitrate ions enables the early onset of hydrolysis and condensation of the silica matrix, as noted for M-2. To compliment these spectroscopic investigations which provide insights into the dynamic chemical evolution of colloidal silica material systems leading to the formation of mesoporous silica, in-operando evolution in the meso-scale features of silica with and without nitrate salts is probed using Small Angle X-Ray Scattering (SAXS) and Grazing Incidence – Small Angle X-Ray Scattering (GI-SAXS) measurements, as discussed in the following sections. 3.3.3 Dynamic Evolution in the meso-Scale Features of Silica To monitor the evolution of mesoporous phase formation, in-situ SAXS measurements were performed in transmission and grazing incidence geometries. The in- 54 situ transmission SAXS curves for M-1 and M-2 are presented in Figures 3.4 (a) and (b), respectively. The increase in the scattering intensity in case of M-2 could be referred to the increase in scattering length density (SLD) in the presence of Mg(NO3)2 (SLD = 19.47 × 10-6 Å-2). The integrated intensities of both samples were also calculated and plotted in Figure 3.4 (c) for M-1 and M-2, respectively. The peaks and Guinier knee-like feature around 0.3 Å-1 were fitted using the ‘small angle diffraction’ tool using the Irena program179 in IgorPro software. The SAXS data for M-1 and M-2 were interpreted using hexagonal close-packed (HCP) cylindrical geometry, which is consistent with the meso- scale organization of these materials.221,222 However, the Guinier knee was fitted using the approach proposed by Beaucage.181,182 The model was fitted between the q values of 0.2 – 0.8 Å-1 to obtain the radius of gyration (Rg) values, which are reported in Figure 3.5. Important insights into the evolution of the meso-scale features of silica can be obtained by investigating changes in the (100) characteristic peak which corresponds to the ordered mesopores 26,30,199. Further, the intensity of (100) characteristic peak was observed to be increasing with time as the mesoporous silica phase was formed. In the case of M-1, the onset of the (100) peak at 25 minutes (Figure 3.4 (a)) corresponded to the onset of siloxane formation, as discussed in section 3.2. In the case of M-2 in which the SBA-15 is synthesized in the presence of nitrate salt, the characteristic peak was noted as early as 2 minutes. The earlier development of the (100) peak in mesoporous silica synthesized using the nitrate salt, M-2 (Figure 3.4 (b))247 is consistent with the earlier onset of siloxane linkages noted in Section 4.3.2. 55 Figure 3.4 Evolution in the characteristic d (100) peak in mesoporous silica, SBA-15 synthesized in the (a) absence (M-1) and (b) presence (M-2) of nitrate salt using in- operando Small Angle X-Ray Scattering (SAXS) measurements. Comparison of the normalized integrated peak intensity of the d (100) peak is shown in (c). 56 Figure 3.5 Estimated radius of gyration (Rg) values for M-1 and M-2 between the q-range of 0.2 – 0.8 Å-1 obtained from the transmission SAXS measurements. To determine whether the scattering was from micelles or mesoporous phase, the values of d-spacing corresponding to the peak centers were analyzed. For M-1, initially, the d-spacing of 11.0 nm was observed, which could be attributed to the scattering from micelles in the solution. Comparable values of d-spacing for P123 micelles have been reported in the literature.26,247 At the onset of siloxane (Si-O-Si) condensation (~27 minutes), the d-spacing value decreased to 10.4 nm and remained constant until 83 minutes of reaction. After 83 minutes of reaction, the d-spacing value changed to 9.9 nm and remained constant until the end of SAXS measurements. This decrease in d-spacing is attributed to the densification of silica-phase around the micelles.201,232,248,249 For M-2, in which nitrate ions were present in the solution, the d-spacing values for (100) plane exhibited a similar trend as shown by M-1. However, the initial value (13.5 nm) was relatively higher than the M-1. The first decrease in the d-spacing value was noted after 10 minutes, where the value decreased from 13.5 to 12.5 nm and eventually attained a 57 value of 11.7 nm after 18 minutes. Upon further reaction for up to 50 minutes, the d- spacing value decreased to 11.0 nm and remained constant until 75 minutes. Afterward, the values changed to 10.4 nm and remained constant until the end of the reaction. The d-spacing of M1 determined from the in-situ measurements and ex-situ measurements of the synthesized powder was 9.9 nm and 9.8 nm, respectively. These data are in reasonable agreement with each other. The d-spacing of M2 synthesized with nitrate salt from the in-situ measurements and ex-situ measurements of the synthesized sample was 10.4 nm and 8.9 nm, respectively. The discrepancy in these data is attributed to the influence of aging these samples on the changes in the mesoscale structure. To probe the effect of aging on the morphology of the particles, SEM images were taken (Figure 3.6). Figure 3.6 Morphologies of as-prepared (a-1) M-1 and (b-1) M-2 and, (a-2) M-1 and (b- 2) M-2 aged for three weeks represented using Scanning electron micrographs (SEM). M-1 and M-2 represent mesoporous silica, SBA-15 synthesized without and with magnesium nitrate salt. The micro-scale morphology of M-1 and M-2 particles was also imaged using 58 SEM and presented in Figures 3.6 (a-1) and (b-1), respectively. The observed morphology of SBA-15 particles synthesized at room temperature (Figure 3.6 (a-1)) is consistent with the observations from prior publications.199,201 However, when nitrate ions were present in the solution (Figure 3.6 (b-1)), no regular morphology was observed. The morphologies of synthesized silica particles have been shown to be sensitive to temperature.215 Prior literature suggested that Cl- ions result in well-defined and regular particle morphologies, Br- ions yield small and slightly irregular particle morphologies while I- ions do not result in regular morphologies.26 In the Hofmeister series for evaluating salting-in effects, nitrate is located in between Br- and I- ions. The initial irregular morphologies observed when using I- ions to synthesize silica particles 26 is consistent with that of nitrate ions in this study. However, we observed that aging the samples synthesized in nitrate salts, changes the particle morphology. SEM images were collected on samples aged for two weeks at room temperature under static conditions (Figures 3.6 (a-2) and (b-2)). Aging M-1 samples prepared in the absence of nitrate salts resulted in platelet or disk-like morphology (Figure 3.6 (a-2)). However, in the presence of nitrate ions, the random particles initially formed were transformed into spherical particles (Figure 3.6 (b-2)). The particle size was also found to be increased in both cases, which was a direct effect of aging in the solution, as reported previously.250 The formation of spherical particles in M-2 could be attributed to the intrinsic need of the system to minimize the surface energy.251 It has been reported that in the presence of salt, more water is expelled during the synthesis resulting in a more flexible molecular rearrangement and thermodynamically favorable structures.26,252 Therefore, the presence of NO -3 ions in the solution, could help minimize the surface energy and 59 eventually produce particles with spherical morphologies. Additionally, if the polymerization of inorganic species (Si-O-Si) is slow relative to the formation of the meso-structure, then well-defined mesostructured materials are developed. However, irregular particles are formed if inorganic species polymerize relatively fast.26,251 Therefore, to understand whether the spherical morphology of M-2 particles was controlled by the presence of NO -3 ions or aging in the solution where the existing silica phase might influence the final morphology, the SAXS experiments were repeated in a GI-SAXS geometry and the mesoporous particles were precipitated on fused silica- substrates. To understand the effect of the substrate or existing silica phase on the morphology of mesoporous particles, in-situ GI-SAXS measurements were performed, as described in Section 2. Briefly, 3.94 mL of water, 0.75 mL of HCl, and 0.125 g of P123 were added in the cell followed by injection of 0.27 mL of TEOS after the first measurements. The evolution of (100) characteristic peaks for both M-1 and M-2 are presented in Figures 3.7 (a-1) and (b-1), respectively. It can be noted that the (100) peak appears after 26 min for M-1 (Figure 3.7 (a-1)), which is relatively late when compared with the emergence of (100) peak in M-2 (Figure 3.7 (b-1)). In the case of M-2, the small peak was noted for the curve at 1 minute, however, a prominent peak at 1.5 minutes was observed. These data show that the presence of nitrate ions facilitates the early nucleation of silica particles. 60 Figure 3.7 Evolution in the characteristic d (100) peak in mesoporous silica, SBA-15 synthesized in the (a-1) absence (M-1) and (b-1) presence (M-2) of nitrate salt using in- operando Grazing Incidence - Small Angle X-Ray Scattering (GI-SAXS) measurements. The morphologies of (a-2) M-1 and (b-2) M-2 are captured using Scanning electron micrographs (SEM). Scattering from M-1 showed that a broad peak appeared after 12 minutes. This peak was attributed to the scattering from the micelles formed and accumulated at the substrate. The initial data from micelles for M-1 was fitted using the core-shell model available in Irena program179 and presented in Figure S3.7. Additionally, the parameters calculated from the model fitting are reported in Table S3.4. The d-spacing value for M- 1 at 12 minutes was noted to be 25.2 nm, which decreased to 18.8 nm after 33 minutes, where the first sharp peak was observed. This decrease in the d-spacing value can be attributed to the densification of silica-phase around the micelles as a result of Si-O-Si polymerization, which increases X-rays contrast. Finally, the d-spacing value decreased 61 to 15.4 nm after 100 minutes of reaction. In the case of M-2, a significant (100) peak from micelles/mesostructures was noted just after two minutes and an increase in the peak growth was observed. Initially, for M-2, the d-spacing of 13.2 nm was observed at 2 minutes. However, as the reaction proceeded, d-spacing decreased from 12.7 nm at 17 minutes to 11.9 nm after 100 minutes. Additionally, the full width half maximum (FWHM) of (100) peaks for M-1 and M-2 were also calculated and are presented in Figure S3.8 (a) and (b), respectively. After 33 minutes of reaction times, FWHM values for M-1 started to decrease and achieved a constant value after 60 minutes. However, in the case of M-2, the FWHM value slightly increased due to peak broadening and achieved a relatively constant value at a comparatively early stage (~12 minutes). These findings were similar to those noted in ATR-IR and transmission SAXS measurements, where Si- O-Si polymerization and pore densification were noted after 25-27 minutes for M-1 and 10-12 minutes for M-2. The SEM images of M-1 and M-2 particles nucleated on the fused silica substrates during GI-SAXS measurements were also acquired to analyze the micron-scale morphology. The SEM images are presented in Figures 3.6 (a-2) and (b-2), respectively. For M-1, hexagonal and cylindrical morphologies were observed as noted in the as- synthesized sample (Figure 3.6 (a-1)). However, upon addition of nitrate ions, spherical mesoporous particles were formed (Figure 3.6 (b-2)). The formation of spherical particles in the case of M-2 can be related to the influence of the existing silica substrate which assists the NO -3 ions to lower the surface energy during the relatively fast polymerization of Si-O-Si in mesostructure formation 251. Further information about the kinetics of mesostructure development was obtained from the GI-SAXS data by fitting 62 the (100) peak intensity vs. time data to the Avrami equation. The Avrami equation can be used to obtain insights into the phase transformation processes involving continuous nucleation, loss or gain of a phase.253–256 The mathematical expression for the Avrami equation is represented below: 𝑛 𝑋𝑠(𝑡) = 1 − 𝑒 −𝑘𝑡 (3.5) where, 𝑋𝑠(𝑡) = 𝐼𝑠(𝑡)/𝐼𝑠(∞), is the fraction of mesostructure formed at time t, n is the Avrami index, and k is the rate coefficient. The value of 𝑋𝑠(𝑡) was calculated by dividing the intensity of (100) peak by the maximum observed intensity. The Avrami equation can be modified into a linearized form by re-writing as follows: ln(ln[1 − 𝑋𝑠(𝑡)]) = 𝑛 𝑙𝑛 𝑡 + 𝑙𝑛 𝑘 (3.6) The fits performed on linearized Avrami equation, and parameters obtained are presented in Figure 3.8. Figure 3.8 Avrami plots for (a) M-1 and (b) M-2 determined from GI-SAXS data. M-1 and M-2 represent mesoporous silica, SBA-15 synthesized without and with magnesium nitrate salt, respectively. The Avrami index reflects the nature of transformation and corresponds to the mechanism of crystal growth or, in the present case, the formation of silica mesostructure.253,257,258 The value of n = 1 corresponds to the one-dimensional (1-D) 63 growth of the objects, n =2 is attributed to the two-dimensional (2-D) growth with the nucleation at the start of process, while n = 3 presents the three-dimensional (3-D) growth of instantaneously formed nuclei or 2-D growth at a constant nucleation rate.253 In the case of M-1, the onset of (001) peak is 26 minutes. Fitting the data in the time scales of 13-20 minutes, just before the appearance of mesostructured phase, gives an Avrami index, n of 2.91 ± 0.25, corresponding to 2-D growth at a constant nucleation rate (Figure 3.8 (a)). In the case of M-2, the onset of nucleation is 1.5 minutes. After 6 minutes, densification of silica particles is noted. Fitting the data in the range of 1.3 – 5.3 minutes results in a n value of 2.27 ± 0.14. The GI-SAXS data together with transmission SAXS and ATR-FTIR data facilitate mechanistic insights into the colloidal assembly of mesoporous silica and guide future synthesis efforts. 3.4 CONCLUSIONS Elucidating the reaction mechanisms, the compositions and chemistry of the reactants on the meso-scale morphologies of silica synthesized via colloidal pathways is essential for developing mechanistic insights into these pathways. In this study, we describe the chemical transformations underlying the hydrolysis and condensation of silica species in the presence and absence of nitrate ions as determined using time- resolved ATR FT-IR measurements. Fast polymerization of Si-O-Si species to form mesoporous silica is noted when SBA-15 is synthesized in the presence of nitrate salts. Transmission SAXS measurements showed that the onset of 2-D hexagonal structure is accelerated in the presence of nitrate salts. However, the equilibrium meso-scale structure is influenced by aging in the synthesis solution, resulting in plate-like morphologies in the absence of the nitrate salt and spherical morphologies in the presence of nitrate salt 64 after two weeks. Further, GI-SAXS measurements show the early nucleation of silica particles when synthesized from solutions bearing nitrate salt. These studies show that tuning the reaction conditions to achieve specific meso-scale morphologies can be informed by characterizing the dynamic evolution in the meso-scale structure of silica. 65 3.5 SUPPLEMENTARY MATERIAL Table 3.2 Table S3.1. Functional groups present on as-synthesized M-1 and M-2 Wavenumber (cm-1) Functional groups 3750 – 3300 O-H stretching mode 2970 – 2850 C-H symmetrical stretch 1460 – 1340 C-H 1047 – 1042 Si-O-Si (siloxane) asymmetrical vibrations 943 – 938 Si-OH (silanol) vibrations ~ 795 Si-O-Si (siloxane) symmetrical vibrations 66 Table 3.3 Table S3.2. Small Angle X-ray Scattering (SAXS) parameters q (Å-1) d-spacing (Å) (hkl) M-1 0.06 100.8 (100) 0.11 57.9 (110) 0.13 49.9 (200) 0.16 38.0 (210) 0.18 34.1 (300) 0.22 28.9 (220) M-2 0.07 88.6 (100) 0.12 51.4 (110) 0.14 44.5 (200) 0.18 33.8 (210) 67 Table 3.4 Table S3.3. Ratios of observed q values for as-synthesized SAXS curves of M-1 and M-2 Sample ID Calculated Ratios from q values Phase 0.06 : 0.11 : 0.13 : 0.16 M-1 Hexagonal (H1) 1 : √3 : √4 : √7 0.07 : 0.12 : 0.14 : 0.18 M-2 Hexagonal (H1) 1 : √3 : √4 : √7 68 Table 3.5 Table S3.4 Parameters used while performing Core-Shell model fitting on M- 1 GI-SAXS experimental data for micelles Parameter Value Form Factor: Core-Shell Rg 97.51 (Å) Shell Thickness 12.15 (Å) Core rho 2.16 × 10-6 (Å-2) Shell rho 2.47 × 10-6 (Å-2) Solvent rho 2.23 × 10-6 (Å-2) 69 Figure 3.9 Figure S3.1 Schematic of experimental setup during in-situ transmission small angle X-ray scattering (SAXS) (a) and in-situ grazing incidence small angle X-ray scattering (GI-SAXS) (b) measurements. 70 Figure 3.10 Figure S3.2 Small Angle X-ray Scattering (SAXS) curves at different time intervals (points) and fitted models (solid line) for M-1 (a) and M-2 (b) samples. 71 Figure 3.11 Figure S3.3 ATR-IR spectra of raw materials used during the synthesis of M-1, and M-2 mesoporous materials. In case of TEOS and water, the background was air. However, for M-1 (pre TEOS) and M-2 (pre TEOS) water was taken as the background. 72 Figure 3.12 Figure S3.4 Deconvoluted ATR-IR spectra during the synthesis of M-1 at different times between the range of 1250 – 1000 cm-1. 73 Figure 3.13 Figure S3.5 Deconvoluted ATR-IR spectra during the synthesis of M-2 at different times between the range of 1250 – 1000 cm-1. 74 Figure 3.14 Figure S3.6 Integrated peak areas for Si-O-Si vibrations ~1079 cm-1 calculated from Figure S4 and Figure S5 for M-1 (a) and M-2 (b), respectively. 75 Figure 3.15 Figure S3.7 GI-SAXS experimental data for micelle scattering from M-1 and fitted core-shell model. 76 Figure 3.16 Figure S3.8 Full Width Half Maximum (FWHM) values for (100) peak for M-1 (a) and M-2 (b), respectively, calculated from GI-SAXS data. The error bars correspond to the 5% of error in calculated values. 77 4 CONTRASTING THERMALLY-INDUCED STRUCTURAL AND MICROSTRUCTURAL EVOLUTION OF ALUMINO-SILICATES WITH TUBULAR AND PLANAR ARRANGEMENTS: CASE STUDY OF HALLOYSITE AND KAOLINITE The contents of this chapter have been published as a journal article: H. Asgar, J. Jiaqi, J. Miller, I. Kuzmenko, and G. Gadikota, Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2021, 613, 126106 4.1 INTRODUCTION There is a rising interest in advancing our understanding of thermally induced structural and morphological transformations in naturally occurring hierarchical materials with an intent to aid the design of analogous engineered materials.5,46,196 Further, materials with well-controlled architectures facilitate our understanding of the anomalous transport,6–10,20 thermodynamics,6,15,16,18,19 and reactivity behavior of fluids in confinement.22–24,33–36 Among the naturally occurring hierarchical materials, aluminosilicate clays have been used for several applications in the past including carbon capture and storage,37–44 the synthesis of engineered porous materials for separations,259– 263 barrier materials for radioactive nuclear waste,3,45 and ceramics for high-temperature thermal energy storage.51,52,264–268 Kaolinite and halloysite are the two most widely studied and extensively used aluminosilicates bearing the same chemical composition (Al2Si2O5(OH)4) with alternating octahedral alumina (AlO6) and tetrahedral silica (SiO4) sheets arranged in a 1:1 manner.46–50 The main difference between kaolinite and halloysite is observed in their morphology (Figure 4.1). Kaolinite naturally occurs as platelet sheets46,49 (Figure 4.1 (a)) while halloysite is comprised of rolled sheets that are organized to form tubular particles47,48,50–53 (Figure 4.1 (b)). In both halloysite and kaolinite, the alternating sheets 78 of tetrahedral silica and octahedral alumina have mismatch in their lateral dimension, where the silica sheet (9.164 Å) is larger than the alumina sheet (8.665 Å).269,270 This causes a misfit of the sheets and this misfit is either compensated by tetrahedral rotation271,272 or the rolling mechanism269,272 during mineral formation. Figure 4.1 Morphology of (a) planar kaolinite and (b) tubular halloysite aluminosilicates as viewed by a scanning electron microscope. Schematic comparison of kaolinite and halloysite structures is shown in (c). The geographical occurrence of these clays also plays an important role in the evolution of the morphologies of these materials.273 Under hydrated conditions, the sheet rolling mechanism is preferred, while dehydrated conditions favor the rotation of the tetrahedral sheet.269,272,274 In a dehydrated structure, the interlayer hydrogen bonding is dominant, resulting in the rotation of the tetrahedral sheet,272 giving rise to a plate-like morphology. However, in a hydrated structure the tetrahedral rotation is restricted by 79 interlayer water, disrupting the hydrogen bonding across the interlayer and resulting in rolling of sheets.269,270,272–275 Geographically, kaolinite clays are found in well-drained dehydrated subsurface environments273 suitable for the tetrahedral rotation mechanism, which aids the formation of plate-like morphologies. In contrast, halloysite minerals are found in environments where the fluids have high ionic concentrations, which favors hydration and the formation of particles with tubular morphology.273 The schematic representation of the platy and tubular organizations in kaolinite and halloysite are shown in Figure 4.1 (c). Another difference between these two aluminosilicates, caused by the hydration, is the interlayer basal spacing. Kaolinite exhibits an interlayer basal spacing of 7.2 Å.49 However, in the case of halloysite, interlayer basal distances of 7 Å and 10 Å, respectively, are noted. The differences in the interlayer basal spacing depends on the water content of halloysite (Al2Si2O5(OH)4.nH2O). Hydrated halloysite (n = 2) has a maximum interlayer basal spacing of 10 Å, corresponding to a monolayer of water molecules between the multilayers, while anhydrous halloysite (n = 0) has an interlayer basal spacing of 7 Å.48,53 The water molecules in hydrated halloysite can be removed under mild heating at ~60 °C to obtain anhydrous halloysite 50,53. This heating at low temperatures has no significant effect on the internal diameter of halloysite nanotubes, which could range between 10 – 100 nm, based on its source.53,276 The meso-scale porosity (pore diameter = 2 – 50 nm237) in halloysite and the nano- scale cylindrical orientation of the pores facilitate the investigation of the properties of confined fluids in natural hierarchical materials. Despite the application of halloysite in ceramics,53,277 thermally induced simultaneous structural and morphological evolution of 80 these materials has not been reported. Prior studies reported the structural transformations in tubular halloysite47,48,278,279 with some information on the pore morphology. The structural changes in tubular aluminosilicates such as halloysite on heating to 1200 °C47,48,278,279 are similar to that of a platy aluminosilicate such as kaolinite46,49,280, as summarized in Table 4.1. Table 4.1 A summary of similarities between the structural transformations in kaolinite and halloysite during thermal treatment Temperature Kaolinite Halloysite Range 25 – 150 °C Removal of loosely bound and Removal of loosely bound 49 interlayer water (hydrated to 25 – 120 °C water anhydrous halloysite) 278 400 – 700 °C Kaolinite to metakaolin 46,49 Halloysite to metahalloysite 278 400 – 600 °C 700 – 1050 °C Amorphous metakaolin phase Amorphous metahalloysite phase 46,49 278 600 – 900 °C 900 – 1100 °C --- Spinel like γ-Al O phase 47,2782 3 > 1050 °C Crystalline mullite phase 46,49 Crystalline mullite phase 47,278 > 1100 °C Recent advancements in non-invasive cross-scale X-ray scattering characterization approaches now facilitate the simultaneous probing of thermally or chemically induced evolution in the structural and microstructural features of engineered materials.46,49,103–110 Further, we elucidate the differences in the structural and morphological features of halloysite with previously published results for kaolinite.49 Therefore, in this study, we investigate the following important research questions that need to be addressed: 81 (i) How does the structure of halloysite evolve on heating? What is the corresponding evolution in the pore morphology of halloysite? (ii) What are the similarities and differences in the structural and microstructural evolution in tubular (halloysite) and platy (kaolinite) aluminosilicates? To address these questions, simultaneous Ultra-Small/Small and Wide-angle X- ray Scattering (USAXS/SAXS/WAXS) measurements are used. This combined approach allows us to probe features in the spatial scales of Ångstroms to micrometers in a single scan within 4-5 minutes. These in-operando measurements are used to evaluate the hypothesis that the structural transformations of halloysite sheets occur from the crystalline to the amorphous phases, and then recrystallization influences the nano-scale and meso-scale morphological features of these materials. These X-ray scattering measurements are complimented by N2 BET measurements to determine pore size distribution as a function of temperature, Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR) measurements are used to evaluate the changes in the chemical bonds and laboratory-based Thermogravimetric Analysis (TGA) is used to determine the changes in the weight as a function of temperature. These insights will advance our understanding of the structural and morphological evolution of hierarchically ordered alumino-silicate materials. 4.2 MATERIALS AND METHODS Halloysite and kaolinite (KGa-1b) samples were procured from the Dragon Mine (Applied Minerals, UT, USA) and the Source Clays Repositories (Purdue University, West Lafayette, IN), respectively. Large pieces of consolidated halloysite from the mine were ground into particles smaller than 150 µm, whereas kaolinite was used as received. 82 The changes in the weight of the halloysite clay during thermal treatment were evaluated up to 900 °C with a ramp rate of 5 °C/min in an N2 environment (purged at 25 mL/min) using a Thermogravimetric Analyzer (TGA) (TA Instruments, SDT650, New Castle, DE). The in-operando USAXS/SAXS/WAXS measurements on the halloysite sample were performed at Sector 9-ID-C at the Advanced Photon Source (APS), Argonne National Laboratory (ANL). The instrument at 9-ID-C is based on the original Bonse- Hart double-crystal setup.175,176 To acquire the scans, the sample was loaded into a quartz capillary (I.D. = 1.3 mm and O.D. = 1.5 mm). Scattering from the empty capillary was also taken as the background and subtracted from the data. The measurements were taken at temperature intervals of 25 °C up to 875 °C with a ramp of 5 °C/min. The total X-ray flux was ~1013 photon mm-2 s−1, X-ray energy was 21.0 keV, and the corresponding X- ray wavelength was 0.59 Å. The sample-to-detector distance and instrument calibrations were performed using silver behenate for SAXS177 and LaB6 for WAXS. The collected USAXS and SAXS/WAXS raw data were reduced using Irena179 and Nika178 macros written in the IgorPro software (Wavemetrics, Lake Oswego, OR), respectively. Finally, the USAXS and SAXS curves were merged using the Irena tool. To quantify the hierarchical morphological features of the halloysite sample, the combined USAXS/SAXS curves were modeled using the “Modeling II” tool in the Irena package179. The fittings were performed by using three unified fit levels based on different q-regions, where q = (4π/λ)sin(θ/2), λ is the incident X-ray wavelength and θ is the scattering angle.180 The following q-regions were selected; q < 0.001 Å-1, q = 0.001 - 0.02 Å-1 and q = 0.02 - 0.5 Å-1. The unified fit model is based on the approach proposed by 83 Beaucage.181,182 The fit performed in each level of q-region can be described by a combined Guinier – Porod regime. The model considers particles to be spherical and centrosymmetric in shape.182 However, it can be extended to scatterers of various shapes, such as spheres, rods, lamellae, and cylinders. This feature is based on the model’s formulation in terms of the radius of gyration (Rg) and free power-law slope. The features in these unified levels represent the scattering response of the microstructural features in the size range of a few nanometers to a few micrometers. Finally, to evaluate the changes in the chemical composition, halloysite and kaolinite samples were heat treated at 150 °C and 700 °C for 1 hour in a small benchtop muffle furnace (Thermo Scientific Thermolyne FB1410M, Asheville, NC) and infrared (IR) spectra of samples were collected in an Attenuated Total Reflection (ATR) mode using an Attenuated Total Reflection-Fourier Transform Infrared spectrometer (ATR- FTIR, NicoletTM iS50, Waltham, MA). The pore size distributions (PSD) of halloysite treated at 90 °C and 700 °C, respectively, were determined from N2 adsorption-desorption isotherms using the Brunauer−Emmett−Teller technique (BET) (Quantachrome Autosorb iQ Analyzer, Boynton Beach, FL). Prior to measuring the isotherms, the powdered samples were outgassed at 90 °C for 24 hours. The organization of pores in the consolidated halloysite sample was determined using nano-XCT (X-ray computed tomography, ZEISS Xradia Ultra 810) with the voxel resolution of 32 nm. Nano-XCT imaging was performed on a consolidated halloysite particle with a diameter of about 100 μm. The laboratory-based measurements, coupled with in-operando data, provided detailed insights into the morphological, structural, and chemical evolution of halloysite during thermal treatment. 84 4.3 RESULTS AND DISCUSSION The structural changes in halloysite on heating are determined using Wide Angle X-Ray Scattering (WAXS) and Small Angle X-Ray Scattering (SAXS) measurements and the weight changes corresponding to the changes in the structure are determined using Thermogravimetric Analyses (TGA) as discussed in Section 4.3.1. The corresponding morphological features are determined from Ultra-Small and Small Angle X-Ray Scattering (USAXS/SAXS) measurements and validated using BET pore size distributions. The pore connectivity is determined from nano-XCT measurements, as noted in Section 4.3.2. 4.3.1 Structural Changes during Thermal Treatment of Halloysite The changes in the weight of halloysite upon thermal treatment, determined using TGA, are presented in Figure 4.2. The first derivative of weight change (%) is also determined and represented by the red curve in Figure 4.2. Based on the changes observed in the weight, the thermal treatment process is divided into four different stages of temperature ranges. Stages I, II, III, and IV correspond to temperature ranges of 25 to 125 °C, 125 to 400 °C, 400 to 625 °C, and 625 to 875 °C, respectively. In stage I, the weight loss in the range of ~50 °C to ~125 °C is associated with the removal of adsorbed or interlayer water in the halloysite 47,48,278,279. No significant changes in the weight are observed during stage II. In stage III, corresponding to temperatures in the range of 400 - 625 °C, the major weight change is noted by the dip in the first derivative curve at ~475 °C. This change is associated with the dehydroxylation of halloysite and conversion to meta-halloysite 47,278,279. Finally, in the last stage which corresponds to temperatures in the range of 625 - 875 °C, no significant changes are noted in the TGA curve. This stage is regarded as the stage of complete dehydroxylation of halloysite and the persistence of 85 the meta-halloysite phase. Figure 4.2 Influence of temperature on weight changes of halloysite as determined by thermogravimetric analysis. Stage I corresponds to the loss of interlayer water. Stage II represents the halloysite structure without interlayer water present. Stage III represents the dehydroxylation of the halloysite structure. Stage IV represents the structure of halloysite after complete dehydroxylation. Additional insights into the structural changes of halloysite during these stages are obtained from SAXS and WAXS curves. The SAXS curves (q = 0.4 Å-1 – 1.0 Å-1) during the thermal treatment in all four stages are presented in Figure 4.3. In fully dehydrated halloysite, the interlayer spacing between the alumina and silica layers is ~ 7 Å. Due to hydration or water uptake, the interlayer slightly increases to ~ 10 Å 50. In our sample, we observe partial hydration since two peaks are observed around the q values of 0.63 Å-1, and 0.82 Å-1 corresponding to the interlayer basal spacing of 9.8 Å and 7.7 Å, respectively (Figure 4.3 (a)). 86 Figure 4.3 Changes in the interlayer basal spacing as a function of temperature in the q range of 0.4 - 1 Å-1 determined from Small Angle X-ray Scattering (SAXS). During stage I as the temperature increases from 25 °C to 125 °C, the interlayer water is removed as shown by the eventual disappearance of the peak around 0.63 Å-1 (d001 = 9.8 Å). This leaves behind a fully dehydrated halloysite with the interlayer spacing of ~7.4 Å. This loss of water could be associated with the first dip in the TGA curve (Figure 4.2) during stage I. As the heating progresses, no significant changes are observed in the structure of fully dehydrated halloysite (Figure 4.3 (b)). The trends noted in the SAXS regime during stage II could also be explained by the absence of significant changes in the TGA curve (Figure 4.2). The major changes are observed in the SAXS regime during the dehydroxylation step in stage III, where the interlayer basal spacing (d001) diminishes upon heating. The dehydroxylation step is completed around 625 °C (Figure 4.3 (c)) where both alumina and silica layers fuse together to produce amorphous 87 meta-halloysite.47,278 Finally, during the last stage IV, no additional changes in the structural arrangement of meta-halloysite are noted. Figure 4.4 Changes in the structural arrangement of halloysite clay during thermal treatment determined using Wide-Angle X-Ray Scattering (WAXS) measurements. The panels at the bottom show the comparison of WAXS curves with halloysite with interlayer basal spacing at 7 Å and 10 Å. Additional details about the structural changes at higher q values are determined using the in-operando WAXS measurements. The WAXS patterns of the halloysite sample show the changes in the structural features as a function of temperature relative to the WAXS patterns of halloysite-7Å, and halloysite-10Å281 in Figure 4.4. The changes 88 in the characteristic (042) and (060) peaks of halloysite on thermal treatment are presented in Figures 4.5 (a-1) and (b-1), respectively. The corresponding changes in the intensities of both peaks are shown in Figures 4.5 (a-2) and (b-2), respectively. The major changes in the peak intensities are observed around ~475 °C during stage III, which is the starting point for halloysite dehydroxylation. Throughout this stage, the peak intensity decreases until 625 °C and this peak completely diminishes as the temperature transitions into stage IV. Figure 4.5 Changes in the characteristic halloysite peaks where (a-1) and (b-1) represent hkl reflections of (042) and (060), respectively, as measured using Wide-Angle X-Ray Scattering (WAXS) measurements. The integrated peak intensities normalized with respect to the maximum values are presented in (a-2) and (b-2). Combining the insights from TGA, SAXS and WAXS curves, the transitions in halloysite structure can be explained through the following reactions. Stage I/II: 89 25−125 °C Al2O . 3 SiO . 2 (OH) . 4 nH2O → Al . .2O3 SiO2 (OH)4 + nH2O (4.1) 25−125 °C hydrated halloysite → anhydrous halloysite Stage III/IV: 400−625 °C Al O .SiO .2 3 2 (OH)4 → Al .2O3 SiO2 + nH2O (4.2) 400−625 °C anhydrous halloysite → meta-halloysite 4.3.2 Morphological Changes during Thermal Treatment of Halloysite Nanotubes To monitor the evolution of morphology of halloysite nanotubes, the combined USAXS/SAXS curves are analyzed for pore size and morphology. The full range of in- operando USAXS/SAXS data is presented in Figure 4.6. The knee-like features around 0.003 Å-1 and 0.02 Å-1 and the subsequent scattering intensities are fitted using the ‘unified fit’ tool of the Irena program179 in IgorPro software using the approach proposed by Beaucage.181,182 The theory describes different levels of related scattering features in multicomponent systems. Each scattering region, i, is defined by a Guinier (knee-like feature) and an associated power-law exponent. The Guinier describes the structure corresponding to the specific scattering regime, i, whereas the power-law exponent provides details about the geometry of that structural arrangement. This approximation of Guinier’s exponential form and the power-law for a specific structural level, i, as proposed by Beaucage 181 is shown in equation 4.3. 𝑞2𝑅2𝑔 (erf(𝑞𝑅𝑔/√6)) 3 𝐼(𝑞) = ∑ 𝑃𝑖𝑖[𝐺𝑖 exp (− ) + 𝐵𝑖( ) ] + 𝐵𝑔 (4.3) 3 𝑞 In the above equation, Gi and Bi represent the Guinier exponential prefactor and a constant prefactor, respectively. The Rg is the radius of gyration and Pi corresponds to 90 the power-law exponent for a specific structural regime, i. A power-law exponent of 4 represents a smooth interface. Power-law exponents between 3 and 4 correspond to the roughness in geometries similar to surface fractals while values smaller than 3 represent mass fractal geometries.108,182 Finally, the Bg represents the residual background intensity. In our data, two knee-like (Guinier) features around 0.003 Å-1 and 0.02 Å-1 are identified which correspond to the scattering from nanotube curvature and pores, respectively. The Rg values calculated from these two levels provide details about the dimensions of pores and halloysite nanotubes. Figure 4.6 Changes in the combined slit-smeared USAXS/SAXS experimental curves of halloysite nanotubes during thermal treatment. The three unified levels are fitted on the combined USAXS/SAXS curves between the q values of 0.0001 – 0.5 Å-1. The first unified level in the q range of 0.02 – 0.5 Å-1 provides information about the pores in the halloysite sample, the second unified level in 91 the q range of 0.001 – 0.02 Å-1 provides information about the changes corresponding to the curvature of the nanotubes, while in the third unified level for the q values < 0.001 Å- 1, no Guinier plateau is noted. In this range, the power-law exponent is fitted as a free fitting parameter by setting the G value to zero 11,187. The results from the unified fits are presented in Figure 4.7. A comparison of experimental scattering data and simulated unified fits for halloysite nanotubes at different temperatures is presented in Figure S4.1. The scattering length density (SLD) can play an important role in the quantification of physical parameters. During stage I, the SLD of halloysite is evaluated with reference to water (interlayer/adsorbed). At this stage, an SLD of 83.11 × 10-6 Å-2 is used. For stages II and III, an SLD of 73.2 × 10-6 Å-2 is used to account for the absence of water in the nanopores. Finally, in stage IV, an SLD of 70.19 × 10-6 Å-2 is used based on the chemical formula for meta-halloysite (Al2Si2O5). Analyses of the USAXS/SAXS data show that the characteristic dimension of the pores, Rg, is around 6.4 nm at 25 °C and remains constant until 550 °C (Figure 4.7 (a)). On heating from 575 °C to 750 °C, the Rg decreases to ~ 6.1 nm. After 775 °C , the Rg value starts to increase and achieves a value of ~6.6 nm at 850 °C and 875 °C. The slight widening of the halloysite pore, which can be attributed to the sintering of the alumina and silica groups in each TO layer, was observed by Ouyang and co-workers47 using high resolution transmission electron microscopy (HRTEM). 92 Figure 4.7 Radii of gyration (Rg) and power-law slopes estimated via unified fit models for scattering from pores (0.001 – 0.02 Å-1) (a) and nanotubes (0.02 – 0.5 Å-1) (b). This increase in Rg is accompanied by a slight decrease in the value of the power- law slope (Figure 4.7 (a)). The power-law slope for scattering from pores remains almost constant (~3.9) throughout the heating ramp and just slightly decreases at 850 °C to 3.87 and eventually attains a value of 3.77 at 875 °C. The slight increase in the roughness of 93 the pore-solid interface could be related to the sintering of pore walls in the halloysite The trend in the power-law slopes suggests the presence of surface fractals with smooth solid-pore interfaces throughout the heat treatment process, with a slight increase in roughness at higher temperatures of 850°C and 875 °C.103,108,195,282 Figure 4.8 3D pore network of consolidated halloysite characterized by nano XCT at the voxel resolution of 32 nm (a) and pore size (diameter) in 3D pore network represented by computed local thickness (b). 94 Further, the 3D pore network in consolidated halloysite is investigated by selecting a 3D section of 12 μm × 6 μm × 6 μm from the nano-XCT scanning results. The 3D pore network of consolidated halloysite is shown in Figure 4.8 (a). Since the nano- XCT voxel resolution is 32 nm, the internal pores of halloysite nanotubes are not characterized in this scanning. The 3D pore network of our nano-XCT image represents the inter-nanotube pore networks in the consolidated halloysite, which accounts for about 13% of the porosity. Pore diameters from the nano-XCT scanned consolidated halloysite are analyzed by computing the local thickness of the 3D pore network with ImageJ, where the diameter of the largest sphere that fits inside the pore network is used to represent the pore size.283 As shown in Figure 4.8 (b), the purple color channels indicate that the majority of the pores have a diameter of around 100 nm. However, in case of scattering from nanotube curvature, the Rg value remains around 120 nm until 600 °C (Figure 4.7 (b)). The Rg value starts to increase during stage IV at temperatures in the range of 625 °C – 875 °C and finally achieves a value of 161 nm. This increase in the value of Rg could be associated with the structural disordering during the re-organization of silica tetrahedral (T) and alumina octahedral (O) sheets between 625 °C – 875 °C upon dehydroxylation, causing a slight expansion in the halloysite nanotubes.278,284 The structural disordering because of dehydroxylation causes an increase in the surface roughness of the nanotubes.278 A slight increase in the surface roughness of halloysite nanotubes at temperatures higher than 600 °C is also noted from the power-law slopes. Initially a power-law slope of 2.48 is noted, which achieves a final value of 2.36 at 875 °C. This slight downward shift in the value of the power-law slope is observed around 600 °C, the same temperature at which Rg starts to increase, which 95 could indicate an increase in the roughness at the surface of the halloysite nanotubes occurring simultaneously with the expansion in the size of the halloysite nanotube. The increase in the surface roughness of halloysite nanotubes, after heating in excess of 600 °C, is also evident by a decrease in the power-law slopes for q values < 0.001 Å-1, presented in Figure S4.2. The scattering in this region is contributed by the surface parallel to the axis of halloysite nanotubes. The power-law slope initially has a value of 3.23 at 25 °C and does not change significantly until 575 °C, where it has a value of 3.26. Upon further heating beyond 600 °C, the power-law slope values decrease and reach a final value of 2.91 at 875 °C. Ideally, for rod like surfaces, as in the case of halloysite nanotubes, the power-law slopes in this q range should reach a value of 1. However, the higher values of slopes here indicate the presence of fractal morphology at larger length scales. To determine the effect of thermal treatment on pore size distribution (PSD) of the halloysite sample, N2 adsorption-desorption isotherms at 77 K were determined for halloysite treated at 90 and 700 °C, respectively. The N2 adsorption-desorption isotherms of both samples are presented in Figures 4.9 (a) and 4.9 (b). Both samples exhibit the type IV isotherm with a type H3 hysteresis loop as per the International Union of Pure and Applied Chemistry (IUPAC) classification.237,278 The hysteresis loop could be associated with the filling and emptying of the cylindrical mesopores of halloysite by capillary condensation.276 Further, the multi-point BET surface areas for dehydrated halloysite and halloysite treated at 700 °C are 52.3 m2/g and 53.3 m2/g, respectively. The PSD curves for both halloysite samples are shown in Figure 4.11 (c). In both cases, two types of major pore populations are observed around 1.9 nm and 6.15 nm. The feature 96 around 1.9 nm could be attributed to either type of the newly formed pores during the dehydration process.278,285 However, the mesopores observed around 6.15 nm could be categorized as cylindrical pores inside the halloysite. These values are in reasonable agreement with those obtained from USAXS/SAXS data (Figure 4.7 (a)). Figure 4.9 N2 adsorption-desorption isotherms for halloysite treated at 90 °C (a) and halloysite treated at 700 °C (b). The pore size distribution as calculated from the BJH model on desorption isotherms (c). 97 4.3.3 Comparison of Structural and Morphological Changes in Kaolinite and Halloysite Given the similarity in the silica tetrahedral (T) and alumina octahedral (O) features in planar kaolinite and tubular halloysite, but the differences in the morphological organization, we contrast the influence of heat treatment in these two materials. It is observed that tubular halloysite can accommodate the multiple water layers (n = 0-2) between its interlayers compared to platy kaolinite, where strong hydrogen bonding between the interlayers does not permit any water layers.269,272,274 To account for these effects of difference in morphology of these clays, in the following section, we discuss the differences in the bond ordering in kaolinite and halloysite and the nano-scale morphological features, such as the interlayer basal spacing, when both clays are heated to temperatures as high as 875 °C. To investigate our hypothesis, both halloysite and kaolinite clays were subjected to similar conditions of thermal treatment. Differences in the composition of untreated clays and both clays treated at 150 °C and 700 °C are presented in the IR spectra in Figure S4.3. For kaolinite (Figure S4.3 (a)), four distinguished peaks for -OH stretching vibrations are identified at 3687, 3668, 3649 cm-1 for surface hydroxyl groups of the octahedral Al-OH and at 3618 cm-1 for hydroxyl groups between the sheets in both untreated clay (25 °C) and clay treated at 150 °C.286,287 These peaks are diminished after thermal treatment at 700 °C, which corresponds to the dehydroxylation of kaolinite clay.288 In the case of halloysite (Figure 4.3 (b)), only two bands for OH stretching vibrations are noted at 3693 and 3621 cm-1, for both untreated halloysite (25 °C) and halloysite treated at 150 °C. The diminishing of the two middle peaks, which were noted in kaolinite, could correspond to the absence of some out-of-phase OH vibrational modes 98 in halloysite.286 Additionally, a band at 3548 cm-1 is also noted, which could be assigned to the hydrogen bonded water within the interlayer of halloysite at 25 °C.286,288 The bands for Si-O stretching vibrations in both kaolinite and halloysite are noted in the range of 1118 – 996 cm-1. In the case of kaolinite, three bands are noted at 1114, 1024, and 996 cm-1 for Si-O, while for halloysite, the doublet around 1114, and 1024 cm- 1 disappears and a single broad band is noted at 1118 cm-1 along with the Si-O in-plane vibrations at 996 cm-1.274,286 The reason for the doublet disappearance and emergence of the broad band is the restriction of Si-O-Si bond vibrations around 1024 cm-1 due to the effects induced by the rolled morphology.274,286,289 The presence of strong bands in both clays around 908 cm-1 is attributed to OH in-plane bending vibrations from the inner surface hydroxyl groups present between the layers.286,288,289 In the case of kaolinite, an additional peak is noted at 935 cm-1, which corresponds to the in-plane bending vibrations of surface hydroxyl (OH) groups.286–288 This is noted only in case of kaolinite because in halloysite the vibration of surface OH groups is hindered due to the presence of interlayer water.286 The bending vibrations for Al-OH bonds are noted around 790 and 749 cm-1 in both unheated (25 °C) and heated (150 °C) kaolinite and halloysite samples.286,288 Finally, in both cases, those bands corresponding to O-H, and Al-OH diminish upon dehydroxylation (curves for 700 °C) and peaks corresponding to Si-O stretching vibrations dominate the spectra. The main peak is noted at 1054 cm-1, which is typical of amorphous meta-kaolinite/meta-halloysite systems.288,290 From these observations we note that the differences originating from the morphological organization also have an effect on the bonding behavior in kaolinite and halloysite. These differences diminish upon dehydroxylation resulting in almost identical spectra for both clays (red curve in 99 Figure S4.3). Based on the observations in this study and a previously reported study49, we compared the structural and morphological changes occurring in halloysite and kaolinite during in-operando heat treatment. The plots comparing changes in the interlayer basal spacings (d001) and characteristic basal peak (001) from both studies are presented in Figures 4.10 (a) and 4.10 (b), respectively. The interlayer basal spacing for kaolinite does not undergo significant changes until complete dehydroxylation occurs around 625 °C. In contrast, the interlayer basal spacing in halloysite slightly decreased to 7.4 Å from 9.8 Å during stages I and II and achieved a value of ~7.2 Å during stage III. Figure 4.10 Comparison of structural changes in kaolinite and halloysite subjected to in- operando heat treatment. The evolution in interlayer basal spacing d001 (a) and (001) peak intensities (b) are presented as a function of temperature. The kaolinite data was adopted from Gadikota et al.49 100 The integrated intensity of the characteristic basal peak (001) for kaolinite initially decreased in stage I and then remained constant until the middle of the dehydroxylation stage, while in case of halloysite, the peak intensity remained almost constant until 450 °C and then started to decrease. However, in both clays, the peak intensities diminished at around the same temperature value (625 °C) corresponding to the completion of dehydroxylation. The evolution of morphological features in both clays upon thermal treatment is shown schematically in Figure 4.11. In the case of platy kaolinite, the nanoscale porosity is affected by the collapse of interlayer spacing, when heated to temperatures higher than 600 °C. However, in halloysite, initially the interlayer spacing decreases from ~9.8 Å to ~7.4 Å due to the removal of interlayer water. Figure 4.11 Schematic representation of the evolution in the structure of kaolinite and halloysite during thermal treatment. 101 4.4 CONCLUSIONS In this study we elucidate the structural transformations and morphological evolution during the heat treatment of naturally occurring halloysite with nanotubular morphology to temperatures as high as 875 °C. Dehydroxylation of halloysite starts around 400 °C and is completed around 625 °C, resulting in the formation of amorphous meta-halloysite, as determined from in-operando Wide Angle X-Ray Scattering (WAXS) measurements. Combined USAXS/SAXS data were used to evaluate the changes in the pore size and curvature of halloysite nanotubes during thermal treatment. The slight widening of the nanotube diameter was attributed to the dehydroxylation phenomenon and slight expansion of the halloysite structure, whereas the increase in the nanotube wall thickness corresponded to the changes in surface texture resulting in rougher walls. The average pore size of halloysite nanotubes, as informed by USAXS/SAXS measurements, were also confirmed using N2 adsorption-desorption and nano-X-Ray computed tomography characterizations. A comparison of the structural and morphological evolution of kaolinite and halloysite on heating showed that nanoscale porosity in halloysite is preserved by the pore space of the nanotubes, while in the case of kaolinite, collapses when heated at temperatures higher than 600 °C. These studies demonstrate the differences in thermally induced transformations of alumino-silicates with similar chemical structures but different morphologies. 102 4.5 SUPPLEMENTARY MATERIAL Figure 4.12 Figure S4.1 Representative Ultra-Small and Small Angle X-ray Scattering (USAXS/SAXS) experimental data for halloysite sample at 25 °C (a), 125 °C (b), 400 °C (c), 500 °C (d), 625 °C (e), and 800 °C (f). Red lines represent the simulated scattering patterns. The simulated data were obtained using 3 levels of unified fit models for the q values < 0.001 Å-1 and in the ranges of 0.001 – 0.02 Å-1, and 0.02 – 0.5 Å-1, respectively. 103 Figure 4.13 Figure S4.2 Power-law slopes estimated for q values < 0.001 Å-1 in the Ultra-Small Angle X-ray Scattering (USAXS) region using the unified fit model. 104 Figure 4.14 Figure S4.3 Functional groups in kaolinite (a) and halloysite (b) as identified using ATR-IR spectroscopy. The insets show the zoomed-in spectra between the range of 375-3550 cm-1 for -OH stretching vibrations. 105 5 DESIGNING CO2-RESPONSIVE MULTI-FUNCTIONAL NANO-SCALE FLUIDS WITH TUNABLE HYDROGEL BEHAVIOR FOR SUBSURFACE ENERGY RECOVERY The contents of this chapter have been published as a journal article: H. Asgar, J. Ilavsky, and G. Gadikota, Energy and Fuels, 2019, 33(7), 5988-5995 5.1 INTRODUCTION Directing subsurface fluid flow and achieving tunable controls on permeability in the subsurface environments necessitates the development of tunable novel multifunctional subsurface fluids. With more than 60% of U. S. oil and natural gas production supplied by unconventional hydrocarbon reservoirs4 and increasing interest in harnessing geothermal environments for renewable energy, there is an emerging need to develop efficient strategies for energy recovery. Conventional approaches to enhance permeability include hydraulic fracturing and the use of proppants to keep the pore spaces open.54,55 In conventional hydrocarbon reservoirs, the use of CO 56–582 thickening agents and microemulsions291–293 has been proposed to enhance CO2 utilization for enhanced oil recovery. While CO2 injection is used in conventional reservoirs to facilitate the expansion of oil to aid flowability, some of the challenges in using alternative fracturing fluids such as CO2 include the ability to transport the proppants. 294 Therefore, the following attributes need to be considered when evaluating multifunctional fluids for subsurface energy recovery: (i) enhanced CO2 delivery to aid the miscibility of the hydrocarbons, (ii) potential to form hydrogels to divert flow, enhance fracturing or refracturing at elevated pressures, (iii) ability to transport proppants, and (iv) potential for phase transformations from gel-like to fluid-like in response to chemical or pressure- based perturbations. Achieving the desired properties of these multifunctional nanofluids requires that 106 the fluids have tunable gelation and rheological behaviors, high CO2 capture and delivery capacity, and proppant carrying ability. The concept of designing nanofluids with tunable properties for subsurface energy recovery coupled with CO2 utilization, starting from silica nanoparticles with swellable polymer chains as the building blocks has not been explored. This approach of designing tunable fluids allows us to confer desirable properties.295–302 One example in this regard refers to enhanced CO2 uptake in nanoscale organic-inorganic materials via enthalpic and entropic effects. Conventional CO2 capture using amine-bearing solvents is primarily driven by the enthalpy effect arising from the chemical interactions between CO2 and task-specific functional groups. The absorption of small gaseous molecules (e.g., CO2) in the organic chains of these materials has been shown to reduce the free energy of the chains. In some cases, the organic/polymeric chains act like a fluid when tethered to inorganic nanoparticles and prevent the agglomeration of nanoparticles by filling the gaps between them. Further, the structural rearrangement of the organic chains (entropic effect) has been shown to improve the enthalpic effect by changing the accessibility and orientation of the task-specific functional groups. Therefore, it is important to correlate the structural changes in the organic chains to the CO2 capture mechanism. 302 Further, the viscosity of the nano-fluids has been shown to increase when exposed to CO2 which is challenging to manage in CO2 capture plants. These effects can be enhanced by tuning the chemical affinity of materials.303–305 When tuning materials for subsurface energy recovery, developing precise control over the rheology and viscosity of these fluids is essential. Ideal subsurface fluids should have the ability to penetrate through the pores of shale rocks followed by hydrogel 107 formation to divert flow or stimulate fractures. Therefore, in this paper, we propose the development of CO2 responsive multi-functional nanofluids and the underlying chemo- morphological changes in these materials in the presence of CO2. The task-specific functional group was poly(allyl amine) (referred to as PAA in this paper) which has been shown to form hydrogels and induce fractures in geothermal environments at temperatures and pressures in the range of 150 – 300 °C and 250-333 atm.306,307 However, for these fluids to be relevant in the context of hydraulic fracturing, their chemistries and morphologies need to be tuned to achieve the formation of hydrogels at lower temperatures and lower pressures. In this paper, we propose the concept of tethering these nanoparticles with polymer chains to achieve enhanced formation of gels at similar conditions of temperature and pressure. The chemistry of the amine-functional groups is important to evaluate in this context. For example, unlike in the work on solid adsorbents reported by Chaikittisilp and co-workers308 where low molecular weight poly(allylamine) was impregnated with silica foams for CO2 capture from gases, this effort focuses on using silica nanoparticles and PAA as the building blocks to develop novel nanofluids for directing flow in subsurface environments. Further, weak hydrogen bonds facilitate the ease of reversibility of hydrogel formation and dissolution, as noted by Jung and co- workers.306 In this study, we investigate the hypothesis that novel nanofluids constructed from SiO2 nanoparticles and PAA show enhanced hydrogel formation due to higher CO2 uptake compared to pure polymer, PAA. The CO2 absorption reaction with aqueous amine-based sorbents for primary and secondary amines is illustrated in Figure 5.1.309,310 Generally, in the first step, CO2 reacts with amines to produce ammonium-carbamate-zwitterion intermediates. In the second 108 step, the zwitterion reacts with other free amine groups to produce ammonium-carbamate ion pairs. Under the hydrated conditions, the carbamate ions may hydrolyze to give bicarbonate ions (Figure 5.1 (c)), eventually forming carbamic acid (NHCOOH or NCOOH). While the chemistry of CO2 interactions with free amine-bearing functional groups is relevant in this context, understanding how the chemical interactions change when PAA is tethered to the silica surface is not as well understood. Figure 5.1 Illustration of CO2 uptake by aqueous amine (a) to produce the intermediate zwitterion (b) production of carbamate ion and the ion pair, and (c) regeneration of amine during hydrolysis of carbamate ion to produce bicarbonate ion. Even before considering these materials for potential fracturing applications, the following research questions need to be addressed: (1) How does the CO2 uptake behavior vary in pure PAA as opposed to PAA tethered to the silica surface? (2) What are the molecular-scale phenomena contributing to the differences in the CO2 absorption behavior in pure PAA vs. PAA tethered to the silica nanoparticles? (3) How does the dynamic nano- and meso-scale morphology of these nanofluids evolve in the presence of 109 CO2? To address these fundamental questions prior to using these fluids for subsurface energy recovery, the CO2 uptake behaviors was quantified using micro-gas chromatography measurements and the changes in the functional behaviors showing the binding behavior of CO2 was evaluated using Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR). Dynamic nano- and meso-scale morphological changes in the nanofluids were captured using in-operando Ultra Small/Small Angle X-Ray Scattering (USAXS/SAXS) measurements. 5.2 MATERIALS AND METHODS 5.2.1 Synthesis of SiO2-PAA nanofluids Suspensions of SiO2 nanoparticles (dia. = 50 nm) in DI water with the concentration of 10mg/mL were purchased from nanoComposix. Aqueous fluids composed of 20 wt.% polyallylamine (PAA) with an average MW ~ 17,000 was purchased from Sigma Aldrich. For the preparation of PAA tethered SiO2 nanoparticle suspensions, 1000 ppm PAA solution in DI water was prepared by stirring at 600 rpm and 30 °C for 1 h. Then, 1 wt.% SiO2 nanoparticles were added in the above solution to make the final volume of 10 mL and stirred under the same conditions for 8 h. As a result of addition of SiO2 nanoparticles, the PAA solution turned from clear to slightly cloudy (Figure S5.1). For comparison purposes, 1000 ppm solution of PAA was also prepared. In the subsequent sections, the 1000 ppm PAA solution and 1 wt.% SiO2 with 1000 ppm PAA are referred to as PAA and SiO2-PAA, respectively. 5.2.2 Experimental Setup and Characterization Breakthrough experiments to measure CO2 absorption under dynamic conditions 110 were performed by using the experimental setup as shown in Figure 5.2. In a typical experiment, 4 mL of sorbent (PAA or SiO2-PAA) was loaded in the cell, and it was degassed using a vacuum pump. Then, the system was stirred at 300 rpm and 10% CO2 (balanced N2) was purged through the cell at 5 mL/min. The concentration of the gas coming out of the cell was monitored using an online gas chromatography instrument (Micro GC Fusion® Gas Analyzer, Inficon, Bad Ragaz, Switzerland). The absorption experiments were carried out until the equilibrium was achieved i.e. when the composition of the outlet gas from the cell matched the composition of the inlet gas (10% CO2 and 90% N2). Figure 5.2 Schematic of the experimental setup for measuring CO2 uptake. The CO2 absorption capacity was determined by the breakthrough curves using the following equation:311 111 𝐹𝐶0𝑖𝑡𝑛 𝑛𝑖𝑎𝑑𝑠 = (5.1) 𝑉 where nadsi is the dynamic absorption capacity of any gas i, F is the molar flow of CO2, C0i is the concentration of the gas i entering the column, V is the volume of sorbent, and tni is the stoichiometric time corresponding to the gas i, which can be estimated determined from the breakthrough profile according to equation: 𝑡 𝐶 𝑡𝑛𝑖 = ∫ (1 − 𝐴𝑖⁄𝐶 ) 𝑑𝑡 (5.2) 0 0𝑖 In the above equation, C0i and CAi are the concentrations of gas ‘i’ going in and coming out of the cell, respectively. To evaluate changes in the chemical bonding after CO2 absorption, infrared (IR) spectra were acquired in an Attenuated Total Reflection (ATR) mode using an Attenuated Total Reflection-Fourier Transform Infrared spectrometer (ATR-FTIR, NicoletTM iSTM 10, Waltham, MA) before and after CO2 absorption experiments (Table 5.1). ATR measurements were also used to evaluate the effect of temperature on the changes in the functional groups of the PAA-CO2 and SiO2-PAA-CO2 fluids when exposed to CO2. For these experiments, the samples were stirred at 300 rpm for 30 minutes each from 30 to 90 °C with a step of 10 °C. The changes in the IR peaks of absorbed CO2 species were monitored with the corresponding changes in temperature to elucidate the mechanism of CO2 absorption on PAA and SiO2-PAA was proposed. The in-operando USAXS/SAXS measurements were performed to monitor the morphological changes during CO2 absorption and hydrogel formation in SiO2-PAA solution. The measurements were performed at Sector 9-ID at Advanced Photon Source (APS) in Argonne National Laboratory (ANL), Argonne, IL using the original Bonse- 112 Hart double-crystal setup.175,176 The total X-ray flux, energy, and wavelength received by the instrument during the measurements at the sample position, were ~1013 photon s−1, 21.0 keV, and 0.59 Å, respectively. Instrument calibrations were performed with silver behenate. The USAXS and SAXS data had enough overlap in the q range which allowed the accurate merging of these data. Finally, Nika178 and Irena179 software packages embedded in the IgorPro software (Wavemetrics, Lake Oswego, OR) were used for data reduction and analysis. 5.3 RESULTS AND DISCUSSION 5.3.1 CO2 Uptake Capacity CO2 absorption behavior in SiO2-PAA and PAA bearing nanofluids was evaluated from the breakthrough curves presented in Figure 5.3. The dynamic absorption capacities of PAA and SiO2-PAA fluids were found to be 0.12, and 0.31 mmol/mL, respectively. SiO2-PAA nanofluids had a twofold higher capacity for CO2 absorption compared with the simple PAA solution. Moreover, to compare the absorption rates in PAA and SiO2- PAA, the slope values (min-1) from the breakthrough curves were determined over time. In the first hour (5-60 minute), the absorption rates were similar based on the analyses of the slopes which were found to be 2.57×10-3 min-1 and 2.81×10-3 min-1 for PAA and SiO2- PAA fluids, respectively. However, during the next hour, PAA reached the maximum absorption capacity in the dynamic conditions, whereas SiO2-PAA continued to absorb more CO2 and the slope values were 8.18×10 -4 min-1 and 2.59×10-3 min-1 for PAA and SiO2-PAA, receptively. In both the systems studied, the concentration of task-specific functional groups i.e., amines were the same (1000 ppm of PAA). Presence of SiO2 nanoparticles facilitated the increased capture of CO2 in case of SiO2-PAA. The higher 113 CO2 uptake by SiO2-PAA system could be attributed to the emergence of entropic effects in the polymeric/organic chains when tethered around the nanoparticles. These chains form stable cages for gas capture and enhance the ability of the material to capture and store more gas. Moreover, as a result of CO2 uptake, hydrogel formation was observed in SiO2-PAA fluids whereas no hydrogels were formed with the PAA solution. To understand this increased absorption by SiO2-PAA fluid, the CO2 absorption mechanisms in PAA and SiO2-PAA fluids were investigated using infrared spectroscopy measurements. Figure 5.3 Comparison of the breakthrough curves of CO2 absorption in PAA and SiO2- PAA fluids. Figure in the inset represents CO2 absorption capacity (mmol/mL) for these fluids. 5.3.2 Mechanism of CO2 Absorption In highly absorbing media, ATR is one of the most promising techniques to probe the intermolecular interactions.312 Therefore, to understand the CO2 capture mechanism 114 in PAA and SiO2-PAA, infrared spectra were obtained by using the ATR technique. To minimize the effect of the solvent (water) on the IR spectra, water was taken as the background before each measurement. ATR spectra of starting materials: 20 wt% PAA and 50 nm SiO2 nanoparticle suspension are presented in Figure S5.2. Table 5.1 IR band assignments for different observed functional groups. Wavenumber (cm-1) Functional Groups Ref. 3400 – 3000 N-H stretching modes 310,313,314 2900 – 2750 C-H stretching modes 310,314 2340 – 2355 C=O stretching mode from dissolved CO2 314 1650 – 1550 Asymmetric COO- from NCOO- 309,313–315 1494.67 1616.77 NH +3 bending from protonated primary amine 310,313,315 1596.75 N-H 310,314,315 deformations in amine 1459.9 C-H deformations 310,314 NH +2 bending from protonated secondary amine 1430 309,313 (NH) 1360.41 C-O stretching in bicarbonate HCO - 3153 1330 NCOO- stretching 310,313–315 Si-O-Si asymmetric Siloxane vibrations in 1113.35 314,316 (SiO)n group 1080 – 1000 C-N stretching vibrations 310 844.61 N-H out of plane deformations 317 782.68 Si-O-Si symmetric stretch 316 In the IR spectrum of PAA, the characteristic N-H asymmetric and symmetric vibrations originating from NH2 were observed at 3367.96 cm -1 and 3304.83 cm-1, respectively, with an N-H deformation peak at 1596.75 cm-1.310,313,314 Moreover, C-H stretching and deformation vibrations were observed at 2923.80 cm-1 (asym.), 2875.45 cm-1 (sym.) and 1455.7 cm-1, respectively.310,314 For SiO2, a broad band at 3521.8 cm -1 was observed for -OH groups along with a bands for Si-O-Si asymmetric stretch at 115 1113.31 cm-1 and symmetric stretch at 782.68 cm-1, respectively. 316 For the materials of interest in this study, 1 wt% SiO2-PAA and PAA nanofluids, the spectra were taken before and after CO2 loadings (Figure 5.4). It could be seen that the CO2 impregnation mechanisms for PAA and SiO2-PAA fluids were quite different. The difference could be associated with the nature of amine present for CO2 uptake in the respective samples. In the IR spectrum of PAA solution (Figure 5.4 (a)), a peak at 1616 cm-1 emerged for NH +3 species upon reaction with CO . 310,313,315 2 This peak could be associated with the protonation of NH2 group of primary amines (Figure 5.1). The hydrolysis of the carbamate ion is evident from the formation of bicarbonate (HCO -3 ) peak at 1360.16 cm-1.315 Additionally, a band at 2343 cm-1 was noted for C=O in dissolved CO .3142 The N-H stretching vibrations also became more prominent around 3000 cm -1 after CO2 loading, which could be associated with the formation of protonated NH + 3 species.310,313 N-H deformations after CO2 uptake shifted slightly to a lower wavenumber ~1500 cm-1. A new peak for out-of-plane N-H deformations at 844.61 cm-1 was noted after CO2 uptake by PAA, which could be attributed to the formation of NH + 3 creating an extra N-H bond. Moreover, the stretching vibrations for C-N bands were noted between 1000 and 1080 cm-1.310 However, in SiO2-PAA, the CO2 uptake was quite different as shown in Figure 5.4 (b). Most of the CO2 was captured as carbamate ions in this case. Along with a weak signal from NH +3 and HCO - 3 species at 1613.2 cm -1 and 1360.41 cm-1, respectively, peaks for NH +2 species were observed at 1430 cm -1.309,310,313–315 Additionally, prominent peaks for carbamate species at 1330 cm-1 and 1490.7 cm-1 for N-COO- and 1561.1 cm-1 for COO- were also observed.309,313–315 Moreover, stretching vibrations for C-N and C=O 116 bands for dissolved CO2 were noted in the same range as PAA solution. Figure 5.4 Identification of the functional groups present in (a) 1000 ppm PAA and (b) SiO2-PAA nanofluids before and after CO2 loading using ATR-FTIR spectra. The peak from NH +2 species upon reaction with CO2 were expected to have emerged from the protonation of NH groups in SiO2-PAA compared with the NH2 groups in PAA solution. These observations were useful in explaining the mechanisms of CO2 uptake in both the fluid systems. Additionally, the CO2 release from SiO2-PAA fluids was investigated to understand the reversibility aspect of these nanofluids. For this purpose, nitrogen (N2) gas (99.99%) was purged through the hydrogel (SiO2-PAA-CO2) for 30 minutes and ATR spectra were collected to investigate changes in the chemical bonding in the fluidic environments. The comparison of ATR spectra of SiO2-PAA and SiO2- PAA-CO2 before and after N2 purge is presented in Figure S5.3. On purging N2, the carbamate signals were significantly diminished. The CO2-bearing nanofluids were also mixed with excess water (200 µL nanofluid in 1000 µL DI water) which also contribution to the removal of CO2 and regeneration of the nanofluid (Figure S5.3). Furthermore, the nature of CO2 interactions with amines in the PAA and SiO2- 117 PAA was further explored by heating the systems up to 90 °C and observing the changes in the functional groups. For this purpose, the fluids were stirred for 30 minutes at temperatures between 30 and 90 °C with a step of 10 °C and the corresponding ATR spectra were obtained. These spectra were compared with the spectra taken immediately after CO2 uptake as shown in Figure 5.5 and Figure 5.6 for PAA and SiO2-PAA, respectively. Figure 5.5 Changes in the functional groups present in CO2 loaded-PAA fluids with increasing temperature determined using ATR-FTIR measurements. 118 Figure 5.6 Changes in the functional groups present in CO2-loaded SiO2-PAA bearing nanofluids with increasing temperature determined using ATR-FTIR measurements. Upon stirring and heating, shifts in the peaks for specific functional groups were noted which were used to infer the speciation of amines and the CO2 uptake mechanisms in these systems. On stirring and heating the fluid composed of 1 wt.% PAA, the emergence and growth of carbamate species at 1559.2 cm-1 and 1494.6 cm-1 for COO- and N-COO-,309,313–315 respectively was noted. These peaks became increasingly distinct on heating to 90 °C. The NH +3 and bicarbonate (HCO - 3 ) peaks were present until 70 °C and disappeared on further heating. However, at high temperatures, the carbamate peaks were still present in the system with a new peak around 1330 cm-1 for N-COO-.310,313–315. The N-COO- band at 1330 cm-1 was initially present as a shoulder peak but became more prominent when the protonated NH +3 and bicarbonate peaks started to disappear as the temperature increased. Further, increasing temperature resulted in the conversion of bicarbonate ions to carbamate ions (Figure 5.1 (c)). Additionally, the protonated species 119 (NH +3 ) were also not stable at higher temperatures. This observation was also supported by the disappearance of N-H out-of-plane bending vibrations around ~840 cm-1 after 60 °C.317 However, the mechanisms of binding CO2 in SiO2-PAA nanofluids were significantly different compared to pure PAA. At low temperatures of 25oC, CO2 was present in the form of bicarbonate ion (HCO -3 ), carbamate ion (N-COO -), and the protonated amines (both NH + +3 and NH 2). On stirring and heating, the peaks corresponding to NH +3 and bicarbonate species disappeared. However, the bands corresponding to NH +2 (~1430 cm -1), N-COO- (~1330 cm-1 and ~1490 cm-1), and COO- (~1560 cm-1) remained stable even after heating to higher temperatures. At 70 °C, a peak around 1595 cm-1 started to emerge, which was identified as N-H deformations from NH +2 . 310,314,315. In addition to the emergence of this peak, the bands from carbamate ions between 1565 cm-1 and 1470 cm-1 started to merge at 1521.6 cm-1 at 90 °C arising from COO- stretching.310 These changes suggest that most of the CO2 initially captured in SiO2- PAA nanofluids was in the form of carbamate ions and protonated species from secondary amines (NH +2 ), with the presence of some of the protonated primary amine (NH + 3 ) and bicarbonate ions (HCO -3 ). With an increase in temperature, the bands from carbamate species started to merge and signal from N-H deformations corresponding to NH +2 were observed. Based on the observations presented in Figures 5.4, 5.5, and 5.6, the functionalization mechanism of SiO2 nanoparticles with PAA and CO2 absorption mechanisms by PAA and SiO2-PAA were proposed, which are presented in panels (a) and (b) of Figure 5.7. Briefly, the polymer PAA and SiO2 nanoparticles are organized 120 via hydrogen bonds between the -OH groups on the silica nanoparticles and the PAA. The formation of hydrogen bonds between the -NH2 groups on the aliphatic amines and -OH groups from SiOH systems were reported by Eckstein and co-workers 318. The enhanced CO2 binding mechanisms in SiO2-PAA nanofluids show the formation of hydrogels at room temperature compared to the pure PAA solution (Figure 5.7 (c)). Figure 5.7 Proposed mechanism for CO2 uptake in (a) PAA and (b) nanofluids containing PAA tethered to SiO2 nanoparticles. Hydrogel formation in nanofluids containing PAA tethered to SiO2 nanoparticles is more prominent compared to fluids containing PAA as shown in (c). Solutions containing PAA or PAA tethered to 1 wt% SiO2 nanoparticle were exposed to CO2 partial pressures of 1 atm for 20 minutes. 121 5.3.3 Morphological Changes during CO2 Capture Tuning the rheological behaviors of the nanofluids necessitates an understanding of the spatial scales that correspond to the formation of hydrogels. Insights into the intra- and intermolecular correlations of polymeric chains tethered to the nanoparticles in the solution can be developed from combined in-operando Ultra-Small and Small Angle X- Ray Scattering (USAXS/SAXS) measurements. The combined USXAS and SAXS curves during the CO2 absorption are shown in Figure 5.8. The form factor of the polymer tethered nanoparticles is captured in q-range of 3 x 10-3 Å-1 – 0.2 Å-1, while the large network formed by the polymeric chains tethered to the SiO2 nanoparticles corresponded to q lower than 3 x 10-3 Å-1. Figure 5.8 Time-resolved USAXS/SAXS measurements of nanofluids containing 1 wt% of PAA tethered to SiO2 nanoparticles (inset: SAXS curves of 1000 ppm PAA) (a) and the corresponding changes in the power law slopes determined in the q range < 10-2 Å-1 (b). Estimated error of the power law slope is 3% of the average value. Time-resolved in-operando USAXS/SAXS measurements were collected as 1 atm of CO2 at 10 ml/min was continuously supplied to the SiO2-PAA nanofluids. On supplying CO2 for the first 6 minutes, no significant changes in the scattering intensity and morphology were observed. However, with the increasing exposure of CO2, the 122 scattering intensity in q-range smaller than 3 x 10-3 Å-1 started to increase, achieving a maximum value at 20 minutes. Increasing scattering intensity suggests enhanced aggregation of the polymer tethered nanoparticles at q-range smaller than 3 x 10-3 Å-1, driven by the absorption of CO2 in these nanofluids. Quantitative insights into the meso-scale aggregation of polymeric chains were obtained from the Modeling II tool in the Irena179 program embedded in the Igor software. The scattering curves and their respective fits are presented in Figure S5.4. The spherical form factor for SiO2 nanoparticles was used in the higher q region and the average size (radius) of the particles was found to be 24.4 nm. However, in the lower q regime, the unified fit model was used to obtain the power law slope from the scattering curves. The power law slopes are presented in Figures 5.8 (b). The power law slope of the phase changing nanofluids progressively increases from about 1.56 to 2.1 suggesting the transition from swollen polymeric coils around the nanoparticles to Gaussian coils like morphology 182 with exposure to CO2 over time. These observations are consistent with the volume expansion of the pure polymer, PAA in the presence of CO as reported by Jung and co-workers 3062 . Changes in the morphologies of these fluids were only noted after the first six minutes of performing these measurements. Entropic effects in the presence of the nanofluids correspond to the conformational changes in the nanofluids in the presence of CO2. Experiments performed at similar conditions with pure polymer, PAA did not show significant changes in the scattering intensity. These data together with the enhanced CO2 uptake in SiO2-PAA nanofluids compared to the pure polymer, PAA show that the nanofluids are morphologically more responsive to CO2 compared to the pure polymer, PAA. 123 5.4 CONCLUSIONS In this study, we explore the development of novel phase changing nanofluids constructed from SiO2 nanoparticles and poly(allylamine) (PAA) polymeric chains as the building blocks. In the presence of CO2, weak hydrogen bonds enhance the cross-linking of the polymer chains leading to the formation of hydrogels at lower temperatures compared to pure polymer, PAA. The enhancement in CO2 uptake in the phase changing nanofluids is 2.6 times that of pure PAA. The CO2 absorption mechanism in the PAA solution is initially controlled by the formation of protonated primary amine and bicarbonate species. In SiO2-PAA nanofluids however, the CO2 absorption mechanisms are mainly governed by the formation of carbamate ions along with protonated primary and secondary amines and bicarbonates. In-operando Ultra Small and Small Angle X- Ray Scattering (USAXS/SAXS) measurements of CO2 absorption in SiO2-PAA nanofluids showed the development of swollen branched polymers with increasing exposure to CO2. Under the same experimental conditions, significant changes in the scattering intensity of pure polymer, PAA were not noted. These studies establish the chemo-morphological basis for CO2 induced hydrogel formation in these novel phase- changing nanofluids. 124 5.5 SUPPLEMENTARY MATERIAL Figure 5.9 Figure S5.1 Clear 1000 ppm PAA solution in DI water (a) turns cloudy on adding 1 wt.% SiO2 nanoparticles (b). 125 Figure 5.10 Figure S5.2 ATR-FTIR spectra of starting PAA solution and 50 nm SiO2 nanoparticles suspension. 126 Figure 5.11 Figure S5.3 ATR-FTIR spectra of starting SiO2-PAA, SiO2-PAA-CO2, SiO2-PAA-CO2 nanofluids purged with N2 (SiO2-PAA-CO2-N2) and SiO2-PAA-CO2 diluted with excess water (left) and physical changes in nanofluids (right). N2 (99.99%) was purged at 1 atm for 30 minutes. 127 Figure 5.12 Figure S5.4 USAXS/SAXS curves and the fitted models of SiO2-PAA nanofluids exposed to CO2 as a function of time. 128 6 STRUCTURE AND SHAPE OF SURFACE-MEDIATED ASSEMBLY OF SURFACTANTS The contents of this chapter have been published as a journal article: H. Asgar, S. Mohammed, S. Seifert, and G. Gadikota, Energy & Fuels, 2021, 35 (24), 20206-20215 6.1 INTRODUCTION The ability of amphiphilic molecules, also known as surfactants, to tune surface tension of fluids has been crucial for stabilizing foams of CO2 bubbles dispersed in water at elevated temperature and pressure, which enables effective utilization of pore space for geologic storage of CO 319–3222. Further, surfactant chemistries can be tuned for developing pharmaceutical therapies to enhance lung capacity and respiration,323–326 delivering medicines that have low solubility in water,327,328 advanced separations for water purification, and the synthesis of novel materials with tunable porous architectures for catalysis, gas separations, and storage.109,199,329–332 These wide-ranging applications are attributed to the structures of surfactants, which are formed due to the aggregation or assembly of their molecules. A surfactant molecule has a bulk hydrophilic head, which is sometimes charged, and a relatively short hydrophobic tail.69 These surfactants tend to self-assemble into a range of hierarchically ordered nanoscale morphologies in response to a variety of environmental variables. The shapes and morphologies of the self- assembled micelles are susceptible to the size of the hydrophilic headgroup62,66,333, the charge on the surfactant62, temperature59,60,64, pH60,65, concentrations of the surfactants in the solution66–68, the length of the hydrophobic tails66,334,335, and the presence of additives61–63,69–71 among other factors. These factors influence the organization of micelles into spherical, ellipsoidal, or cylindrical shapes that consequently determine the extent to which these micelles can be utilized for the application of interest. 129 Amphiphilic molecules are broadly categorized as cationic, anionic, or amphoteric if the head carries a positive charge, negative charge, or two oppositely charged groups, respectively. Anionic and cationic surfactants are of interest because the charge on their hydrophilic ends enables their use in removing fine particles and as disinfectants, respectively. These attributes have enabled the extensive industrial and household use of these surfactants as foam-generating fluids. Despite significant advancements in the use of the materials for wide-ranging applications, there is a limited understanding of the influence of solid interfaces on the organization, shape, and size of micelles formed from cationic surfactants. Latest advancements in operando X-ray scattering measurements109,335,336 now enable us to evaluate the hypothesis that the chemical and energetic interactions of surfactants with the solid surface influence the mesoscale organization of micelles. In this study, we investigate the organization of cetyltrimethylammonium bromide (CTAB), which is one of the most widely studied cationic surfactants.69,337 Moreover, cationic surfactants such as CTAB, are effective reagents for enhanced oil recovery338–340. CTAB can be used to recover oil from silica-based reservoirs via wettability alteration.341 In this process, CTAB is preferentially adsorbed on the rock surfaces341,342, resulting in a reduction of interfacial tension between oil and rock. Therefore, in applications related to energy recovery and effectively utilizing subsurface environments, understanding the organization of surfactants and different surfactant systems is of interest. In an aqueous solution, core-shell type micelles having ellipsoid shape are usually 130 formed by CTAB molecules, where the hydrophilic head groups form the core and condensed counterions form an electron-dense shell around the core.332,337 For CTAB molecules, two different critical micellar concentrations in water, CMC1 (0.9 mM) and CMC2 (300 mM), exist at 25 °C. 343 It is reported that at CMC2, anisotropic micellar growth is usually noted.343 Various approaches have been investigated to tune the morphologies of surfactants. The addition of salts such as sodium salicylate,62 sodium bromide,63,344 sodium nitrate, and sodium chlorate345 has shown to change the globular micelles of CTAB to worm-like micelles. Block copolymers are also widely studied as non-ionic surfactants, where the amphiphilic molecules in the micelles are used as structure directors to develop hierarchical structures.201,213 Pluronic triblock copolymers consisting of polypropylene (PP) block sandwiched between two polyethylene (PE) blocks are examples of amphiphilic molecules.216,217 When added in an aqueous solution, these Pluronic triblock copolymers form micelles with a hydrophobic core of polypropylene (PP) block and a hydrophilic shell or corona around it, which is made up of polyethylene (PE) block.217–220 The organization of micelles has been investigated using various approaches, including electron microscopy65,346–349 and small-angle scattering.62,69,222,337,343,346,347,350– 358 Transmission electron microscopy (TEM) has been used to resolve the shapes, diameters ranging from 4-15 nm, and length scales ranging over several micrometers in colloidal systems.346,347 While TEM provides direct imaging of micellar shapes,346,348,349 the samples need to be frozen for imaging. The non-invasive characterization of the morphology and dimensions of the micelle aggregates is possible using Small-Angle X- ray Scattering (SAXS) or Small-Angle Neutron Scattering (SANS) as a function of the 131 temperature359–362, pH360, and chemical environments.343,352,355,362,363 The combination of real and reciprocal space imaging using SAXS and SANS analyses and the use of mathematical models can be used to delineate the structure and organization of micelles.355,359,363 Advancements in operando and fast X-ray scattering measurements, particularly Grazing Incidence – Small Angle X-Ray Scattering (GI-SAXS) and Transmission Small Angle X-Ray Scattering (Transmission SAXS), now allow us to address critical knowledge gaps underlying surface-mediated organization of micelles.109 We aim to harness the experimental data to validate molecular-scale models - an approach that has not been explored in the context of probing the assembly of micelles. Molecular dynamics (MD) simulations have shown that a mixture of cationic/anionic surfactants on quartz surface forms spherical-like micelles near the quartz surface while very few molecules adsorb directly on the surface. 364 The findings of this simulation were supported by linking the formation of the micelles on the quartz surfaces to the experimental contact angles and the adsorption behavior of surfactants on the quartz surface. Duan and co-workers365 showed that the atomic structure of surfactants has a considerable effect on the formation of micelles at quartz surfaces. In this context, introducing a secondary amine group in the dodecylamine (DDA) structure increases the adsorption of the surfactants on the quartz surface, which is driven by enhanced electrostatic interactions and hydrogen bonding interactions. Wang and co-workers366 showed that a mixture of dodecylamine and oleate formed a micelle structure on a muscovite surface with the atomic structure of these surfactants determining the micelle size and shape. Despite these advances, the molecular scale basis underlying the sizes and shapes of micelles at solid interfaces remained unresolved. To address this challenge, the 132 following research questions are addressed: (i) How does the organization of micelles differ at solid interfaces and in bulk fluids? (ii) What is the effect of adding non-ionic surfactant (P123) to cationic (CTAB) surfactant on the organization of micelles? (iii) What are the energetic interactions that contribute to the organization of micelles at quartz surfaces and in bulk fluids? To address these research questions, we aim to unlock and contrast insights underlying the organization of micelles at quartz surfaces and in bulk fluids using GI-SAXS, Transmission SAXS measurements, and molecular dynamics simulations. 6.2 MATERIALS AND METHODS The reagents used in this study are Pluronic® P123 (EG27PG61EG27), cetyltrimethylammonium bromide (CTAB), ethanol, and ammonium hydroxide (NH4OH). The reagents were used in the molar ratios indicated below: 367: For CTAB based system, ethanol : H2O : NH4OH : CTAB = 20 : 45.6 : 10.4 : 0.15 For CTAB + P123 mixture, ethanol : H2O : NH4OH : CTAB : P123 = 20 : 45.6 :10.4 : 0.15 : 0.15 Small Angle X-ray Scattering (SAXS) measurements, in both grazing incidence and transmission modes, were performed in a microreactor cell, shown in Figure 6.1. During the measurements, the micelles assembly at the top of the quartz substrate and in the bulk solution was investigated. The cell has a total volume of 6 mL, and the material compositions were adjusted accordingly. The GI-SAXS measurements were performed at sector 12 ID-C at the Advanced Photon Source in Argonne National Laboratory. The 133 scattered intensity during the measurements was collected on a 2-D Pilatus 2 M detector (Dectris Ltd., Baden, Switzerland). The instrument was operated at an X-ray energy of 18 keV, corresponding to the X-ray wavelength of 0.68 Å. The SAXS data were acquired in the q range of 0.006 – 0.74 Å-1, with an acquisition time of 1 second for each scan. The sample-to-detector distance during the measurements was 206 cm, which was calibrated using silver behenate [67]. The X-ray beam was directed to the substrate at an incidence angle (αi) of 0.11°, which is lower than the critical angle for total external reflection at the given energy. The GI-SAXS data was cut along the horizontal 433 axis (Yoneda Wing), and 1D curves were obtained using GISAXSshop, an Igor (Wavemetrics) based program. Figure 6.1 Schematic representation of a surfactant molecule and self-assembled core- shell micelle (a) and X-ray scattering experimental setup (b). The scattering from the empty cell was also acquired and subtracted as background from the data. Analyses of 1D SAXS data were performed using SASview v5.0.3. The models used to fit the X-ray scattering data are explained in detail in Supplementary Material (section S1), and the schematics of micelle shapes corresponding 134 to the fitted form factors are presented in Figure 6.2. The schematic representations of a surfactant molecule and self-assembled core-shell micelle and the experimental setup are shown in Figure 6.1. Figure 6.2 Schematic representation of models used for modeling the X-ray scattering data. A cut through at the equatorial axis (a), and a cross-section through the rotational axis (b) for prolate core-shell ellipsoid model and core-shell cylindrical model (c). Molecular dynamics (MD) simulations were performed to understand the atomic scale organization of CTAB surfactants and the mixture of CTAB + P123 surfactants. A series of classical molecular dynamics (MD) simulations are performed on CTAB solutions and a mixture of CTAB and P123 solutions in a bulk solvent and on a quartz surface. The molecular structures of CTAB, P123, H2O, and NH4OH are constructed and optimized using Avogadro software. The snapshots of initial configurations of solvent 135 and surfactants in bulk and on quartz surfaces are shown in Figure S6.1. The quartz surface unit cell was optimized using a DFT algorithm implemented in quantum espresso software (see Figure S6.2 and S6.3), and the optimized unit cell was replicated in x, y, and z directions; for detailed information on the optimization algorithm, see Mohammed and co-workers.368 The ratio of EG: PG groups in the P123 structure is chosen to be 1:1 such that reasonable MD simulations can be performed to capture the self-assembly and adsorption phenomena. The constructed polymers are solvated with water and NH4OH, with final polymer concentrations and solvent compositions matching the solutions used in the scattering measurements (see Figure 6.1). The x, y, and z dimensions of the initial configurations of bulk solutions and solutions on quartz surfaces are 8.200 nm × 8.200 nm × 8.200 nm and 6.874 nm × 6.874 nm × 12.000 nm, respectively, and these configurations are periodic in x, y, and z directions. CTAB, P123, and NH4OH were modeled using the OPLS/AA forcefield369, while water molecules were modeled using SPC/E parameters.370 Quartz surface parameters are taken from the CLAYFF forcefield.371 The force fields parameters used in this study are summarized in Table S6.1 in the supplementary material. These forcefields have been used extensively to probe the interfacial properties of hydrocarbons and surfactants on a variety of solid surfaces, including silicious surfaces and pores, and validated against experimental characterizations 342,372–375. Further, qualitative comparisons have been made between the simulations and the experiments throughout this work and qualitative agreements in the aggregation behavior indicate the validity and compatibility of the used forcefields. The energy minimization step is performed on the initial configurations for 50,000 steps using the steepest descent method to optimize the atomic positions of the molecules 136 in the simulation cells and avoid inappropriate geometries. A constant number of molecules, volume, and temperature (NVT) ensemble were performed on the optimized cells for 50 ns. The temperature is kept at 298 K using a Nose-Hoover thermostat376,377 with a temperature coupling time of 1 ps. The potential energy of each system accounts for bonded and nonbonded interactions. Bonded interactions include bond stretching, angle bending, and dihedrals, while nonbonded interactions considered include Lennard- Jones and Columbic interactions. MD simulations are performed using GROMACS 2018 software.378 6.3 RESULTS AND DISCUSSION 6.3.1 Organization of Micelles in Bulk Fluids and at Quartz Interfaces The structure of the aggregated micelles was determined experimentally using X- ray scattering measurements. These findings were contrasted with predictions from MD simulations. The X-ray scattering curves, 2D GI-SAXS patterns, and snapshots from MD simulations for micelles in the bulk phase and on the surface are presented in Figures 6.3, 6.4, 6.5, and 6.6, respectively. The scattering intensity, I(q), is determined by the product of form factor P(q) and structure factor S(q)62,350 (section S6.1). In the case of inter-micellar or intra-micellar interactions, the contributions from the form factor and the structure factor give rise to a correlation peak, which is related to the mean inter- micellar distances d 62,343,353im. A double peak that corresponds to the core-shell organization of matter343 is noted in the scattering curves for CTAB (Figure 6.3). 137 Figure 6.3 Organization of CTAB molecules in (a) the bulk fluids and (b) in fluids interacting with quartz surfaces using Small-Angle X-ray Scattering (SAXS) and Grazing-Incidence Small-Angle X-Ray Scattering (GI-SAXS), respectively. The scattering from CTAB micelles (Figure 6.3 (a-1)) presents the typical core- shell ellipsoid in the bulk fluid.62,337,343 In an aqueous solution, the hydrophobic tails of CTAB form the core of micelles, while the hydrophilic heads organize as the shell. A similar scattering profile is exhibited by CTAB surfactants on the quartz surface (Figure 6.3 (b-1)). The power-law slope ~1.3 in the low q-region (< 0.02 Å-1) for CTAB could indicate the formation of elongated ellipsoid features in the presence of the surface. In CTAB + P123 mixtures, these elongated ellipsoid features noted from the experimental data can be represented as core-shell structures. The structure factor, S(q), is used to determine the correlation peak, qcorr. qcorr is directly related to the mean inter-micellar distance, dim of the micelles in solution through the following relationship: dim = 2π/q .343,356corr In addition to the core-shell dimensions, the shape was determined. The shape is denoted by (Core)x and (Polar shell)x. In ellipsoid micelles, an oblate core is 138 evident if (Core)x < 1, whereas prolate and spherical cores are evident when (Core)x > 1 and (Core)x = 1, respectively. 350,354 The parameters representing the size and shape of the aggregated micelles are presented in Table 6.1. Figure 6.4 Organization of mixture of CTAB + P123 molecules in (a) the bulk fluids and (b) in fluids interacting with quartz surfaces using Small-Angle X-ray Scattering (SAXS) and Grazing-Incidence Small-Angle X-Ray Scattering (GI-SAXS), respectively. The core radius for CTAB in the bulk fluid is 16.0 Å, while on the quartz surface, the core radius is 14.2 Å. The corresponding shell thickness is 11.26 Å in the bulk fluids and 17.54 Å at the quartz surface. The densification of the micellar core in the presence of quartz surface can be attributed to the minimization of free energy, which promotes the agglomeration of more surfactant chains to form the micelles.251 Further, an increase in (Core)x and a decrease in (Polar shell)x from 2.71 to 3.57 and 2.64 to 0.37, respectively, are noted in the presence of the quartz surface. These findings indicate an elongation of micelles in the presence of the quartz surface. The emergence of the power-law slope of 1.3 in the low q (< 0.02 Å-1) region in the presence of the quartz surface corresponds to 139 the scattering from these elongated faces of micelles. Table 6.1 Parameters extracted from SAXS and GI-SAXS modeling of data. Cylindrical Core- Ellipsoid Core-Shell Model Shell Model CTAB CTAB on CTAB + CTAB + P123 on Parameters in Quartz P123 in Bulk Quartz Bulk Form Factor (P(q)) Core Radius (Å) 15.97 14.17 14.61 10.04 (Core)x 2.71 3.57 2.48 -- Shell Thickness 11.26 17.54 12.93 24.97 (Å) (Polar shell)x 2.64 0.37 2.55 -- SLD core (Å-2) 21.93 10.17 2.00 47.52 SLD shell (Å-2) 27.20 28.31 30.07 25.01 SLD solvent (Å-2) 26.04 26.04 25.17 26.14 Length (Å) -- -- -- 486.27 Structure Factor (S(q)) Effective Radius 41.14 39.75 40.30 110.11 (Å) dim (Å) (2 × effective 82.28 79.50 80.60 220.22 radius) Volume fraction 0.12 0.18 0.15 0.005 Further, we investigated the influence of non-ionic surfactant, P123 on the shape and the size of the micelles. Significant differences are noted in the scattering behavior of bulk fluids and fluids in the presence of a quartz interface are noted in CTAB + P123 mixtures. Core-shell ellipsoid structures are noted in bulk solutions while core-shell cylindrical micelles are evident in the presence of the quartz surface. The core radius 140 decreased from 14.61 Å to 10.04 Å, and the shell thickness almost doubled from 12.93 Å to 24.98 Å in the presence of the surface. The inter-micellar distances (dim) for CTAB + P123 in the bulk fluid is 40.3 Å, which is significantly different from the inter-micellar distances (dim) for CTAB in the bulk fluid and on the quartz surface (82.3 Å and 79.5 Å respectively) (Table 6.1). The greater proximity of micelles in the presence of P123 is attributed to lowered Gibbs free energy in the mixture of charged (CTAB) and non-ionic (P123) surfactants.379 Figure 6.5 Representative GISAXS patterns for CTAB + P123 (a) in bulk and (b) on Quartz surface. The dotted white line indicates the portion of Yoneda Wing, along which the horizontal cut is made to obtain the 1D curves. Further, the insights about the aggregation behavior, particularly, the orientation of micelles growth are obtained from the 2D GI-SAXS patterns of CTAB with and without P123 on quartz surface (Figure 6.5). In the case of CTAB on quartz surface (Figure 6.5 (a)), a diffuse ring pattern is noted around the scattered beam and beam stop, which indicates that the CTAB micelles grow on the surface without any preferred orientation for aggregation253. However, for CTAB + P123 (Figure 6.5 (b)), the diffuse scattering is accompanied by the densification of the ring. This indicates that the mixture 141 of CTAB + P123 has a random orientation with some micelles aggregating parallel to the surface 253. Figure 6.6 The self-assembly of CTAB (a-1), the mixture of CTAB and P123 (b-1) in bulk fluid, and CTAB (a-2), the mixture of CTAB and P123 (b-2) in fluids interacting with the quartz surface. The snapshots are taken during the last 1 ns of the simulation time. CTAB and P123 molecules are shown in CPK drawing method impplemented in VMD software. The presence of a quartz interface resulted in a cylindrical organization of micelles as opposed to an ellipsoidal organization. The densification of cores is also noted by the change in the power-law slopes in the higher q-region (> 0.1 Å-1). The increase in the power-law slope from 1.7 to 2.7 for CTAB and from 1.7 to 2.4 for CTAB + P123 mixture in the presence of the quartz interface is attributed to scattering from the micellar core. The increase in the power-law slope can also be associated with the densification of 142 the core in the presence of quartz surface. The shapes and sizes of the organization of micelles are summarized in Figures 6.7 (a-d). It can be noted that the ellipsoid CTAB micelles elongate (on quartz surface) along the rotational axis without P123 and along the length of the cylinder in the presence of P123. Figure 6.7 Schematic representation of the organization of CTAB micelles in (a) the bulk fluid and (b) the fluids in contact with the quartz surface. Figures (c) and (d) represent CTAB + P123 micelles in the (c) bulk fluid and (d) the fluids in contact with the quartz surface. These structures are inferred from X-ray scattering data. Insight into the cylindrical organization of micelles at the quartz interface is obtained from the S(q) contributions of different micelles in Figure S6.6. The S(q) almost approaches 1 as shown in Figure S6.6, indicating that the repulsions in the micelle shells are minimized in the presence of a surface, giving rise to cylindrical micelles.62,343 The structure factor contributions indicate repulsion between the micelles,62 originating from the counterions in the micellar shells. This observation is attributed to the penetration of P123 chains in the shell, assisted by the surface, which causes the rearrangement of the shell constituents. Further, the micellular repulsion interactions result in an inter-micellar distance of 22 nm in CTAB + P123, which is higher than all the other cases investigated in this study. 143 To delineate the effect of surface interactions on the number of micelles in the aggregates (Nagg) formed, equation 7.1 222 is used and the data is reported in Table 6.2. 4 𝜋 𝑅3 𝑁 𝐻𝑆𝑎𝑔𝑔 = ( )𝐶/𝜑 (6.1) 3 In equation 1, RHS and φ are the effective radius and volume fraction, respectively, determined from structure factor correlation, C = (c×NA/1000), c is the molar concentration of micelles, and NA is Avogadro's number. The number of micelles in the aggregates, Nagg is 220 for CTAB in the bulk fluid and 132 for CTAB in the presence of a quartz surface, which is attributed to the higher content of surfactant molecules in the bulk phase. In the case of the mixture of CTAB + P123, Nagg noted in bulk solution is 330, which is higher than Nagg for CTAB alone in bulk and on the surface. Based on this observation, it can be inferred that the presence of P123 chains assists the aggregation of micelles. However, for CTAB + P123 on quartz, a significantly higher Nagg of 202 × 10 3 is noted. This can be associated with the significantly lowered free energy for the organization of micelles in the presence of the surface251 and the mixture of charged and non-ionic surfactants.379 To delineate the energetic basis for these experimental observations and probe the influence of the quartz interface on the time scales and sizes of the micelle aggregates, classical molecular dynamics (MD) simulations are performed. The results are discussed in the following section. 144 Table 6.2 Calculation of Number of Aggregates (Nagg) from structure factor (S(q)) parameters. Sample ID RHS (Å) φ c (mol/cm3) Nagg CTAB in Bulk 41.14 0.12 0.15 220 CTAB on Quartz 39.75 0.18 0.15 132 CTAB + P123 in Bulk 40.30 0.15 0.30 330 CTAB + P123 on Quartz 110.11 0.005 0.30 202 × 103 6.3.2 Energetics and Aggregation Behavior of Micelles MD simulations show that the Lennard-Jones (L-J) interactions between CTAB molecules are attractive while the electrostatic interactions are repulsive. Electrostatic interactions are relatively unchanged over the simulation time in the bulk solvent and on quartz surfaces (Figure 6.8), but the magnitude of L-J interactions increases as a function of the simulation time due to the aggregation of CTAB and P123 that enhance the intermolecular collisions between the involved molecules. In the absence of P123 molecules (Figure 6.8 (a)), the Lennard-Jones interactions are more favorable on the quartz surface compared to the bulk fluid. This trend is reversed in the presence of P123 molecules (Figure 6.8 (b)), where the L-J interactions are substantially higher in the bulk fluid compared to in the presence of the quartz surface. These observations are consistent with the significantly smaller volume fraction contribution (0.0005) of S(q) in CTAB + P123 mixtures on the quartz surface, compared to the higher contribution (0.18) from CTAB on quartz. The volume fractions represent the contribution of S(q) i.e., the ordered micelles in the systems. In general, the form factor is mostly affected by the change in contrast due to the penetration of P123 chains 145 in the shell, while the structure factor disappears upon this surface-assisted interaction. Figure 6.8 The electrostatic and Lennard-Jones intermolecular interactions of CTAB- CTAB in the bulk fluids and the fluids in contact with the quartz surface in the absence and presence of P123 molecules. Insights into the assembly of micelles in the presence of CTAB and P123 molecules are further obtained from the average cluster sizes and associated times scales from MD simulations (Figure 7.9). The average cluster size of CTAB and P123 (Nn) is calculated as follows:  i.Ni N = i (6.2) n Ni i In equation 6.2, Ni is the number of clusters containing i molecules. The 146 summation starts at i = 2 and does not account for monomers.380 Significant differences in the assembly of CTAB and P123 molecules were noted. In the absence of P123, CTAB molecules formed larger aggregates in the presence of quartz surface compared to the bulk solvents and in shorter times. The size of the CTAB-bearing aggregate in the bulk solvent is half of that in the presence of the quartz surface. Similar trends are observed in the presence of P123 molecules in bulk fluids and on quartz surfaces such that the size of the CTAB and P123 aggregates are larger on quartz surfaces. CTAB and P123 molecules aggregated together in the presence and absence of the quartz surface to form an aggregate composed of all the simulated CTAB and P123 molecules (Figure 6.9). The trends in aggregation behavior observed in simulations are in agreement with the experimental data (see Table 6.2). Figure 6.9 The aggregation number of CTAB and P123 in the bulk fluids and the fluids in contact with the quartz surface as a function of the simulation time. 147 The higher aggregation numbers of CTAB and P123 molecules in the presence of the quartz surfaces are driven by the adsorption of the solvent components, particularly water, on the quartz surface (Figure 6.10). This adsorption behavior changes the solvent compositions and reduces the solvent density in the regions further away from the silica- solvent interface. The change in the solvent compositions and the lower density in the bulk region results in stronger intermolecular interactions between CTAB and P123 molecules. Interestingly, CTAB and P123 molecules aggregated away from the quartz- solvent interface, and no CTAB or P123 adsorption was observed on the quartz surfaces. Figure 6.10 Density profiles of fluidic components in solutions bearing (a) CTAB alone and (b) CTAB and P123 molecules as a function of the distance from the quartz surface. 148 6.4 CONCLUSIONS Differences in the assembly of micelles formed from CTAB and CTAB + P123 in bulk fluidic environments and the presence of a quartz surface are probed using GI-SAXS, SAXS, and classical MD simulations. CTAB molecules form ellipsoid core- shell micelles in bulk fluids and the presence of quartz surfaces. The addition of P123 molecules causes the micelles to elongate, and, in the presence of quartz, assemble into cylindrical core-shell morphologies. Faster aggregation of micelles and larger aggregates are noted for both CTAB and CTAB + P123 systems in the presence of the quartz substrate. CTAB molecules in the absence of P123 aggregated in a random orientation on the quartz surface, however, in the presence of P123, the micelles aggregated randomly and somewhat parallel to the quartz surface. While CTAB and P123 molecules were not adsorbed on the quartz surface, the adsorption of solvents on the quartz surface contributed to local changes in the density. The preferential adsorption of water on the quartz surface alters the compositions of the bulk solvent. The change of the solvent compositions influences the intermolecular interactions between the surfactants molecules that consequently affect the assembly of micelles. These studies provide the mechanistic basis for tuning the shapes and sizes of micelles for specific applications. These studies demonstrate that the organization of fluids at solid interfaces influences the assembly of micelles. These findings inform emerging strategies to tune fluid interactions in subsurface geologic environments for applications related to geologic carbon storage and CO2 utilization as a working fluid for subsurface energy applications. 149 6.5 SUPPLEMENTARY MATERIAL Figure 6.11 Figure S6.1 Snapshots show the initial configurations of (a) CTAB in bulk solvent, (b) CTAB and solvent on quartz surface, (c) CTAB + P123 in bulk solvent and (d) CTAB + P123 and solvent on quartz surface. CTAB, P123 and quartz atoms are shown using VDW drawing method the solvent atoms are showen in Licorice drawing method implemented in VMD software. 150 Figure 6.12 Figure S6.2 Total energy convergence of the quartz unit cell as a function of the cutoff energy (top) and K-points mesh (bottom). A cutoff energy of 420 eV and a K-point mesh of 6×6×6 have been used to oprimize the quartz unit cell. 151 Figure 6.13 Figure S6.3 The total energy profile governed from DFT energy optimization. The total energy is converged in 14 steps. The insets show the initial configuration and the optimized configurations of the quartz unit cell. 152 Table 6.3 Table S6.1 The forcefield parameters used to model the quartz surface, and water molecules. Atom σ (nm) ε (kJ/mol) Charge (q) Silica Si 0.37061(0.3022) 7.700 x 10-6 12 + 2.100012 O 0.35531(0.3162) 0.650212 - 1.050012 Water O 0.3553 0.6498 - 0.8476 H 0 0 + 0.4238 1 The parameters for Lennard-Jones equation in Cygan et al. (ref. 73). 2The parameters implemented in GROMACS code. 153 6.5.1 Section S6.1. Details about the X-ray Scattering Modeling The total intensity (I(q)) of small-angle X-ray scattering (SAXS) is interpreted by using equation (S7.1). I (q) = P(q) × S(q) + background (S6.1) where P(q) is the form factor related to the shape of the micelles, S(q) is the structure factor due to interaction between the micelles,337,351 and background is the background level. The calculation of P(q) for core-shell ellipsoid and core-shell cylindrical particles is discussed below. 6.5.1.1 S6.1.1. Ellipsoid Core-Shell Model The form factor (P(q)) for ellipsoid core-shell micelles is given by equation (S6.2). scale P(q, α) = F2(q, α) + Background (S6.2) V where, F(q, α) = 𝑓(𝑞, 𝑅𝑒 , 𝑅𝑒 × 𝐶𝑜𝑟𝑒𝑥, 𝛼) + 𝑓(𝑞, 𝑅𝑒 + 𝑡𝑠ℎ𝑒𝑙𝑙, 𝑅𝑒 × 𝐶𝑜𝑟𝑒𝑥 + 𝑡𝑠ℎ𝑒𝑙𝑙 × 𝑆ℎ𝑒𝑙𝑙 𝑥, 𝛼) (S6.3) 3∆𝜌𝑉 (sin[𝑞𝑟(𝑅𝑝,𝑅𝑒,𝛼)]−cos[𝑞𝑟(𝑅𝑝,𝑅𝑒,𝛼)]) 𝑓(𝑞, 𝑅𝑒 , 𝑅𝑝, 𝛼) = 3 (S6.4) [𝑞𝑟(𝑅𝑝,𝑅𝑒,𝛼)] 𝑟(𝑅 2 2𝑒 , 𝑅𝑝, 𝛼) = [𝑅𝑒𝑠𝑖𝑛 𝛼 + 𝑅 2 𝑝𝑐𝑜𝑠 2𝛼]1/2 (S6.5) 𝑉 = (4⁄3)𝜋 𝑅 2 𝑝𝑅𝑒 (S6.6) where α is the angle between the axis of the ellipsoid and wavevector q, V is the volume of micelles, Rp is the polar radius along the rotational axis, Re is the equatorial radius perpendicular to the rotational axis, tshell is the thickness of the shell at the equator, and Δρ is the scattering length density difference, either (ρcore – ρshell) or (ρshell – ρsolvent). For 154 an ellipsoid micelle, (Core)x < 1 represent oblate core, (Core)x > 1 show prolate core and (Core)x = 1 indicate the presence of spherical core. 350,354 Figure S6.4 exhibits a typical prolate core-shell ellipsoid micelle. Figure 6.14 Figure S6.4 Schematic representation of the core-shell ellipsoid model with a cut through at the equatorial axis (a), and a cross-section through the rotational axis (b). 6.5.1.2 S6.1.2. Cylindrical Core-Shell Form Factor The form factor for cylindrical core-shell systems is based on the model given by Kline.381 In the model, the form factor (P (q, α)) is normalized using the micelle volume and is given by equation (6.7). scale I(q, α) = F2(q, α) × sin (α) (S6.7) V𝑠 where, 1 sin (𝑞 2 𝐿 𝑐𝑜𝑠𝛼) 2 𝐽1(𝑞 𝑅 𝑠𝑖𝑛𝛼)F(q, α) = (𝜌𝑐 − 𝜌𝑠)𝑉𝑐 + 1 𝑞 2 𝐿 𝑐𝑜𝑠𝛼 𝑞 𝑅 𝑠𝑖𝑛𝛼 1 sin (𝑞 ( 𝐿+𝑇)𝑐𝑜𝑠𝛼) 2 2 𝐽1(𝑞 (𝑅+𝑇) 𝑠𝑖𝑛𝛼) (𝜌𝑠 − 𝜌𝑠𝑜𝑙𝑣)𝑉𝑐 1 (S6.8) 𝑞 ( 𝐿+𝑇) 𝑐𝑜𝑠𝛼 𝑞 (𝑅+𝑇) 𝑠𝑖𝑛𝛼 2 155 𝑉 2𝑠 = 𝜋 (𝑅 + 𝑇) (𝐿 + 2𝑇) (S6.9) where α is the angle between the axis of the cylinder and wavevector q, Vs is the total volume of micelles (i.e. including both the core and the outer shell), Vc is the volume of the core, L is the length of the cylindrical core, R is the radius of the core, T is the thickness of the shell, ρc is the scattering length density of the core, ρs is the scattering length density of the shell, and ρsolv is the scattering length density of the solvent. The outer radius of the shell is given by R+T and the total length of the outer shell is given by L+2T. J1 is the first-order Bessel function. A typical core-shell cylindrical micelle is presented in Figure S6.5. Figure 6.15 Figure S6.5 Schematic representation of the core-shell cylindrical model. 156 Figure 6.16 Figure S6.6 Structure factor (S(q)) contributions calculated based on the volume fraction and effective radius of hard spheres during data modeling. 157 7 DISSOLUTION AND REPRECIPITATION OF AMORPHOUS SILICA IN SILICA RICH SHALES INDUCES NON-MONOTONIC EVOLUTION OF POROSITY IN ACIDIC REACTIVE ENVIRONMENTS The contents of this chapter are currently under review in a journal as: H. Asgar, S. Mohammed, A. Socianu, J. Kaszuba, P. D. Shevchenko, and G. Gadikota, in ACS Earth and Space Chemistry 7.1 INTRODUCTION The dual needs to sustainably meet our growing energy and resource demand and limit detrimental impacts on climate and the environment motivate advances in transformative subsurface energy technologies including CO2 storage in unconventional reservoirs.1,72–75 As with engineered carbon storage via carbon mineralization,1,72,76,106,234,382–389 it is essential to consider the feedback effects of reactivity on the mineralogical and morphological changes of the underlying substrates. Unanticipated changes in the pore morphology and permeability impact long-term projections of fluid storage (e.g., CO2) in these environments. While CO2 storage in siliceous environments (e.g., sandstone with permeability in the range of 0.01 to 100 mD) has been extensively investigated,390–394 there is a limited scientific understanding of the fate and transport of CO2 in nanoporous shales with permeability in the range of 0.1 µD – 0.009 mD.394,395 Furthermore, in supercritical CO2-rich and water lean environments, this fluid mixture is known to act as a super acid and rapidly dissolve basic minerals.396,397 This highly reactive behavior has significant implications for the stability of shale as a stable overburden impermeable layer that prevents the migration of CO2 to the surface. 398 Alternatively, there is interest in storing CO2 directly in shales in which case the influence of highly acidic environments 158 such as those created by wet supercritical CO2 need to be resolved. 399 With more than 60% of current oil and gas production coming from shales (e.g., unconventional hydrocarbon reservoirs),400 these depleted reservoirs offer tremendous potential for subsurface CO2 storage. 76–79 Furthermore, the recovery of useful metals such as vanadium from shales typically requires acid-based leaching.401–403 The key scientific uncertainty underlying these diverse applications is the mineralogical and morphological transformation of shales in acidic environments. Shales comprise siliceous phases such as silica (predominantly as quartz), carbonaceous phases such as calcite, and clay-bearing phases such as illite. Calcite and clays readily dissolve in acidic solutions, while silica dissolution occurs at elevated pH environments. The mineralogy and morphology resulting from acid-induced dissolution influence subsequent fluid access, transport, and reactivity into these environments. While it is expected that the varying mineralogies of shales influence their reactivity with acidic solutions,83,84 the resulting morphological changes as a function of the composition of shales (especially with respect to silica content) remain unresolved. Furthermore, the influence of the mobilization of fine particles resulting from the acid-induced treatment of shales on the resulting porosity of shales needs to be resolved. Prior insights into the influence of acidic solutions on the mineralogies and morphologies of shales are important to evaluate in this context. Hydraulic fracturing is normally used to access oil and gas buried deep in these shales.80 However, for shales around the depth of 3,000 m – 4,000 m, the hydraulic fracturing approach can result in safety issues due to the high breakdown pressures required at such depths. To circumvent this challenge of requiring high pressures, acid fracturing (acidizing) is sometimes 159 applied as an alternative or pre-step to alter the properties of reservoir rocks and increase the permeability of the reservoirs.81–84 Acidizing dissolves various mineralogical phases in shales and creates flow channels to assist with the flow of hydrocarbons. Acidizing is known to enhance the conductivity of natural microfractures83,404 by dissolving the carbonate content. However, the influence of acids on the underlying siliceous structure remains unresolved. Prior studies investigating the influence of acids on the solubility of various magnesium silicate structures showed that dehydroxylated siliceous structures are more soluble compared to highly crystalline phases.405 The bonding between Si and O in silicate species is determined using the number of non-bridging oxygens (NBO). The number of bridging oxygens per Si tetrahedron is represented by Qn (n = 0, 1, 2, 3, 4) 406, where Q4 corresponds to 0 NBO in SiO2 species, Q 3 corresponds to 1 NBO in [Si 2-2O5] , Q2 corresponds to 2 NBO in [SiO ]2-3 , Q 1 corresponds to 3 NBO in [Si2O 6- 0 7] , and Q represents 4 NBOs in [SiO4] 4- related species. Detailed insights into the different silicate species, corresponding NBOs, and wavenumber ranges (cm-1) are presented in Table S7.1 and shown (schematically) in Figure 7.1 (a). In this study, Attenuated Total Reflectance – Fourier Transform Infrared Spectroscopy (ATR-FTIR) measurements are used to investigate changes in silica coordination network due to acid leaching. The bands noted between 850 – 1050 cm-1 in ATR-FTIR spectra correspond to Q1 – Q3, indicating the presence of crystalline species, while Q4 (1051-1250 cm-1) features indicate the presence of amorphous silica. To date, there have been no studies linking the changes in the silica coordination of shales treated in acidic environments to the changes in the pore volume and temporal evolution of the porosity. Therefore, this study aims to link the changes in the siliceous matrix of shales with varying mineralogies to the nanoscale and 160 micron-scale porosity of the reacted materials. Shale reservoirs typically consist of varying degrees of clay contents. Clays are aluminosilicate minerals, generally categorized in swelling (non-smectic) and non- swelling (smectic) clays, having 1:1 and 2:1 ratio of octahedral alumina and tetrahedral silica sheets, respectively.84,407,408 In shales deposits, illite, kaolinite and montmorillonite could be present.84 The presence of clay phases can also affect the reactions in reservoirs when exposed to acids and the type of precipitates formed. Further, the dissolution kinetics of clays are different for pure clay and clays mixed with other minerals. In the presence of carbonates, the clay minerals show a relatively different trend as opposed to pure clays.409 In the presence of carbonates, illite and kaolinite remained unaffected when reacted with HCl having concentrations up to 10 M, while dissolution of montmorillonite has been noted due to exchange of cations with protons leading to the formation of amorphous silica.409 Shale reservoirs typically consist of varying degrees of clay contents. Clays are aluminosilicate minerals, generally categorized in swelling (non-smectic) and non- swelling (smectic) clays, having 1:1 and 2:1 ratio of octahedral alumina and tetrahedral silica sheets, respectively.84,407,408 In shales deposits, illite, kaolinite and montmorillonite could be present [ref]. The presence of clay phases can also affect the reactions in reservoirs when exposed to acids and the type of precipitates formed. The dissolution kinetics of clays are different for pure clay and clays mixed with other minerals. In the presence of carbonates, the clay minerals show a relatively different trend as opposed to pure clays.409 In the presence of carbonates, illite and kaolinite remained unaffected when reacted with HCl having concentrations up to 10 M, while dissolution of montmorillonite 161 has been noted due to exchange of cations with protons leading to the formation of amorphous silica. In this study, we investigate the changes in the mineralogy and morphology of silica rich – carbonate/clay lean shale (Mowry), silica, carbonate & clay bearing shale (Frontier), and silica lean – carbonate/clay rich shale (Niobrara) reacted in 1 M hydrochloric (HCl) acid solution. While there is extensive evidence supporting increases in the pore volume of shales resulting from carbonate dissolution, the temporal evolution of porosity in silica-rich shales is due to changes in the crystalline and amorphous content of silica and relative solubilities is investigated. Thus, the specific research questions that are addressed through this effort are: (i) How does the relative content of amorphous and crystalline silica phases differ based on the relative silica, carbonate, and clay content in shales? (ii) What is the resulting change in the pore volume of shales due to reactivity in acidic environments? (iii) What is the temporal evolution of porosity in silica-rich shales? To address these questions, changes in silica co-ordination and the corresponding pore volumes are determined using ATR FTIR and BET pore size measurements. In-situ X- ray microtomography measurements are harnessed to probe the evolution of porosity in shales reacted in acidic environments. Addressing these research questions sheds fundamental insights into the mineralogical and morphological evolution of heterogeneous siliceous, carbonaceous, and clay-bearing rocks and minerals for emerging applications related to the recovery of high-value elements with inherent carbon storage. 7.2 MATERIALS AND METHODS Shale samples from three different formations which are the Mowry formation, Frontier formation, and Niobrara formation were used in the study. The shales 162 are extracted from depths ~10,000 ft (Mowry), and ~12,000 ft (Frontier & Niobrara), and ground to powders using 8000M Mixer/Mill® (SPEX® Sample Prep). These powdered samples are used in the study. Further details about the composition of shale samples are provided in Table 7.1. Based on the silica and carbonate contents of the shale samples, the samples are labeled as Silica Rich – Carbonate Lean (Mowry), Silica & Carbonate Bearing (Frontier), and Silica Lean – Carbonate Rich (Niobrara). The powder samples are reacted with 1 M HCl for 2 hours in a well-stirred environment. For reaction 1 g of powdered sample is reacted with 100 mL of 1 M HCl. All the experiments are performed at room temperature in a glass beaker. The changes in the chemical bonding of the shale powders after the reaction are evaluated using infrared (IR) spectra, acquired in an Attenuated Total Reflection (ATR) mode using a Fourier Transform Infrared - Attenuated Total Reflection spectrometer (FTIR-ATR, NicoletTM iS50, Waltham, MA). The spectra are collected in the range of 4000 – 650 cm-1, both before and after the reactions. For each spectrum, a total of 32 scans are acquired and averaged with a resolution of 2 cm-1. The changes in Q1 – Q4 coordination are evaluated by deconvoluting the IR spectra in the range of 850-1250 cm-1 to determine changes in the silica-based species upon reaction. The deconvolution is performed using the Levenberg Marquardt algorithm using the Gaussian model embedded in Origin Pro software (OriginLab Corp.). The details about the IR data modeling are provided in Section S7.1. The acid solutions after reaction with the powdered samples are analyzed using Inductively-Coupled Plasma – Atomic Emission Spectroscopy (ICP-AES) to determine the concentrations of leached species in the solution. As reference, 1 M HCl is also analyzed. 163 Table 7.1 Estimated chemical compositions of Frontier, Niobrara, and Mowry shale samples used in the study. Mowry Shale Frontier Shale Niobrara Shale Content (%) Silica Rich – Silica, Carbonate Silica Lean – Carbonate/Clay Lean & Clay Bearing Carbonate/Clay Rich Quartz 72.2 43 30 Carbonate 3.9 5 12 K-spar 0.5 4 4 Plagioclase 9.1 7 11 Clay 5.8 38 40 Pyrite 3.7 3 3 TOC 2.25 0.92 1.71 Changes in the phase compositions, and pore-solid morphology of shale samples on reaction with 1M HCl are determined using wide-angle X-ray scattering (WAXS), and ultra-small and small angle X-ray scattering (USAXS/SAXS) measurements, respectively, performed at Sector 9-ID-C of the Advanced Photon Source (APS), Argonne National Laboratory. The unreacted and reacted samples are sandwiched between a scotch tape and placed on the measurement plate for data acquisition. The scattering from the tape is also acquired and subtracted from the data as background. During the measurements, the X-ray energy is set to 21.0 keV (corresponding to the X- ray wavelength of 0.59 Å), having a total X-ray flux of ~1013 photon mm-2 s-1. The calibrations for instrument and sample-to-detector distance are performed using LaB 4106 for WAXS and silver behenate177 for SAXS. The 2D area detector data are reduced and processed to 1D I(q) v q (Å-1)) curves using an Igor software (Wavemetrics, Lake Oswego, OR) based Nika178 and Irena179 macros. The size distribution profiles of pores, 164 both open and closed, are estimated from combined USAXS-SAXS scattering curves using maximum entropy (MaxENT) method in Irena macro179. Further, details about the fractal dimensions at pore-solid interface are obtained by applying the Guinier-Porod approximation to combined USAXS/SAXS I(q) v q (Å-1) curves using Beucage’s approach181. The details about the used models and treatment of X-ray scattering data is reported in Section S7.2 (supplementary information). The variations in the mass of unreacted and reacted samples with temperature are recorded via thermogravimetric (TG) measurements, performed up to 850 ºC with a ramp rate of 5 ºC/min in an N2 environment (purged at 25 mL/min) using a Thermogravimetric Analyzer (TGA, TA Instruments, SDT650, New Castle, DE). The morphologies of reacted and unreacted shale powders are imaged using a scanning electron microscope (LEO 1550 FESEM). The results from TGA and scanning electron microscopy are discussed in detail in Section S7.3 (supplementary material). The nanoscale porosity and surface areas are examined using N2 adsorption-desorption isotherms at 77 K using the Brunauer−Emmett−Teller technique (BET, Quantachrome Autosorb iQ Analyzer, Boynton Beach, FL). Finally, the changes in reaction-induced porosity in the Silica Rich – Carbonate Lean (Mowry) shale sample are determined using the time-resolved in-situ X-ray microtomography measurements using the custom-reactor, similar to the one reported by Fusseis et al.411 A core sample with dimensions of 3 mm in diameter and 8 mm in height is drilled out of the rock shale sample and used for the tomography measurements. The schematic of the reactor and X-ray tomography setup is presented in Figure 7.1 (c). 165 Figure 7.1 Schematic of (a) different Qn coordination in silicate species, (b) evolution of nanoscale porosity upon interaction with 1M HCl, and (c) X-ray tomography setup used during the temporal evolution of microscale porosity during reaction with 1M HCl. The X-ray microtomography measurements are performed at the bending- magnet 2-BM-A beamline of Advanced Photon Source (APS) in Argonne National Laboratory (ANL). FLIR Oryx ORX-10G-51S5M camera with 2448 × 2448 pixels (pixel size 3.45 µm × 3.45 µm) is used in a fly scan mode and the projections are recorded while the sample is rotated between 0 – 180°. The data are collected on the detector region 2448×1024 because of the reduced size of the X-ray beam passing the monochromator adjusted for the energy of 27 keV. The camera recorded projections from a 100 µm-thick LuAG: Ce single-crystal scintillator, magnified through a 5× lens by yielding a resulting 166 isometric voxel size of 1.3 µm. The acquisition time for each image is 66 seconds. The core sample is fitted in a custom cell and 1 M HCl is purged through the core for 75 minutes. The flow rate of the solution during the experiments is set at 0.25 mL/min. A schematic of the experimental setup is shown in Figure 7.1. These measurements coupled with the IR spectroscopic measurements, electron microscopy, and nanoscale porosity data provide detailed insights into the feedback effects of carbonate dissolution on the silica speciation in the shale samples and changes in the porosity attributed to the fine particles’ mobilization upon reaction with hydrochloric acid. 7.3 RESULTS AND DISCUSSION 7.3.1 Chemical Evolution in Shale Samples The shale samples studied herein are extracted from deep wells and contain a variety of mineral phases. The compositions of these phases are reported in Table 7.1. The silica contents in Silica Rich – Carbonate/Clay Lean (Mowry) shale, Silica, Carbonate & Clay Bearing (Frontier) shale, and Silica Lean – Carbonate/Clay Rich (Niobrara) shale are 72.2 %, 43 %, and 30%, respectively. The quartz content reported in Table 7.1 contains amorphous and crystalline constituents. The carbonate contents in Silica Rich – Carbonate/Clay Lean (Mowry) shale, Silica, Carbonate & Clay Bearing (Frontier) shale, and Silica Lean – Carbonate/Clay Rich (Niobrara) shale are 3.9 %, 5 %, and 12%, respectively. The clay contents in Silica Rich – Carbonate/Clay Lean (Mowry) shale, Silica, Carbonate & Clay Bearing (Frontier) shale, and Silica Lean – Carbonate/Clay Rich (Niobrara) shale are 5.8%, 38%, and 40%, respectively. 167 Figure 7.2 Attenuated Total Reflection Infrared (ATR-IR) spectra for Silica Rich – Carbonate/Clay Lean (Mowry shale) (a), Silica, Carbonate & Clay Bearing (Frontier shale) (b), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) (c) samples before and after reaction with 1M HCl. Silica, Carbonate & Clay Bearing (Frontier) and Silica Lean – Carbonate/Clay Rich (Niobrara) shales have prominent carbonate bands around 712 cm-1, 875 cm-1, and 1450 cm-1 412 while Silica Rich – Carbonate/Clay Lean (Mowry) shales exhibit carbonate bands as shoulders (Figure 7.2). This observation is attributed to the higher silica content in the sample, which causes the Si-O bands to dominate the IR spectrum. The bands < 800 cm-1 correspond to Si-O-Si vibrations from silicates, which is typical from quartz.413 The vibrations between 850 – 1150 cm-1 are typically attributed to Si-O in SiO 2-4 from amorphous silica, and 1430 - 1460 cm-1 are identified as Si-O-Si vibrations,412 the detailed band assignment is presented in Table S7.3. After reaction with 1M HCl, the carbonate bands (CO 2-3 ) diminish (green curves in Figure 7.2) which is consistent with previously reported work.414 As mentioned, the Si-O bands between 850 – 1150 cm-1 are usually assigned as SiO 2-4 from amorphous silica. 168 Figure 7.3 Delineation of Q1-Q4 contributions from Silica using deconvoluted ATR-IR spectra for Silica Rich – Carbonate/Clay Lean (Mowry shale) (a-1, a-2), Silica, Carbonate & Clay Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) (c-1, c-2) unreacted and reacted with 1M HCl, respectively. Insights into the changes in the silica coordination behavior of shales before and after dissolution were determined from ATR FTIR analyses. For this purpose, the Si-O bands between 850 – 1250 cm-1 are deconvoluted to identify Q1 - Q4 contributions before and after reaction with 1 M HCl for the silicate species by determining the number of NBOs, as discussed earlier. The deconvoluted IR bands are presented in Figure 7.3. The reaction results in the dissolution of carbonate bands as indicated by the disappearance of carbonate bands between 873 – 881 cm-1 in all three samples. The bands noted between 850 – 1050 cm-1 in ATR-FTIR spectra correspond to Q1 – Q3, indicating the presence of crystalline species, while Q4 (1051-1250 cm-1) features indicate the presence of amorphous silica415 in different shale samples. The bands in the Q1 – Q3 region shift to 169 slightly higher wavenumbers after the reaction, which is an indication of the increase in Q3 type species upon dissolution of carbonate-rich phases in these samples. The contribution of Q1 – Q3 and Q4 units in ATR-FTIR deconvoluted spectra of Silica Rich – Carbonate/Clay Lean Figures 7.3 (a-1, a-2), Silica, Carbonate & Clay Bearing Figures 7.3 (b-1, b-2), and Silica Lean – Carbonate/Clay Rich Figures 7.3 (c-1, c-2) shale samples, before and after the reaction, are estimated by the band area estimations and presented in Figure 7.4. The bands centered at wavenumbers below 1050 cm-1 are labeled as Q1 – Q3 species, while bands centered at wavenumbers higher than 1050 cm-1 are characterized as Q4 species.406 For comparison, XRD patterns and IR spectra of model crystalline and amorphous silica are also presented in Figure S7.1. Quartz and Silica 60 are selected as model crystalline and amorphous silica, respectively, are selected. The deconvolution of IR spectra between 850 cm-1 and 1250 cm-1 shows that for crystalline silica (quartz) the major Si-O vibration band centers around 1050 cm-1 with the most deconvoluted bands appearing at wavenumbers less than 1050 cm-1, while in case of amorphous silica (silica 60), the Si-O vibrations bands appear at wavenumbers higher than 1050 cm-1. Analyses of the changes in silica coordination showed that there was less than 5% change in the Q1 – Q3 species corresponding to the crystalline content and Q4 content that is associated with amorphous content in Silica Rich – Carbonate/Clay Lean shale and Silica, Carbonate & Clay Bearing shale. In contrast, significant changes in the Q1 – Q3 species and Q4 content are noted in Silica Lean – Carbonate/Clay Rich shale. Q1-Q3 species increase by 34% from 61% in the unreacted to 95% in the reacted shale and a corresponding decrease in Q4 species is noted in reacted Silica Lean – Carbonate/Clay 170 Rich shale. These results show that the amorphous content corresponding to Q4 species dissolves preferentially compared to crystalline Q1-Q3 species in Silica Lean – Carbonate/Clay Rich shale. These unusual and significant changes in the silica content in Silica Lean – Carbonate/Clay Rich shale motivate us to investigate the basis for these observations. Figure 7.4 Contributions of Q1-Q3 and Q4 species in unreacted and reacted (1M HCl) Silica Rich – Carbonate/Clay Lean (Mowry shale), Silica, Carbonate & Clay Bearing (Frontier shale), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) samples from the estimated band areas. Several hypotheses are investigated to explain the significant increase in the amorphous silica content in silica-lean shales. The first hypothesis is that the increase in solution pH resulting from carbonate dissolution contributes to silica dissolution and 171 reprecipitation. In the presence of a reactive fluid (e.g., HCl), a non-equilibrium chemical state exists between the shale sample and the fluid, which can lead to several reactions, including, mineral dissolution and precipitation of secondary minerals.416 Highly acidic solutions dissolve calcium carbonate, neutralize the acid, and increase the solution pH.417– 419 This increase in the solution pH enhances the solubility of silica. The corresponding changes in the crystalline phases are determined using WAXS measurements. The WAXS patterns for unreacted and reacted shale samples are presented in Figure 7.5. The major phases identified are quartz,420 calcite,421 dolomite,422 clay,423,424, and pyrite.425 Upon reaction, the peaks of calcite around 2.07 Å-1 and 3.36 Å-1, corresponding to the (104) and (116) planes are diminished due to the dissolution of carbonate phases from all three samples. As expected, the higher peak intensity for calcite peak (~2.07 Å-1) is in the Silica Lean – Carbonate/Clay Rich (Niobrara) shale sample (Figure 7.5 (c-1)) compared to other samples. Moreover, the peaks of dolomite ~2.18 Å-1, corresponding to (104) plane, noted in all the unreacted samples also diminish after reaction with 1M HCl. Carbonate dissolution is known to increase the pore size of shales.426 The extent of carbonate dissolution during the reaction of the acid with shale is controlled by the quantity of carbonates in the shale. The carbonate mineral content of the shale formation therefore primarily determines the system’s pH and controls various pH-dependent reactions taking place in the shale reservoirs. In the case of the Silica Lean – Carbonate/Clay Rich shale sample, the higher carbonate content (12 %) could lead to a greater dissolution of minerals and subsequently increase the local pH of the system 427. pH increases enable silica dissolution and result in significantly smaller amounts of amorphous silica species (Q4) and higher content of crystalline silicate species (Q1 – Q3) 172 compared to Silica Rich – Carbonate\Clay Lean and Silica, Carbonate & Clay Bearing samples. Figure 7.5 Identification of different phases in Silica Rich – Carbonate Lean (Mowry shale) (a-1, a-2), Silica & Carbonate Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate Rich (Niobrara shale) (c-1, c-2) samples before and after reaction with 1M HCl, respectively, determined using the wide-angle X-ray scattering (WAXS) measurements. The second hypothesis is that chemical transformations involving clay-bearing phases contribute to silica dissolution and reprecipitation. For example, the substitution of Al3+ for Si4+ can shift Si-O- bands to relatively lower wavenumbers, which is noted in the case of Silica Lean – Carbonate/Clay Rich sample, where higher numbers of NBOs are noted. Moreover, the presence of Fe and Mg sulfates and Mg phyllosilicates in silicate minerals increases the release of SiO2 into aqueous solution, which eventually precipitates as silica or silica-rich minerals.428,429 The modeling of low-temperature alteration of silica-rich rocks using GEOCHEQ code430 has shown that the amorphous 173 silica forms in secondary accumulations in acidic pHs. Further, in the presence of sulfate- rich rocks (as in the case of Silica Rich – Carbonate/Clay Lean sample), silica can deposit at low pHs because of these weathering processes. Finally, the low solubility of silica phases in the solutions with acidic pH can result in the formation of silica-rich deposits in these reservoirs in contact with acidic solutions. Moreover, the clay-rich shales (Mancos) have shown a relative decrease in the quartz content before and after the treatment with acid treatment.83 The possible reactions in the studied samples can be identified based on the type of phases involved and their dissolution upon interaction with low pH acids (i.e., HCl).83,84,431 (a) Dissolution of carbonate phases CaCO + 2HCl → Ca2+3 (s) (aq) (aq) + 2Cl - (aq) + H2O (aq) + CO2 (g) (7.1) CaMg(CO ) + 4HCl → Ca2+3 2 (s) (aq) (aq) + Mg 2+ (aq) + 4Cl - (aq) + 2H2O (aq) + 2CO2 (g) (7.2) (b) Dissolution of pyrite phases FeS2 (s) + 2HCl 3+ (aq) → Fe (aq) + 2Cl - (aq) + H2S (g) (7.3) (c) Dissolution of clay-based phases Al4Si 3+ - 4O10(OH)8 (s) + 12HCl (aq) → 4Al (aq) + 12Cl (aq) + 10H2O (aq) + SiO2 (s) (7.4) Based on the reactions above, the increased contribution of SiO2 (Q 4 species) in Silica Rich – Carbonate/Clay Lean (Mowry) shale can be explained by the precipitation of SiO2 in the reacted sample on the existing silica surfaces. Furthermore, the dissolution of clay-based phases leads to the formation of SiO2 as shown in reaction 4. In our experiments, we note a monotonic increase in the crystalline silica content (Q1- Q3) with higher clay content (Figure 7.4). From these studies, we conclude that the higher clay 174 and carbonate content in these shales favor the formation of crystalline silica species, while higher amorphous silica content is noted in carbonate and clay lean samples. 7.3.2 Fate of Leached Species The concentrations of leached/dissolved elements for shale samples upon reaction with 1 M HCl are approximated using ICP measurements and presented in Figure 7.6 for major species and Figure S7.2 for minor phases. The analysis is also performed on 1 M HCl solution in the study, for comparison. Significantly higher concentration of leached Ca is noted in case of silica lean – carbonate/clay rich sample (620.81 mg/L) compared to other samples, i.e., 147.22 mg/L for silica, carbonate & clay bearing sample and 108.71 mg/L silica rich – carbonate/clay lean sample (Figure 7.6 (a)). For Mg, relatively higher leached concentration is exhibited by silica, carbonate & clay bearing sample (71.85 mg/L) compared to silica rich – carbonate/clay lean (18.17 mg/L), and silica lean – carbonate/clay rich (37.26 mg/L) samples (Figure 7.6 (b)). These results are consistent with the observations from WAXS results, where calcite is dominant phase in silica lean – carbonate/clay rich sample and dolomite peaks are dominant in silica, carbonate & clay bearing sample. The samples containing higher clay contents exhibit relatively higher leached Al content, 80.9 mg/L in silica, carbonate & clay bearing and in 50.77 mg/L silica lean – carbonate/clay rich, compared to 7.75 mg/L in silica rich – carbonate/clay lean sample (Figure 7.6 (c)). Similar trend is exhibited by Si, where a significantly higher amount is noted for silica, carbonate & clay bearing (45.64 mg/L), and silica lean – carbonate/clay rich (34.61 mg/L) samples, compared to 5.41 mg/L in silica rich – carbonate/clay lean sample (Figure 7.6 (d)). The higher amounts of leached Si in carbonate and clay rich samples also validate the hypothesis that a local increase in the 175 pH, upon dissolution of carbonate phases favors silica dissolution. Moreover, the significantly lower amount of leached Si in silica rich – carbonate/clay lean sample also indicate the reprecipitation of Si as amorphous silica as noted from increased Q4 vibrations in the reacted sample (Figure 7.4). Figure 7.6 Concentration of different leachates from shales samples upon reaction with 1M HCl (1 g powder per 100 mL solution) at room temperature for 2 hours. We also note that higher content of leached potassium from silica, carbonate & clay bearing (70.13 mg/L), and silica lean – carbonate/clay rich (54.73 mg/L) samples, which contain higher clay contents, compared to silica rich – carbonate/clay lean sample, where only 4.55 mg/L of leached K is noted (Figure 7.6 (e)). A similar trend is noted for Ba, where Ba can be present in the clay matrix or as a substituent for K+ in K- feldspars.432,433 Clay and pyrite minerals are the source of small quantities of Fe in the leached solutions (Figure 7.6 (f)).84 Finally, we also note relatively higher leached 176 amounts of S (15.35 mg/l) and P (28.60 mg/L) in silica rich – carbonate/clay lean sample indicating the dissolution of pyrite and K-spar phases in the sample, which also favors the precipitation of amorphous silica phases. Prior studies have shown that the injection of reactive (acidic) fluids can create nonuniform surface etching along the fracture surfaces in the shale samples434 and impact the porosity and permeability of reservoirs. The carbonate dissolution in these systems can also result in the release of fine particles (also called fines) of minerals such as K- spar,435 which can move within the reservoir and may cause pore blockage. The effect of carbonate dissolution on the nanoscale morphology of these shale samples upon reaction with 1 M HCl is determined using gas adsorption-desorption measurements as discussed in the following section. 7.3.3 Changes in Nanoscale Pore Morphology of Shales Detailed insights into the changes in the pore volumes and specific surface area are obtained from BET N2 adsorption-desorption isotherms. The isotherms, pore size distribution (PSD) curves, and cumulative pore volumes of unreacted and reacted shale samples are presented in Figure S7.4, and Figure 7.7, respectively. It was interesting to note that the cumulative pore volumes of the shales reacted in silica, carbonate and clay- bearing shales and silica lean, carbonate and clay-rich shale increases when reacted in acids unlike silica-rich shales (Figure 7.7). This can be attributed to the higher carbonate and clay contents in these samples, which results in higher dissolution of this mineral content upon reaction with 1M HCl. 177 Figure 7.7 Cumulative pore volumes and pore size distributions of Silica Rich – Carbonate/Clay Lean (Mowry shale) (a-1, a-2, a-3), Silica, Carbonate & Clay Bearing (Frontier shale) (b-1, b-2, b-3), and Silica Lean – Carbonate/Clay Rich (Niobrara shale) (c-1, c-2, c-3) samples before and after reaction with 1M HCl, respectively, determined using Barrett-Joyner-Halenda (BJH) method applied on the desorption isotherm. The pore volume contributions arise from changes in the pores having sizes greater than 4 nm for silica rich – carbonate/clay lean shale sample (Figure 7.7 (a-1)), 178 where the pore volume in the size range of 4 – 60 nm is increased and that greater than 60 nm is slightly decreased. Based on this observation, it is inferred that the mineral components (carbonate/clay) reside in these pores (<60 nm) and their dissolution causes a small increase in the pore volumes in this range, while the precipitation of secondary phases occurs along the walls of relatively larger pores (> 60 nm). For silica, carbonate and clay bearing sample (Figure 7.7 (b-1)) and silica lean – carbonate/clay rich sample (Figure 7.7 (c-1)), the slight increase in the pore volumes after reaction is attributed to the dissolution of carbonate and clay-based phases. For example, the cumulative pore volume of silica rich – carbonate/clay lean shale decreases by 14.2%. However, for silica, carbonate and clay-bearing, and silica lean – carbonate/cay lean shales the cumulative pore volumes increase by 16.67 %, and 41.67%, respectively, compared to the unreacted shales. Furthermore, a significant increase in the surface area and rougher interfaces are noted on the dissolution and precipitation of silica species (Table 7.2). For example, the surface areas of silica-rich, silica, carbonate and clay-bearing, and silica-lean shales increased by 29.88 %, 30.17 %, and 64.21 %, respectively, compared to the unreacted shales. The relatively higher increase in the surface area and pore volume after reaction with 1 M HCl for Silica Lean – Carbonate/Clay Rich sample can be attributed to the higher carbonate (12%) and clay (40%) content compared to Silica, Carbonate & Clay Bearing sample (5% carbonate, 38% clay) and Silica Rich – Carbonate/Clay Lean (3.9% carbonate, 5.8% clay) sample. The decrease in the average pore size of Frontier and Niobrara shale samples is attributed to the dissolution of carbonate/clay-based phases. 179 Table 7.2 Specific surface areas, pore volumes, and pore sizes for unreacted and reacted shale samples were determined using the BJH method from N2 desorption isotherms. Specific Pore Volume Avg. Pore Samples Surface Area (cc/g) Size (nm) (m2/g) Silica Rich – Unreacted 6.76 0.021 4.10 Carbonate/Clay Lean (Mowry Reacted with 8.78 0.018 4.10 Shale) 1M HCl Unreacted 28.40 0.12 3.80 Silica, Carbonate & Clay Bearing Reacted with 36.97 0.14 3.73 (Frontier Shale) 1M HCl Silica Lean – Unreacted 24.25 0.12 3.80 Carbonate/Clay Reacted with Rich (Niobrara 0.17 3.74 Shale) 1M HCl 39.82 The gas adsorption measurements provide information about the open or available pores in the samples. Comprehensive insights into the closed and open pores of these materials are obtained using ultra-small and small angle X-ray scattering (USAXS/SAXS) measurements. The combined USAXS/SAXS curves and corresponding pore size distributions for samples before and after reaction with 1M HCl are presented in Figure 7.8. Data fit and models used for these analyses are reported in Section S7.1 (supplementary material). The interlayer spacings emerging from clay content in the sample are noted at higher q-values. For instance, the peaks ~ 0.75 Å-1, corresponding to the d-spacing of 8.4 Å, diminish after the reaction (see insets in Figures 7.8 (a-1), (b-1) and (c-1)). These observations indicate the collapse of interlayer spacing upon reaction, which could be caused by leaching of cations from the interlayers and eventual collapse, which also results in silica formation. Further, the pore volume distributions are evaluated by normalizing the volume distributions of each sample. This 180 approach can help estimate the relative abundance of pores within each sample. In case of Silica Rich – Carbonate/Clay Lean sample, the unreacted sample has relatively higher number of larger mesopores (10 – 30 nm) and these pores decrease in number after reaction with 1M HCl. Moreover, a small shift in the pore sizes is noted, which could indicate the precipitation of new phases along the pore walls. Figure 7.8 Combined USAXS/SAXS curves for (a-1) Silica Rich – Carbonate/Clay Lean, (b-1) Silica, Carbonate & Clay Bearing, and (c-1) Silica Lean – Carbonate/Clay Lean samples. The corresponding pore size distributions obtained from fitting the USAXS/SAXS curves are presented in panles (a-2), (b-2), and (c-2). For Silica, Carbonate & Clay Bearing sample, a significant decrease in the relatively large mesopores (10 – 20 nm) is noted, while the average mesopores size is increased slightly (~ 5 nm to ~8 nm) after the reaction. This observation can be attributed to the dissolution of carbonate phases in the sample residing in these pores and dissolution of the clay phases. Moreover, an increase in larger mesopores sizes is noted (> 25 nm). 181 In case of Silica Lean – Carbonate/Clay Rich sample, the relative abundance of smaller mesopores (~ 5 nm) remains consistent, while the pores with sizes ~ 20 nm are diminished and either become large (~ 25 nm) or decrease in size as can be noted by the increase in relative abundance of pores having sizes ~12 nm. Finally, the size of macropores increase slightly after the reaction for all samples. The relative abundance of macropores decreases slightly for Silica Rich – Carbonate/Clay Lean sample, while a prominent decrease is noted in case of Silica, Carbonate & Clay Bearing sample. However, for Silica Lean – Carbonate/Clay Rich sample, the relative abundance of macropores remains somewhat similar. The noted increase in relatively larger mesopores and macropores for samples containing higher carbonate and clay content after the reaction is consistent with the increase pore volumes and surface areas for these samples. Further, the fractal dimensions at the pore-solid interface are determined from the power-law exponent (P) using a unified fitting approach based on Beaucage’s method181 (details in Section S7.2). The fractal dimensions are evaluated in two population regions in our data: population 1 between 0.003 Å-1 and 0.3 Å-1, and population 2 at q-values < 0.003 Å-1. The P values for samples before and after the reaction lie between 3 and 4, indicating the presence of surface fractals (Ds), and Ds = 6 - P. The changes in Ds upon reaction are presented in Figure 7.9. For population 1, Ds value for all three samples is 2, which indicates scattering from a smooth pore-solid interface.182 After reaction with 1M HCl, Ds values increase to 2.42 and 2.47 for Silica Rich – Carbonate/Clay Lean and Silica, Carbonate & Clay Bearing samples, respectively. Only a small increase (Ds = 2.07) is noted for Silica Lean – Carbonate/Clay Rich sample. This increase in the value indicates a slight increase in the roughness at the pore-solid 182 interface. The scattering in this range (for population 1) is attributed to the features at interfaces of pores sized between 2.1 nm and 209.4 nm i.e., mesopores and macropores. Figure 7.9 Fractal dimensions of unreacted and reacted shale samples estimated from combined USAXS/SAXS data at two different length scales. Population 1 and population 2 represent the scattering from pore having dimensions 2 – 200 nm and larger than 200 nm, respectively. The increased roughness can be attributed to the dissolution of matter, and precipitation of new phases along pore walls. The observations of relatively higher increase in roughness at pore-solid interface for Silica Rich – Carbonate/Clay Lean and Silica, Carbonate & Clay Bearing samples compared to Silica Lean – Carbonate/Clay 183 Rich sample are consistent with the changes in pore size distributions obtained from X- ray scattering (Figure 7.8). Moreover, the fractals at low q-values (< 0.003 Å-1), which correspond to features larger than ~210 nm, show a slight increase in values, meaning that the pore-solid interfaces for larger pores became smoother after the reaction. The increase, although not significant across the samples, becomes more prominent with the decreasing silica and increasing carbonate/clay contents. Finally, to understand the changes in the microscale porosity during the reaction of Silica Rich – Carbonate/Clay Lean (Mowry) shale sample with 1M HCl, in- situ X-ray microtomography measurements are performed. These results are discussed in detail in the following section. 7.3.4 Evolution of Microscale Porosity via in-situ Microtomography The changes in microscale porosity of Silica Rich – Carbonate/Clay Lean (Mowry) shale core are determined using time-resolved X-ray microtomography measurements. These measurements are performed when 1 M HCl is in continuous contact with the solid sample at a constant fluid flow rate of 0.25 mL/min in a triaxial cell.436 The 2D stack images, collected on the detector, are reconstructed using Object Research System (ORS) Dragonfly software437 to obtain the 3D images of the core sample. The images of the Silica Rich – Carbonate Lean core sample at the start (0 minutes), after 25 minutes, 50 minutes, and 75 minutes of reaction time are processed and presented in Figure 7.10 (a). The porosity changes are determined by pixel analysis on the X-ray microtomography images. The voids (dark pixels), representing the total porosity, in the core sample, are labeled as microscale pores as shown in Figure 7.10 (a- 1). The changes in the porosity are determined by analyzing the changes in the pixel 184 percentage (%) of voids during the reaction. The evolution of flow channels is estimated by analyzing the connected voids (pixels). The large void bodies connected via 6 pixels and 26 pixels (available options in the software) are analyzed to estimate the changes in small and large flow channels, respectively, as shown in Figures 7.10 (a-2) and (a-3). The estimated changes in the total porosity, channels connected via 6 pixels and 26 pixels are presented in Figure 7.10 (b). Figure 7.10 X-ray microtomography images of core sample drilled out of (Silica Rich – Carbonate/Clay Lean) Mowry shale sample. The darker (black) spots (a-1) indicate the total porosity in the sample. Pore channels connected via 6 pixels (a-2), and 26 pixels (a- 3) are also presented. The diameter of the core presented is 2.64 mm and the pixel size is 1.3 µm. Porosity estimated from pixel (%) as a function of reaction time estimated from the X-ray tomography image analysis (b). The changes in the channel positions at 50 minutes and 75 minutes indicate that the local porosity evolves as the reaction proceeds, governed by the mobilization of precipitated particles. The highlighted regions in (a-2) indicate the changes in the flow channels originating from the movement of precipitated fine particles. Non-monotonic temporal evolution of the porosity of the reacted shales is noted. Dissolution of carbonate/clay-based phases in the shale sample causes the porosity to increase after the first 25 minutes. At 50 minutes and 75 minutes, sedimentation of 185 amorphous silica (SiO2) species as the reaction proceeds reduces the total porosity. Briefly, the total porosity increases from 6.7 % to 10.7 % after 25 minutes of reaction with 1M HCl. The percentage of channels connected via 6 pixels increases from 2.6 % to 6.8 %, while that for 26 connected pixels increases from 3.1 % to 8.2 %. However, after 50 minutes, a decrease in the porosity of the shale core is noted. The total porosity is decreased to 4.24 % and 4.02 % after a reaction time of 50 minutes and 75 minutes, respectively. Moreover, a decrease in the percentage of channels connected via 6 pixels and 26 pixels is also noted. The percentage of smaller channels (6 pixels) decreases to 0.95 % and 0.77 %, while the percentage of relatively large channels decreases to 1.33 % and 1.16 % after 50 minutes and 75 minutes of reaction time, respectively, (Figure 7.10 (a-2)). This evolution in porosity is attributed to the mobilization of precipitated fine particles and fines released due to carbonate dissolution435 under the applied flow rate (0.25 mL/min). These fine particles not only decrease the overall porosity of the core sample but can also move within the developed flow channels freely, which is noted by the differences in the channels (connected by the pixel size of 6) at 50 minutes and 75 minutes (Figure 7.10 (a-2)). These mobilized fine particles contribute to pore plugging in these reservoir rocks and may have a direct effect on the accessibility of these pore spaces for applications related to CO2 storage. Based on these observations, we propose the mechanism of phase dissolution, silica speciation/precipitation, and resulting rougher pore-solid interfaces in Figure 7.11. Initially, the dissolution of carbonate/clay phases increases the porosity in silica-rich shales. Over time, the precipitation of fine particles in acidic environments (which are typically silica particles) reduces the pore volume and enhances the surface roughness. 186 Amorphous silica is more labile and soluble compared to crystalline silica.438,439 Figure 7.11 Schematic representation of changes in the porosity of shale sample during reaction with 1M HCl. The carbonate/clay phases are present in the silica rich matrix (a), the porosity of sample increases upon dissolution of these phases within first 25 minutes of reaction (b), precipitation of silica-based species causes the porosity to decrease as the reaction proceeds (c), and increased roughness at the pore-solid/fracture-solid interface caused by the precipitation. 7.4 CONCLUSIONS Investigation of the feedbacks of mineralogical heterogeneity on the chemistry and morphology of shale samples in acidic environments shows that dissolution and reprecipitation of amorphous silica in silica-rich shales reduces the porosity of these materials. These studies show that highly acidic environments such as those created by wet supercritical CO2 can have vastly different impacts on shales based on differences in the mineralogy. The amorphous content of silica in silica-lean and 187 carbonate-rich shales is significantly reduced while the corresponding crystalline content is enhanced. The increase in amorphous silica content relative to crystalline content in silica-rich shales is attributed to the dissolution of clays and the resulting precipitation of amorphous silica particles and increases in solution pH resulting from carbonate dissolution which local silica dissolution, which then reprecipitate in a bulk acidic fluid. Pore volume and surface area are considerably higher in the reacted silica-lean and silica- bearing shales due to the abundance of reactive carbonate and clay phases. Non- monotonic evolution of the porosity in silica-rich shales is attributed to the initial dissolution and reprecipitation of particulate matter. Even though the conventional understanding is that silica is unreactive in acidic environments, our findings suggest that the dissolution and reprecipitation of siliceous matter influences the nano-scale and micron-scale morphology and the evolution of flow paths in these heterogeneous material systems. Incorporating these non-monotonic temporal effects underlying the morphological evolution of these heterogeneous systems is crucial for developing predictive controls over the fate of fluids in subsurface reservoirs with mineralogical heterogeneity for applications related to sustainable subsurface energy technologies. 188 7.5 SUPPLEMENTARY MATERIAL 7.5.1 Section S7.1. Details about ATR-FTIR data modeling The ATR-FTIR spectra of pure silica powders, both amorphous and crystalline, are also obtained and used as a baseline for the origin of bands in silica-bearing samples. The ATR-FTIR spectra of amorphous Silica 60 (procured from ABC), and crystalline quartz (XYZ) are presented in Figure S1. To confirm the crystallinity of powders, XRD patterns are also obtained for both Silica 60 and quartz (Figure S1 (a)). Figure 7.12 Figure S7.1. X-ray diffraction patterns (a), and infrared (IR) spectra (b) of crystalline (Quartz) and amorphous (Silica 60) samples. Deconvoluted IR spectra of quartz (c) and silica 60 (d) between the wavenumbers of 850 cm-1 and 1250 cm-1. The fitting of IR data is performed using a Gaussian function with a Levenberg Marquardt algorithm. −4 ln(2) (𝑥−𝑥 2𝑐) 𝐴 𝑒 𝑤2 𝑦 = 𝑦0 + (S7.1) 𝑤 𝜋 √4 ln (2) 189 Table 7.3 Table S7.1. Classification of different silicate units and corresponding non- bridging oxygens (NBOs).406 Non-Bridging Species Wavenumber (cm-1) Vibration Mode Oxygens (NBOs) 0 (Q4) SiO2 1250 – 1051 Asymmetric stretch 1 (Q3) [Si2O 2- 5] 1050 – 981 Symmetric stretch 2 (Q2) [SiO ]2-3 980 – 951 Symmetric stretch 3 (Q1) [Si2O ] 6- 7 950 – 901 Symmetric stretch 4 (Q0) [SiO ]4-4 900 – 850 Symmetric stretch 190 Figure 7.13 Figure S7.2. Concentration of leachates of minor species from shales samples upon reaction with 1M HCl (1 g powdered sample per 100 mL solution) at room temperature for 2 hours. 191 7.5.2 Section S2. Details about Models used to Process Combined Ultra-Small & Small Angle X-ray Scattering (USAXS/SAXS) Data The intensity (I(q)) of a typical X-ray scattering experiment is given by equation S7.2. 𝐼(𝑞) = | 𝑟 ∆𝜌2| ∑ 𝑚𝑎𝑥𝑟 |𝐹(𝑞, 𝑟)| 2 𝑉(𝑟) 𝑓(𝑟) 𝑑𝑟 (S7.2) 𝑚𝑖𝑛 In the equation above, Δρ2 is scattering contrast between the two phases of a sample (in our case, it is the contrast between shale matrix and pores), F(q,r) is scattering form factor, V(r) and f(r) are volume of sample and volume size distribution, respectively. f(r) is given by equation S7.3. 𝑓(𝑟) = 𝑉(𝑟) 𝑁 𝑃(𝑟) (S7.3) where N is the total number of scatterers and P(r) is the probability of finding a scatterer at distance r. The pore size distributions of samples are estimated by assigning pores as phase I (ρ1) and shale matrix as phase II (ρ2) and taking in account the X-ray scattering length densities (SLDs) of both phases. Shales consist of different components (Table 7.1), and to estimate the SLD of a shale sample, an average SLD (for the total solid matrix) can be calculated using equation S7.4.440 ∑𝑛𝑣𝑜𝑙% (𝑖) 𝑆𝐿𝐷(𝑖) 𝑆𝐿𝐷𝑆ℎ𝑎𝑙𝑒 = 𝑖 (S7.4) 100 where i is an individual component and n represents the total number of components in the sample. SLDs for the samples under study are calculated using the X-ray SLDs of individual components and their respective volume fractions. The densities and X-ray SLDs of components in our sample are reported in Table S7.2. The SLD of pores is set to zero since the physical density of air is approximately equal to zero in the pores.440,441 The pore size distributions, evaluated between the q-vector range between 0.0008 Å-1 and ~0.1 Å-1, from combined USAXS/SAXS curves are presented in Figure 7.8. Further, the 192 information about the fractal dimensions at the pore-shale interface is extracted using the Guinier-Porod approximation proposed by Beaucage’s approach.181 Briefly, the approach evaluates the scattering features in different regions by knee-like Guinier features and an associated power-law exponent in the Porod region. The Guinier feature explains the structure corresponding to a specific scattering regime, i, while the power-law exponent (P) describes the geometry of the related structure. The general expression of Beaucage’s approximation is given in equation (S7.5). 𝑃 𝑞 𝑅 3 𝑖𝑦 𝑞2𝑅2 (erf ( ⁄ )𝑔 𝐼 (𝑞) = ∑𝑖[ 𝐺𝑖 exp (− ) + 𝐵 ( √6 ) ] + 𝐵 (S7.5) 3 𝑖 𝑞 𝑔 In equation (S4), Gi represents the Guinier exponential prefactor and Bi is a constant prefactor. Rg and Pi correspond to the radius of gyration and power-law exponent of a specific structural regime, i, respectively. The values of P lie between 1 and 4. P values of 1, 2, and 4 represent the scattering from rigid rod-like features, plate-like features, and smooth interfaces, respectively. Moreover, P values between 3 and 4 correspond to scattering from features similar to surface fractals, whereas, P < 3 represents geometries similar to mass fractals at pore-solid interfaces.108,182,410 The mass (Dm) and surface (Ds) fractal dimensions can be obtained from P values using equations (S7.6) and (S7.7), respectively. 𝑃 = 𝐷𝑚 (S7.6) 𝑃 = 6 − 𝐷𝑠 (S7.7) In our data, two populations for unified fitting are identified, which are; population 1 between 0.003 Å-1 and 0.3 Å-1, and population 2 at q-values < 0.003 Å-1. The representative fitted curves for pore size distribution using ‘MaxENT’ method and unified 193 fit for Silica-Lean & Carbonate/Clay-Rich (Niobrara) sample are presented in Figure S7.3. In the population range 1, the Guinier (knee-like) feature is evident, followed by a power-law exponent at relatively higher q-values. However, in case of population 2, the Guinier (structure) feature is at very low q-values and doesn’t appear in the collected q- vector range and only a power-law exponent can be extracted. The estimated fractal dimensions for shale samples before and after reaction are presented in Figure 7.9. Table 7.4 Table S7.2. Densities and X-ray scattering length densities (SLDs) for different components present in the shale samples. Component Density (g/cm3) X-ray SLD (×1010 cm-2) Quartz 2.65 22.72 Calcite 2.71 23.23 Dolomite 2.86 24.46 K-spar 2.56 21.82 Plagioclase 2.61 22.22 Clay 2.7 23.12 Pyrite 5.01 40.76 TOC 1.40 12 Figure 7.14 Figure S7.3. Combined USAXS-SAXS curves and the fitted models during (a) pore size distribution fitting and (b) unified fitting to obtain fractal dimensions. 194 Figure 7.15 Figure S7.4. N2 adsorption-desorption isotherm for Silica Rich – Carbonate Lean (Mowry shale) (a-1, a-2), Silica & Carbonate Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate Rich (Niobrara shale) (c-1, c-2) samples before and after reaction with 1M HCl, respectively. 195 Table 7.5 Table S7.3. Bands in the IR spectra.412–414 Wavenumber (cm-1) Bonds 694 – 695 Si-O-Si in silicates typical of Quartz 712.43 Carbonate (CO 2-3 ) 777 – 778 Si-O-Si in silicates typical of Quartz 796 – 797 Si-O-Si in silicates typical of Quartz 873 – 881 Carbonate (CO 2-3 ) 850 – 1150 Si-O in SiO 2-4 (am) 1160 – 1165 Si-O-Si 1430 – 1460 Carbonate (CO 2-3 ) 196 7.5.3 Section S7.3 Weight Changes & Micron Scale Morphology in Unreacted and Reacted Shale Samples The changes in the weight % of shale samples after reaction with 1M HCl estimated using thermogravimetric analysis are presented in Figure S7.5. In the unreacted shale samples, the highest weight loss around 14.72% is noted for the Silica Rich – Carbonate Lean (Mowry) sample (Figure S7.5 (a)), while 6.35% and 11.46% weight loss are noted for Silica & Carbonate Bearing (Frontier) (Figure S7.5 (b)) and Silica Lean – Carbonate Rich (Niobrara) (Figure S7.5 (c)) samples, respectively. The major weight loss in Silica & Carbonate Bearing and Silica Lean – Carbonate Rich samples is corresponded to the decomposition of carbonates due to the release of carbon dioxide (CO2), pyrite, and clays. Silica Lean – Carbonate Rich sample has a higher content of clay (40%) and carbonates (12%) compared to Silica & Carbonate Bearing sample, where clay and carbonates contents are 38% and 5%, respectively. However, the highest weight loss noted in the unreacted Silica Rich – Carbonate Lean sample can be attributed to the higher moisture content (weight loss of ~5% around 100 °C) and total organic content (TOC) (2.25%). In the case of reacted samples, Silica & Carbonate Bearing (Frontier) and Silica Lean – Carbonate Rich (Niobrara) samples almost similar weight loss (~ 5%) is noted after the dissolution of carbonate species in the presence of 1M HCl. However, relatively higher weight loss (7.24%) is noted for the reacted Silica Rich – Carbonate Lean (Mowry) shale sample. The micron-scale morphology of unreacted and reacted shale samples was imaged using scanning electron microscope (SEM) and is presented in Figure S7.6. The observed morphology of unreacted Silica Rich – Carbonate Lean (Figure S7.6 (a-1)), Silica & Carbonate Bearing (Figure S7.6 (b-1)), and Silica Lean – Carbonate Rich (Figure S7.6 (c-1)) shales are consistent with the observations from prior 197 literature. However, for the reacted samples, no significant changes are noted. Figure 7.16 Figure S7.5. Thermogravimetric analysis (TGA) of Silica Rich – Carbonate Lean (Mowry shale) (a), Silica & Carbonate Bearing (Frontier shale) (b), and Silica Lean – Carbonate Rich (Niobrara shale) (c) samples before and after reaction with 1M HCl. 198 Figure 7.17 Figure S7.6. Scanning electron micrographs (SEMs) of Silica Rich – Carbonate Lean (Mowry shale) (a-1, a-2), Silica & Carbonate Bearing (Frontier shale) (b-1, b-2), and Silica Lean – Carbonate Rich (Niobrara shale) (c-1, c-2) samples before and after reaction with 1M HCl, respectively. 199 8 INTERFACIAL REACTIVITY AND SPECIATION EMERGING FROM Na- MONTMORILLONITE INTERACTIONS WITH WATER AND FORMIC ACID AT 200 °C: INSIGHTS FROM REACTIVE MOLECULAR DYNAMICS SIMULATIONS, INFRARED SPECTROSCOPY, AND X-RAY SCATTERING MEASUREMENTS The contents of this chapter have been published as a journal article: M.G. Muraleedharan, ǂ H. Asgar, ǂ S.H. Hahn, ǂ N. Dasgupta, G. Gadikota, and A.C.T. van Duin ACS Earth Space Chem, 2021, 5, 1006-1019 ǂEqual contribution 8.1 INTRODUCTION Advancing experimentally supported predictive insights into reactive phenomena at fluid-solid interfaces is essential for gaining scientific insights into the evolution of matter on planets. In this context, reactions involving montmorillonite clays in aqueous and formic acid environments is of particular interest. Montmorillonite clays are identified in different carbonaceous chondrites86,442,443 that are pieces of asteroids that remained unprocessed on earth since the formation of our solar system.87 These chondrites contain various forms of organic matter including aliphatic and aromatic hydrocarbons, carboxylic acids, and alcohols.87 Moreover, the organic materials were also deposited in the early earth at metamorphic conditions with the weathering products of intermediate and mafic rocks, which are primarily montmorillonite clays.85,86 Furthermore, formic acid is the simplest carboxylic acid and is often observed to be remaining or left over after the building of meteorites and comets.88 Additional organic materials could be buried in Earth’s subsurface through geologic and tectonic processes.86 In this context, the aim of this study is to probe the reaction mechanisms involved in the interactions of sodium montmorillonite with formic acid and water at an elevated temperature of 200 0C, especially how the hierarchical 2D nanoscale structure of Na- 200 montmorillonite89 and the intercalation of Na+ ions contribute to differences in the chemical interactions at the basal plane, edge or facet of Na-montmorillonite. Several complex and competing reactions occur as Na-montmorillonite reacts with aqueous formic acid environments.444–446 Na-montmorillonite undergo surface hydroxylation and proton generation reactions in aqueous environments, which further triggers a chain of other reactions, such as the formation of hydroxides.447–449 These reactions contribute to structural and morphological changes of clay solids.92–94 Chemical interactions between organic acids and water with montmorillonites can result in the formation of carbonate species that eventually neutralize the dissolved cations and precipitate within the interlayers.90,91 The formation of carbonates has been shown to change the interlayer spacing and the resulting swelling behavior in sodium montmorillonite.90,91 Despite these observations, significant knowledge gaps remain in the interactions of Na-montmorillonite with water and formic acid at elevated temperatures. Uncertainties regarding the intermediates that are formed leading to the observed phases, associated reaction energy barriers, and differences in the reactivity of the clay mineral facet, interlayers, and edge exist. To address these challenges, the following questions are addressed in this study: 1. What new phases and species are formed as Na-montmorillonite clay reacts with water and formic acid? How does reactivity influence the interlayer basal spacing of the clay structure? 2. What are the possible reaction pathways leading to the formation of observed phases? 3. How do the differences in the chemistry of the facet, interlayer, and edge of sodium montmorillonite influence reactivity? 201 To address these questions, computational models such as ReaxFF/MD and experimental approaches such as Fourier-Transform Infrared Spectroscopy (FT-IR) and X-ray scattering measurements are used to investigate reactivity and speciation when sodium montmorillonite reacts with formic acid and water. Although numerical simulation approaches such as Monte Carlo (MC) methods,450–452 Molecular Dynamics (MD),453–455 and Density Functional Theory (DFT)456,457 have been used to study the interfacial dynamics of fluids in clays, ReaxFF/MD methodology458,459 is uniquely suited to elucidate the interfacial chemical reaction mechanisms46 and to estimate early-stage kinetics94 in reactive fluid-solid systems. ReaxFF allows the user to set up an appropriate initial geometry and then harness the reaction-diffusion processes to drive the system towards local chemical equilibria. In contrast with a non-reactive MD simulation with non-reactive empirical potentials, where the system topology remains constant throughout the simulation, this feature of ReaxFF methodology makes it much more general. ReaxFF forcefields are trained against the dataset obtained from accurate electronic structural calculations such as density functional theory (DFT), which enables near-quantum mechanical accuracy, especially for reaction barriers and enthalpies, circumventing the high computational costs of ab-initio based methods. For these reasons, ReaxFF based MD simulations have been used to accurately simulate the dynamics of mineral/fluid interfacial chemistry in prior studies.46,93,94,460 In this study, we probe the reactive interactions of Na-montmorillonite with formic acid and water using a hybrid simulation and experimental approach. In this study, we probe the reactive interactions of Na-montmorillonite with formic acid and water using a hybrid simulation and experimental approach. In this study, we probe the reactive interactions of Na- 202 montmorillonite with formic acid and water using a hybrid simulation and experimental approach. We further analyze the system to delineate reactivity of different types of interfaces within the system that are challenging to probe experimentally, like the difference in reactivity of a mineral edge, facet, and the interlayer regions when exposed to the same fluidic environments. 8.2 MATERIALS AND METHODS 8.2.1 Experimental Methods and Materials Na-montmorillonite (SWy-3) clay was obtained from The Source Clays Repositories (Purdue University, West Lafayette, IN) and used as received. Formic acid with purity in the range of 98-100% (EMSURE® ACS, Reag. Ph Eur) was purchased from Millipore Sigma. To determine the reaction products, ~500 mg of clay powder was reacted with 100% water and 1:1 mixture of formic acid and water at 200 °C, 1 atm for 2 hours. The reactions were carried out in an acid digestion vessel (Parr Instrument Company). After the reactions, the powders were filtered to remove the liquids and air- dried at 90 °C for 48 hours. To evaluate changes in the chemical bonds as a result of reaction, the infrared (IR) spectra were acquired in an Attenuated Total Reflection (ATR) mode using an Attenuated Total Reflection-Fourier Transform Infrared spectrometer (ATR-FTIR, NicoletTM iS50, Waltham, MA). The spectrum of unreacted clay was also acquired as a control. The IR spectra were acquired in the range of 4000 – 500 cm-1 with the spectral resolution of 1 cm-1 and signal averaged over 32 scans. Additionally, to uncover the changes in various functional groups, spectra in specific range were also deconvoluted into Gaussian profiles using the OriginPro 2017 with the help of ‘Multiple Peak Fit’ analysis tool. The deconvolutions were performed in two different frequency 203 ranges of 3800-2650 cm-1, and 1800-1300 cm-1 since dominant changes to the spectra were observed in these regions. The R-squared (R2) values corresponding to the coefficient of determination (COD) for each deconvolution fit were also reported. The R2 value is the percentage of the response variable variation that explains the fitted regression line. A typical R2 value is always between 0 and 1. If the value is 0, it indicates that the fitted line does not explain any variability of the response data around its mean. However, if R2 is 1, it indicates that the fitted line explains all the variability of the response data around its mean. In our fits, we noted an R2 value of > 0.99 in all cases, which indicates a good fitness of fits and reliable agreement between the modeling fits and the experimental data. To determine the changes in the microstructure and structure, multi-scale Ultra- Small, Small and Wide-Angle X-ray Scattering (USAXS/SAXS/WAXS) measurements were performed at Sector 9-ID-C at Advanced Photon Source (APS) in Argonne National Laboratory (ANL). The instrument at 9-ID-C uses the original Bonse-Hart double-crystal setup.175,176 To obtain the scans, the powdered samples were sandwiched between a clear scotch tape and loaded on the acquisition plate. The scattering from the empty tape was also taken as background and subtracted from the data. The X-ray wavelength, energy and total flux during the measurements were 0.59 Å, 21.0 keV, and ~1013 photon mm-2 s−1, respectively. Calibrations for sample-to-detector distance and instrument were performed using silver behenate for SAXS177 and LaB6 for WAXS. USAXS, SAXS, and WAXS data were obtained by reducing the collected data using the Irena179 and Nika178 macros in the IgorPro software (Wavemetrics, Lake Oswego, OR). 204 8.2.2 ReaxFF/Reactive Molecular Dynamics Simulations ReaxFF is a bond-order dependent potential, wherein the total energy of the system consists of contributions from bond-order dependent terms and nonbonded interaction terms. The ReaxFF bond order is calculated based on the interatomic distances of all atom pairs in every time step. Energy contributions from bond-order dependent terms such as bond, valence angle, and torsion angle disappear upon bond dissociation, and only the nonbonded interactions such as van der Waals and Coulombic energies need to be considered thereafter. The connectivity between all atom pairs is calculated on-the- fly from the local atomic environment and updated every time step of the simulation. This feature allows ReaxFF to capture the chemical reaction process systematically. Atomic charges required to calculate the non-bonded interaction energies is a dynamic quantity and derived using the electronegativity equalization method (EEM).461 More details on the ReaxFF functional form and implementation can be found in previous work.452,462 To model atomic interactions in Na-montmorillonite, we started with the Na/Si/O/H ReaxFF parameterization from Hahn et al.463 and combined it with the Si/Al/O/H ReaxFF parameters which were previously reported by Pitman and van Duin460 for clay-zeolite composites. We then augmented the training set with the sodium carbonate (Na2CO3) and bicarbonate (NaHCO3) groups as well as the vibrational normal modes of carbonate ion to ensure accurate reproduction of the IR spectra (ref: Supplementary Material, Section 1). Although the Pitman and van Duin parameter set were extensively tested to study the structure of Ca-montmorillonite within the zeolite housing and cation/water diffusion under conditions of dynamic chemical equilibrium, a well-trained Na-related parameter set is critical for describing the hydration of the Na- 205 montmorillonite surfaces and the subsequent leaching processes. The Na/Si/O/H parameters used in this study were trained against a DFT-based training set which describes, sodium-water binding energies, hydration of sodium hydroxide with water and sodium ion interactions with silanol (Si-OH). All the given training dataset are relevant to the chemical dissolution of silica/silicate/silicalite surfaces in the presence of sodium cations and therefore, could provide a reliable description of sodium leaching dynamics, chemisorption and physisorption of water molecules at the Na-montmorillonite surface. Furthermore, the parameterization of the Pitman and van Duin model along with its extensions had been tested for different crystalline and amorphous structures.464–468 This has also captured the enhanced sodium ion diffusion behavior in water at elevated temperatures due to the disruption of hydrogen bonds of water in solvation shell.469,470 The Na/Si/Al/O/H parameter set employed herein are suitable for studying the structure and dynamics of sodium transport under varying temperature and solvation conditions. Na-montmorillonite is a dioctahedral phyllosilicate with a 2:1 arrangement of tetrahedral silicate and octahedral aluminum layers. The crystalline Na-montmorillonite structure used for the simulations consisted of 11200 atoms created using a unit cell with lattice parameters a = 5.22 Å, b = 9.02 Å, and c = 12.4 Å. This structure was first independently energy minimized with the (001) cleavage plane exposed to vacuum and leveraged the reactive forcefield for surface atomic rearrangements and optimization. Following this, the system is equilibrated at T = 298 K and P = 1 atm with periodic boundary conditions but leaving 2 Å of vacuum on either side of the free surface. The space between the TOT (tetrahedral-octahedral-tetrahedral) layers contains sodium cations (Na+). The overall structure of Na-montmorillonite has a negative charge which 206 is balanced by the positively charged intercalated Na+ ions. Single water and formic acid molecules were independently created and allowed to relax to the lowest energy configuration within the force field. We chose 13600 fluid molecules each for both water and formic acid and were randomly arranged around the Na-montmorillonite structure on all sides of the system until the desired density was achieved corresponding to the chosen temperature (T = 473 K) and pressure (P = 1 atm). Thereafter, the energy of the system was minimized and non-reactively equilibrated at target temperature and pressure, to form a system geometry (Figure 8.1), thereby exposing crystal facet, edge, and the interlayers to fluid molecules to create avenues for protonation and other surface reactions. We used ReaxFF integrated into the Amsterdam Density Functional (ADF)471 for reactive MD simulations. All simulations were run in the anisotropic isothermal-isobaric (NPT) ensemble with fixed x and y dimensions, using a weak Berendsen thermo/barostat with a temperature damping constant of 0.1 ps to keep the temperature constant. A time step size of 0.25 fs was used, and the equations of motion were integrated using the velocity-Verlet integration scheme.472 The system was run for 0.6 ns allowing for the generation of sufficient statistics. A total of three independent repetitions of the simulation starting from different initial geometries were performed; their mean values were obtained to ensure an unbiased statistical sampling of the MD trajectory. We also used ReaxFF/MD implementation in LAMMPS473,474 to generate the data necessary for computing IR spectra. For this, the system was run in NPT ensemble for a maximum of 20 ps. For the IR spectra calculation, the output in the form of the total dipole moment of the system was obtained every 0.5 fs, which was later post-processed to compute the IR 207 spectra.475 Figure 8.1 Snapshot of the simulated initial configuration of the molecular simulation showing Na-montmorillonite, water and formic acid molecules at 473 K and 1 bar. 8.3 RESULTS AND DISCUSSION 8.3.1 Speciation Behavior The first step is to benchmark the reactive forcefield by ensuring that the different species signatures observed in ATR-IR spectra are accurately predicted by the simulation. Figures 8.2 (a) and (b) represent the measured and computed IR spectra respectively. As can be seen from these figures, roughly, three frequency regimes can be identified characteristic of different types of vibrational modes: 3800-2650 cm-1, 1800-1300 cm-1, and 1300-500 cm-1. These regimes were also deconvoluted into Gaussian peaks to classify them based on representative species, as shown in Figures S8.10 and S8.11. 208 Figure 8.2 Comparison of (a) experimental and (b) computed IR spectra for unreacted Na-montmorillonite (Na-MM), Na-MM reacted in water, water and formic acid ratio of 1:1, and in formic acid with a purity of 98-100% at 200 °C and 1 atm for a reaction time of 2 hours. In Figure 8.2 (a), the IR peak around ~515 cm-1 is associated with the bending vibrations of Si-O-Al of pristine Na-montmorillonite crystal 476. Upon reacting with both the fluids, a slight shift to a higher wavenumber i.e. from 516.70 cm-1 (unreacted) to 516.74 cm-1 (after reactions), was also noted for the Si-O-Al linkages. Importantly, heights of these peaks were influenced by the chemistry of surrounding fluids: reactivity with H2O yielded the largest decrease in height followed by the 1:1 mixture of H2O and HCOOH and HCOOH. Computed IR peaks also showed similar characteristics for the Si-O-Al linkages. In Figure 8.2 (b), the computed IR peak corresponding to the bending vibrations of Si-O-Al linkages in unreacted Na-montmorillonite crystal is observed around ~430 cm-1. This peak decreases in height upon reaction with various fluids and also shifts marginally to higher wavenumber (~440 cm-1), similar to the experimental IR data. Note that there is ~86 cm-1 difference between the experimental and computed frequencies, because the forcefield was not directly fitted to the Si-O-Al vibrational frequencies. Additionally, computed IR peaks corresponding to pure HCOOH shows the 209 largest reduction in peak height contrary to the experiments, suggesting that the simulations have overpredicted the reactivity of HCOOH with Na-montmorillonite surface. To further investigate the physical reasons behind peak intensity shifts, we calculated the angle distribution of Si-O-Si (Figure S8.5 (a)) and Si-O-Al (Figure S8.5 (b)) before and after the reactions. It is evident from Figure S8.5 that there is a broadening of these angles after reaction, which could be attributed to the peak shifts to higher frequencies. This observation is further validated by prior studies reporting the broadening of angles due to the formation of surface silanol (Si-OH) groups.93,94 Corroborating evidences were also observed from the peaks associated with the hydroxyl groups, where it is interesting to note that no shifts were observed in the bending vibrations of hydroxyl groups ( OH) of Al-Al-OH (~914.7 cm-1) and tridymite (~796 cm-1) in Na- montmorillonite. This observation also directed our attention to investigate changes in silanol (Si-OH) groups. The IR bands around ~1115 cm-1 and ~1000 cm-1 which are typically attributed to the Si-O (out-of-plane) and Si-O (in-plane) stretching vibrations, respectively 476–478 were determined for Na-montmorillonite samples. However, a reduced intensity of IR spectra that corresponds to Si-O bonds when Na- montmorillonite is reacted in water is observed, which may be attributed to the bond dissociation of Si-O-Si followed by silanol formation. We also observed a shift from 982.81 to 1000.78 cm-1 for Si-O in-plane stretching vibrations as a result of the reactions. However, for the ReaxFF/MD case, the frequencies were slightly underpredicted (red- shift) for the Si-O (in-plane) case which is located at ~800 cm-1 whereas for the Si-O (out- of-plane) case, the predictions fall in place of ~1100 cm-1. Nonetheless the general trend of reduction in intensity post-reaction remained unchanged. 210 Furthermore, as seen in the deconvoluted peaks in Figures S8.10, in the unreacted clay, the prominent bending vibrations were observed at 1647.54 cm-1 and 1632.94 cm-1. These peaks correspond to -OH bending vibrations. In the reacted Na-montmorillonite, similar vibrations were observed but the peaks were slightly shifted. For example, in Na- montmorillonite reacted with water, the aforementioned peaks were observed at 1626.77, 1581.65, 1544.31, and 1366.57 cm-1, respectively. In addition to a slight shift in the peak positions, the peak around 1581.65 cm-1 became prominent and appeared as a shoulder peak. Similarly, peaks at lower wavenumbers (1544.31, and 1366.57 cm-1) also became prominent as compared with the ones observed in the unreacted clay. A small peak at 1720.34 cm-1 corresponding to O-H bending vibrations was also noted as a result of reaction. We also computed similar peaks that followed the same qualitative trends as shown in Figure 8.2 (b). Most importantly, we were able to capture the IR signatures of carbonate species with unprecedented levels of accuracy. In the deconvoluted IR spectra (Figure S8.10), we noted the emergence of a sharp peak at 1444.07 cm-1 that was associated with the bending vibration of C-O in carbonate ion (CO 2-3 ) formed as a result of different carbonation reactions 479,480. Simulated C-O bending peak for CO 2-3 was also observed at ~1450 cm-1 suggesting that the carbonate formation reactions may have been simulated accurately. Additionally, weak peaks ~3600-3800 cm-1 corresponding to the C-O stretching vibrations for CO 2-3 was observed in both experiments and simulations, further confirming the efficacy of the forcefield. Figure S8.10 also shows peaks corresponding to various other expected reaction products. In case of the sample reacted with H2O-HCOOH mixture, besides the peaks 211 appearing at 1715.09, 1633.28, 1580.20, 1544.81, 1374.58 cm-1 for OH bending vibrations and 1442.84 cm-1 for C-O due to carbonation of NaOH, we also observed peaks around 1715.09 cm-1 (sharp), and 1664.73 cm-1, which corresponded to the COO- vibrations in HCOONa. A peak attributed to the vibrations of C=O groups was observed at 1685.83 cm-1. Additionally, we also noted the vibrations from C-O group in carboxylic acid salts i.e., HCOONa in our case, at 1607.00 and 1392.96 cm-1 481–484. These peaks, however, are not quite apparent in the computed IR spectra, partly because the forcefield was not trained against these vibrational modes and partly because the concentration of these formed species was negligible to produce a characteristic signature. 8.3.2 Precipitation of Solids at the Interlayer Reactions between the (bi)carbonate species and dissolved Na+ cations result in the precipitation of Na2CO3 and NaHCO3 solids that can potentially deposit at the interlayer.485 As evident from the concentration profiles of the (bi)carbonate salts shown in Figure S8.15 and Figure S8.16, the propensity to form NaHCO3 and Na2CO3 is higher at the interlayer regime owing to the high concentration of Na+ and H2CO3. The mechanism of NaHCO3 and Na2CO3 precipitation as obtained from our MD simulations is shown in Figure 8.3. In this mechanism, dissolved Na+ ion attacks the oxygen of H2CO3, followed by the formation of intermediate species, Na--H2CO3 (Figure 8.3 (b)), which dissociates to produce NaHCO3 and proton, as shown in Figure 8.3 (c). To form Na2CO , Na + 3 ion attack the NaHCO3 Figure 8.3 (d) releasing a proton via Na +/H+ exchange reaction Figure 8.3 (e). 212 Figure 8.3 Mechanisms involved in the formation of sodium bicarbonate (NaHCO3) near the interlayer of Na-montmorillonite where (a) represents the interactions between Na+ ion and the oxygen of H2CO3, followed by the formation of intermediate species, Na-- H2CO3 as shown in (b). This intermediate species dissociates to produce NaHCO3 and proton, as shown in (c). (d) Na+ ion attacks the oxygen of OH group of NaHCO3 resulting in (e) Na2CO3 formation. One direct consequence of this precipitation is the change in the interlayer basal spacing. To determine if salt precipitation alters the interlayer spacing, we inspect the peak positions in X-ray scattering measurements. The changes in the interlayer basal spacing of Na-montmorillonite as a result of reactions was determined using SAXS measurements. The combined USAXS and SAXS curves for samples in the study are shown in the Figure 8.4, wherein the zoomed-in SAXS portion is shown in Figure 8.4 (b). Changes in the interlayer basal spacing of Na-montmorillonite were noted, depending on the reacting fluid. The interlayer basal spacing (d-spacing) for unreacted clay was noted to be 12.36 Å. Upon reaction with H2O, the interlayer spacing slightly increased to 213 14.01 Å. This value falls between the 1W and 2W hydration of Na-montmorillonite clays17, which could be attributed to the precipitation of different species between the interlayers. Further, a slight hump after reaction with H2O was also noted around q = 0.26 Å-1, corresponding to the basal spacing of 24.17 Å (d = 2π/q). Peaks for the same interlayer spacing (24.17 Å) were also noted in case of reaction with HCOOH and 1:1 mixture of H2O and HCOOH. This could be attributed to the precipitation of different species in the interlayer of swelling clays like Na-montmorillonite as reported previously.90,91,486 Moreover, for both HCOOH and 1:1 mixture of H2O and HCOOH, the original interlayer basal spacing of ~12 Å was also noted, which indicates that the original clay spacing has been largely preserved. Figure 8.4 Changes in the interlayer basal spacing of Na-montmorillonite after reacting with water, HCOOH, and, 1:1 mixture of HCOOH and water at 200 °C and 1 atm for 2 hours using Ultra-Small Angle Scattering/Small Angle X-Ray Scattering (USAXS/SAXS) measurements. Other species with the potential to swell clays are NaOH and HCOONa. As shown in Figure 8.7 and Figure S8.13, we observe an increasing concentration of NaOH and HCOONa molecules respectively, observed in MD simulations. In Figure 8.5, the WAXS intensities for Na-montmorillonite clay before and after reactions are shown. Some 214 additional peaks were also noted in the WAXS pattern after reaction with the fluids. After reaction with H2O, two prominent new peaks were noted around q = 2.99 and 3.48 Å -1, corresponding to the interplanar d-spacing of 2.10 and 1.81 Å, respectively. These peaks correspond to the (200) and (220) planes of cubic NaOH,487 which was formed during the reaction. Figure 8.5 Evidence of the formation of Na2CO3, NaOH, and HCOONa due to reaction of Na-montmorillonite with water, 1:1 mixture of water and formic acid, and formic acid (98-100%)) at 200 °C and 1 atm for a reaction time of 2 hours using Wide Angle X-Ray Scattering (WAXS) measurements. Na-montmorillonite reacted with pure HCOOH and H2O+HCOOH mixture resulted in the formation of Na2CO3 and HCOONa salts. These characteristic peaks noted at q = 1.67 and 1.81 Å-1, in Na-montmorillonite (1:1, H2O:HCOOH), correspond to (111) 215 and (111) planes of monoclinic Na 4882CO3 with the interplanar d-spacings of 3.74 and 3.44 Å, respectively. However, in case of acid (HCOOH) only, (201) and (111) planes of monoclinic NaOH were noted around 1.63 and 1.81 Å-1, corresponding to the interplanar d-spacings of 3.86 and 3.48 Å, respectively. Moreover, additional peaks were also noted in both cases with formic acid. In 1:1 mixture, the peak around q = 3.93 Å-1, having an interplanar d-spacing of 1.59 Å corresponds to the precipitation of HCOONa.489 Na- montmorillonite reacted in HCOOH resulted in two peaks around 1.74 and 3.98 Å-1 (and the corresponding interplanar d-spacings of 3.62 and 1.58 Å) which correspond to HCOONa.489 These experimental results confirm predictions from ReaxFF/MD simulations of the formation of carbonate and formate phases when Na-montmorillonite is reacted with HCOOH. In the following sections, we investigate the pathway of these reactions with the help of ReaxFF/MD simulation trajectory with emphasis on the differences in reactivity between Na-montmorillonite facets, edges, and interlayer regions. 8.3.3 Differences in the Reactivities of Facets, Edges, and Interlayers Three distinct reactive surfaces can be identified on the Na-montmorillonite structure in Figure 8.1: facets, edges, and the interlayers. Edge surfaces are assumed to have the same stoichiometry and structure as the bulk crystal, with slight bond-length relaxation to account for over- or under-coordinated surface O atoms.490 However, recent ab initio MD simulation results indicate that cations in the octahedral layer adopt a 5-fold coordination making it highly reactive.491 Interlayers are like facets but consist of Na+ counterions at the surface to balance the excess surface charge. They also have adsorbed water and formic acid near the surface that result in the formation of reactive surface 216 hydroxyl groups. The presence of excess charge, adsorbed molecules, and surface hydroxyl groups make the edge and interlayers relatively more reactive than the facets. In this section, we explore the various reaction mechanisms stemming from these reactivity differences. 8.3.3.1 Physisorption Properties of Na-montmorillonite Surface The first observed step in these mechanisms is the physisorption of the fluid molecules at the montmorillonite surfaces. Figure S8.4 shows the early-stage interactions (before 2.5 ps) at the interface of Na-montmorillonite-water/acid interfaces. These are non-reactive, physical adsorption events at time scales in the range of 0-2.5 ps, causing an increase in the density of adsorbed layer, setting stage for surface protonation events (see Figures S8.4 (a) and (b)). It is important to ensure that the forcefield accurately captures the adsorbed fluid layer at the montmorillonite surface. Physisorption is due to van der Waals and Coulombic forces between the dipoles of water and acid and the induced dipoles on the montmorillonite surface. Hence, a stable physiosorbed layer also confirms that the nonbonded interactions between the atoms of montmorillonite, water, and formic acid are modeled accurately by the forcefield. We obtained an adsorbed layer with a thickness of ~1-2 Å as shown in Figure S8.4, which is comparable with prior MD calculations94,492 and the energy of adsorption of ~1 kcal/mol, which is in line with the hydration energy reported elsewhere.493 To confirm that the adsorption energy is predicted accurately for the right physical reasons, we characterized the adsorption behavior of the fluid molecules. On the Si-terminated surface, we found that most of the water is adsorbed by hydrogen bonding to bridging oxygen (BO) of the surface Si-O-Si linkage. In the case of formic acid, however, the hydrogen bound to C tends to bind with 217 the bridging oxygen via hydrogen bonding. After complete physisorption, the reactions are turned on. The change in concentration of the adsorbed water and formic acid species due to chemical reactions, as a function of time in the edge, interlayer, and facet regimes from t = 0 (fully physisorbed state) to t = 0.6 ns (end of simulation) for different fluid environments are shown in Figure S8.6. Note that these three regimes are defined by considering a cleavage plane at a perpendicular distance of 0.5 nm from the surfaces on either side. The edge and interlayer regions have adsorbed the highest concentration of fluid molecules, which may be ascribed to the presence of Na+ ions resulting in a positively charged surface that attracts the oxygen groups. This is further corroborated by the fact that water being a polar molecule is in a more physisorbed state than formic acid. 8.3.3.2 Formation and Utilization of Hydroxyl Groups The dissociation of the adsorbed water or formic acid molecules over time and the associated decrease in the concentrations of these molecules over time is shown in Figure 8.6. The products of the dissociation of adsorbed water or formic acid molecules are protons (H+) and hydroxyl (OH-) ions. The OH- ions are produced from the decomposition of water at the surface by formation of silanol (Si-OH) groups as a result of surface protonation. 94 The ≡Si-O- (NBO) sites on the silica/silicate surface react with the adsorbed water molecules to become protonated.93,494,495 Compared with the silica/silicate surface, the exposed surfaces of Na-montmorillonite are the tetrahedral silicate layers with all the Si atoms being Q4 species, meaning that Si of SiO4 tetrahedron within the layer is connected by four bridging oxygens. OH- ions are highly reactive and can result in several other crucial reactions that determine the final composition of the 218 mixture. We also quantified the time dependent changes in concentration of OH- ions, as shown in Figure 8.6. As seen in the figure, for water + formic acid and pure formic acid cases, OH- concentration increases to a peak value in 0.2 ns and then reduces (or stays nearly constant) with time for all three regions. However, for pure water case, OH- concentration decreases as a result of interactions with the interlayer but increases due to interactions with the edge and facet regions. The decrease in OH- concentrations is attributed to reactions with formic acid. Formic acid dissociates to release a proton that combines with OH- to produce water leaving behind formate species following an acid- base neutralization reaction. These formate ions further react with OH- to produce formaldehyde following the reaction: HCOO- + OH- → HCHO + O2. This results in an increased concentration of formaldehyde as shown in Figure S8.7 (b). In the pure water case, OH- is mostly only consumed by Na+ ions that are present in the interlayer, resulting in a steadily decreasing trend, as seen in Figure S8.6. OH- ions are consumed by Na+ ions as soon as they form, to produce NaOH molecules, which either deposit in the interlayer or diffuse outwards (Figure S8.8), thus contributing to the leaching of Na+ ions. It is important to note the gradually decreasing trend of OH- concentrations in the interlayer region where Na-montmorillonite is reacted with formic acid compared with reactions with pure water at the edge and facet. This may be attributed to multiple competing reactions. In the interlayer region, OH- concentration decreases because these ions are consumed by Na+ ions as soon as they are produced, to form NaOH molecules (Figure 8.7). 219 Figure 8.6 The concentration of hydroxyl ions as a function of time at the edge, interlayer, and facet of Na-montmorillonite for various fluidic environments such as a 1:1 mixture of water and formic acid, formic acid, and water. Moreover, the replenishment of OH- ions by diffusion of water molecules to the interlayer is a comparatively slow process. For the edge and facet regions, however, continuous surface protonation constantly produces OH- groups but the concentrations of NaOH at the edge and facet is substantially lower than that of the interlayer. Lower than expected consumption of OH- ions is attributed to the slower diffusion of Na+ ions compared to OH- formation kinetics at the edges and the facets. This hypothesis is confirmed by the trends in HCOONa production rates as seen in Figure S8.13. The HCOO- molecules formed by the deprotonation of formic acid are neutralized with Na+ ion to form sodium formate (Figure S8.12). Alternatively, these HCOO- molecules are adsorbed on the surface of Na-montmorillonite and converted to CO, CO2, and carbonate (CO 2-3 ) species based on the local conditions. 220 Figure 8.7 NaOH concentrations as a function of reaction time at the edge, interlayer, and facets of Na-montmorillonite in various fluidic environments such as a 1:1 mixture of water and formic acid, formic acid, and water. 8.3.3.3 Conversion of HCOOH to CO, CO2, and CO 2-3 Groups The interactions of formic acid and clays at elevated temperatures and pressures result in the formation of CO, CO 2-2, and CO3 species. CO concentrations are particularly important since CO molecules are strong reducing agents, and the precursor to CO2 formation which is eventually converted to bicarbonates and carbonates. Figure 8.8 shows the concentration of CO in the different regimes as a function of time. For edge and interlayer, water + formic acid case yields higher CO concentration but for facets, pure HCOOH case results in a higher concentration. CO concentration increases with time in the interlayer but decreases in the facet region. In the edge region, in comparison, CO concentrations increase marginally up to 0.4 ns and then decrease. Interactions of formic acid and water mixtures with the edge and the interlayer result in higher levels of CO formation compared to formic acid. In contrast, formic acid produces more CO molecules due to interactions with the facet region of sodium montmorillonite. The mechanisms underlying these observations are discussed below. 221 Figure 8.8 CO concentrations as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid and formic acid are shown. There are two mechanisms involved in the formation of CO. In the first mechanism, CO is formed by the simple decomposition of HCOOH without any surface catalytic influences. In a surface catalyzed mechanism, the adsorbed water decomposes a formic acid molecule creating two water molecules and CO as shown in Figure 8.9. We performed independent bond restraint analysis on these two mechanisms, which yielded an activation energy barrier of ~59 kcal/mol for the surface catalyzed reaction and an activation energy of ~47 kcal/mol for the HCOOH decomposition reaction in the absence of a solid interface. Hence, these reactions have nearly equal probability of occurrence. For the case of simple decomposition, note that at 473 K, the kT energy ~1 kcal/mol is significantly lower than the energy barrier of ~47 kcal/mol. While the low kT energy may be insufficient to drive many such reactions in the system, for a single HCOOH molecule to decompose, it is only required that molecule absorbs enough vibrational energy for the C-O bond to vibrate, stretch, and eventually break. As temperature increases, we expect the concentration of CO to rise owing to higher kT energy. These reactions will be more prominent in the earth’s subsurface where the temperatures could go up to several 222 thousand kelvins. The same argument is also applicable to surface catalyzed HCOOH to CO conversion with an additional requirement of water molecules and a catalytic surface, which are also likely be present in subsurface environments, making this alternate route equally significant. Nonetheless, in the bulk fluid, we expect more HCOOH decomposition reactions while in the presence of surfaces, we expect more surface catalyzed CO production reactions. For instance, the water + formic acid case has substantially more CO concentration for edge and interlayer regions because the high concentration of surface adsorbed water aids in CO production. At the facet, CO formation due to the decomposition of HCOOH is dominant. Figure 8.9 Mechanisms involved in CO formation due to surface water catalysis where (a) represents the interactions between the water adsorbed on the surface and the formic acid molecule, (b) represents proton abstraction from C-H bond of formic acid to water and from water to oxygen resulting from hydrogen bonding (c) represents the formation of intermediate species: CO-H2O, and (d) shows the formation of CO and H2O molecules. The strong reducing nature of CO contributes to CO2 formation. The 1:1 mixture 223 of water and formic acid also produces more CO2 molecules, in all cases, compared to the pure water or formic acid cases. In principle, HCOOH to CO2 conversion can occur by three different mechanisms: direct, indirect, and the formate pathway, as represented by the reactions below: −2H+,−2e− 1. HCOOH ⟷ HCOOHad → CO2 (Direct pathway) (8.1) −H+,−e− −H+,−e− 2. HCOOH ⟷ HCOOH → HCOO−ad ad+ ? → CO2 (Formate pathway) (8.2) −H2O +H2O,−2H +,−2e− 3. HCOOH ⟷ HCOOHad → COad+ ? → CO2 (Indirect pathway) (8.3) Our simulations showed that the indirect mechanism as illustrated in Figure 8.11 is the dominant source of CO2. Here, the adsorbed CO molecules react with water at the surface to form CO2. From the CO2 concentration profile shown in Figure 8.10, it is clear that the CO molecules are consumed at the interlayer and produce more CO2 molecules. Figure 8.10 CO2 concentrations as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid and formic acid are shown. The concentration of CO2 also begins reducing after 0.4 ns owing to the formation of carbonic acid. This manifests as the decrease in CO2 concentration with time for edge 224 and interlayer cases (Figure 8.10). Whereas for the facet, carbonic acid production is low and therefore, we observe a steady rise in CO2 concentration. CO2 molecules can further react with water and form carbonate species i.e. conversion of CO2 to CO 2- 3 . CO 2- 3 concentration (Figure 8.12) changes only in the interlayer region whereas at edge and facet, it is non-existent. Figure 8.11 Mechanisms of CO2 formation resulting from the oxidation of CO catalyzed at Na-montmorillonite surfaces where (a) shows the adsorption of CO on the surface site, (b) represents the formation of intermediate species CO*, (c) represents the formation of intermediate species, H--CO2, and (d) represents the formation of CO2 and a proton. To interrogate the trends shown in Figure 8.12 further, we analyzed the pathways of CO 2- 3 formation, yielding two distinct mechanisms: −H+ −H+ 1. CO −2 + H2O → H2CO3 → HCO3 → CO 2− 3 (carbonic acid to carbonate decomposition as shown in Figure S8.17 and Figure S8.18) (8.4) 225 2. HCOO + O∗ → CO2−ad 3 + H + (surface catalyzed oxidation of adsorbed formate ion as shown in Figure 8.13). (8.5) Figure 8.12 CO 2-3 concentrations as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid and formic acid are shown. (Zero error bar indicates that all three simulation runs yielded same concentrations). In the interlayer region, due to multiple clay sheets engulfing the formic acid molecules, both these reactions were observed in our simulations. To assess which reaction is more probable, we examined the H2CO3 concentration (Figure 8.14). For edges, although H2CO3 concentration is high, no carbonate molecules are formed but for interlayer, although the H2CO3 concentration is lower than the edges, carbonate concentration is higher. The trends shown in Figure 8.12 and Figure 8.14 can be explained by the combined effects of long residence time of adsorbed H2CO3 ions, presence of interlayer Na+ and OH- ions in the interlayer region. H2CO3 molecules formed at the facets and edges diffuse out into the bulk fluid whereas those adsorbed at the interlayer decomposes to CO 2- 3 ions over time. The surrounding OH - ions help in abstracting protons from H +2CO3 and Na ions in precipitating the carbonate salts. These effects are mutually complementing in the interlayer region whereas that is not observed at the edge and facet regions. 226 Figure 8.13 Mechanisms involved in the formation of CO 2-3 species from HCOO - adsorbed at the interlayer of Na-montmorillonite by binding to the Al or Si site where (a) represents the simultanous attack of one dangling O of montmorillonite on C of HCOO- and weakening of C=O double bond followed by the formation of -C-O-Al/Si bridge as shown in (b), and the formation of CO 2- 3 which remains in adsorbed state and is neutralized by protons or Na+ ions as represented by (c). Figure 8.14 Carbonic acid (H2CO3) concentration as a function of reaction time at the edge, interlayer, and facet of Na-montmorillonite in 1:1 mixture of water and formic acid. For the interlayer region, however, the number of carbonate ions produced from H2CO3 conversion and HCOO- conversion is in ~1:3 ratio. This suggests that the carbonate formation reaction from H2CO3 conversion has higher probability of occurrence. To confirm this hypothesis, we performed bond restraint analysis on both these reaction pathways. Decomposition of carbonic acid (as shown in Figure 8.12) and bicarbonate ions (as shown in Figure 8.13) was shown to have an activation energy of ~29 kcal/mol and ~34 kcal/mol, respectively. On the other hand, the activation of energy 227 associated with the formation of CO 2-3 species from HCOO - adsorbed at the interlayer of Na-montmorillonite (as shown in Figure 8.14) was shown to have ~100 kcal/mol activation energy from bond restraint analysis. Therefore, it is energetically more favorable for carbonate production to proceed in the H2CO3 decomposition pathway, but the presence of mineral surfaces may invoke a surface catalyzed formate ion oxidation pathway, especially at high temperatures. The formation of HCO - 2- 3 and CO3 ions (Equation 4) is the underlying cause of reprecipitation of NaHCO3 and Na2CO3 described in Section 3.2. These precipitates can act as heterogeneous nucleation sites for further metal carbonate nuclei growth by different growth mechanisms observed by prior researchers like classical monomer-by- monomer addition and modern oriented attachment.196,485,496 8.3.3.4 Summary of Speciation Reactions Considering the complexity in speciation behavior of clay surfaces, we have summarized the various interfacial and speciation reactions described in sections 8.3.3.2 and 8.3.3.3 in Table 8.1. The first column contains stable intermediate and final species produced during the reaction process. The second and third columns contain the corresponding reaction pathways and activation sites observed in our simulations. The last column gives the energy barriers for the key reactions corresponding to second column obtained from bond-restraint calculations. Note that the energy barriers were only calculated for competing reactions to assess their relative significance. These results delineate the experimentally observed speciation behavior of Na-montmorillonite in aqueous and acidic media. These simulations advance the fundamental understanding of surface speciation behavior of clay minerals and can be employed to even more 228 complicated systems of mixed clays and directly compared with experimental data. Table 8.1 Summary of interfacial and speciation reactions observed in ReaxFF/MD simulations. Energy Observed barrier New Reaction pathways activation/reaction from bond species sites restraint analysis - H2O + --Si-O-Si-- → --Si-OH + Surface Si-O-Si 70 OH ≡Si-O- linkages kcal/mol46 HCHO HCOO- + OH- → HCHO + O2 Bulk fluid - Bulk fluid and NaOH Na+ + OH- → NaOH hydroxylated - surfaces HCOONa HCOO- + Na+ → HCOONa Adsorbed surfaces - HCOOH → CO + H2O Bulk fluid 47 kcal/mol CO Surfaces with HCOOH + H2O → CO + H2O adsorbed water and 59 kcal/mol acid molecules + Surfaces with CO2 COad +H2O → 2H + CO2 - adsorbed CO Bulk fluid and H2CO3 CO2 + H2O → H2CO3 - surfaces HCO - H - + 3 2CO3 → HCO3 + H Interlayer 29 kcal/mol HCO -3 CO 2- → 3 + H + Interlayer 34 kcal/mol CO 2- 3 Interlayer adsorbed 100 HCOOad + O*→ CO 2- + 3 + H surfaces kcal/mol NaHCO3 HCO - 3 + Na + → NaHCO3 Interlayer - Na2CO3 NaHCO3 + Na → Na + 2CO3 + H Interlayer - 8.4 CONCLUSIONS In this study, we determined the speciation behavior when sodium montmorillonite is reacted in three different fluid environments (water, formic acid, and 1:1 water + formic acid) using ReaxFF/MD simulations, IR spectroscopy, and X-ray 229 scattering (WAXS, SAXS) measurements. All the major peaks in the experimental IR spectra of Na-montmorillonite before and after reaction with water and formic acid, such as those corresponding to Si-O-Al linkages, O-H and CO 2-3 groups were predicted by ReaxFF/MD with reasonable levels of accuracy. Our MD simulations predict that bicarbonate (HCO -) and carbonate (CO 2-) ions react with Na+3 3 to produce NaHCO3 and Na2CO3 solid precipitates, respectively. A direct consequence of this precipitation – an increase in the interlayer spacing was observed as additional peaks in the SAXS intensity plot. Furthermore, WAXS intensities also showed strong signatures of NaOH and HCOONa which also have the tendency to precipitate in the interlayer regions. The differences in the reactivities of the edge, interlayer, and facet regions were noted from the simulations. The interlayer preferentially aided the formation of CO, CO2, and carbonates over the edge and facet regions. The higher reactivity of the interlayer is attributed to the presence of Na+ counterions owing to over/under-coordinated O-atoms and 5-fold coordination of cations in the octahedral layer. The facet region was the least reactive surface where most reactions were attributed to surface mediated decomposition of adsorbed species. Molecular-level mechanistic insights of the speciation behavior of OH- ions, CO, CO2, and CO 2- 3 were obtained from the MD simulations. In a pure water system, OH - ions are consumed by Na+ ions to form NaOH molecules that either deposit in the interlayer or leach outwards into water. In acid containing environments, OH- ions are consumed by formic acid to produce water and formate ions, which further reduce to formaldehyde (HCOO- + OH- → HCHO + O2). Formation of CO due to simple decomposition of HCOOH and water-assisted surface catalytic decomposition of 230 HCOOH was observed with both these pathways yielding energetically similar probability of occurrence. CO2 formed by the indirect conversion of CO to CO2 near the clay edge and interlayer surfaces. The formed CO2 later converts to HCO - 3 and CO 2- 3 molecules. The experimental and simulation approaches described in this study and the transferable forcefields for fluid-clay interactions can be applied translationally to advance the science of clay-fluid interactions for several applications including subsurface fluid storage and recovery and clay-pollutant dynamics. 231 8.5 SUPPLEMENTARY MATERIAL 8.5.1 Materials The as-received Na-montmorillonite (SWy-3) clay, procured from The Source Clays Repositories (Purdue University, West Lafayette, IN) was used in the study. Formic acid used in the study was purchased from Millipore Sigma and had the purity in the range of 98-100% (EMSURE® ACS, Reag. Ph Eur). 8.5.2 Quantum Chemical Calculations and Force Field Development The quantum mechanical DFT calculations of Sodium Bicarbonate has been performed with Jaguar497 software using M06-2x functional with 6-311++G(d,p) basis set. Full geometry optimizations were performed on these clusters without using any symmetry or structural constraints. To obtain the potential energy profile along the Na- O-C angle and Na-C off-diagonal. The constrained geometry optimization was applied in the Na-O-C angle ranging from 60° to 110° and Na-C off-diagonal ranging from 1.9 Å to 3.0 Å. The vibrational frequency of NaHCO3 molecule was also calculated using the same functional and basis set. The training set is provided in the Supporting Information. In this study we have optimized the reactive force field parameters for Na-O-C angle and Na-C off-diagonal to develop a transferable ReaxFF potential for Na/C/O interactions. The parameter sets were developed by training against QM data. We used the general ReaxFF parameter optimization strategy. This involved a single parameter linear search method. Parameter correlations which are quite extensive in ReaxFF are captured by performing multiple loops over the optimizable force field parameters until the force field error converges. The weights depend on the relevance of a particular training set data point typically, data points closer to the equilibrium are given higher 232 weights. Figure 8.15 Figure S8.1 Comparisons of ReaxFF to QM values for constraining of (a) Na-O-C angle and (b) Na-C off-diagonal. 233 Figure 8.16 Figure S8.2 ReaxFF and QM comparison of vibrational frequencies of NaHCO3 molecule. 234 Figure 8.17 Figure S8.3 Different C-O bond stretching and compression for NaHCO3 vibrational frequencies. Figures S8.1(a), S8.1(b) and S8.2 show the comparison between ReaxFF and QM values for angle scanning, off-diagonal scanning and vibrational frequencies respectively. The comparisons of ReaxFF to QM data is reasonably good and the difference is comparable to the error of DFT calculations. The average deviation of ReaxFF is 1.2 kcal/mol for Na-O-C angle and 0.75 kcal/mol for Na-C off diagonal. On expanding and confining the Na-O-C angle and Na-C off-diagonal it requires high energy. The DFT vibrational frequency range of NaHCO3 molecule ranges from 75 cm -1 to 3500 cm-1. It is represented in Figure S8.2 and agrees well with the frequencies calculated from ReaxFF force field. Frequencies 8, 9 and 10 in Figure S8.2 denote the C-O bond stretching and compression in all three directions and it ranges between 1000 cm-1 and 1700 cm-1. The normal modes representing mainly the C-O bond vibration is reported in Figure S8.3. 235 Figure 8.18 Figure S8.4 Physisorption of formic acid and water on Na-montmorillonite surface. (a) Less dense adsorption layer at t = 0 ps, (b) dense adsorption layer at t = 2.5 ps, and the zoomed in image of adsorbed layer (right). 236 Figure 8.19 Figure S8.5 Angle distribution in (a) Si-O-Si and (b) Si-O-Al linkages before and after reacting with water, as calculated from ReaxFF simulations. 237 Figure 8.20 Figure S8.6 The concentration of water (H2O) and formic acid (HCOOH) molecules with a ratio of 1:1 at the edge, interlayer, and facet of sodium montmorillonite are represented. The physisorbed state of the molecules is shown at t = 0. The concentrations of these molecules at reaction times of 0.2, 0.4, and 0.6 ns are shown. 238 Figure 8.21 Figure S8.7 Concentrations of H+, HCHO, CHO- and H2 as a function of time for various environments. 239 Figure 8.22 Figure S8.8 Mechanisms involved in the reaction of sodium ions with hydroxyl ions to produce sodium hydroxide molecules where (a) represents the surface oxygen atom of a strained Si-O-Si bond at the elevated temperature, (b) represents the protonation of the surface site and Na+/proton exchange in water, and (c) represents reactive/non-reactive diffusion of NaOH to bulk fluid. 240 Figure 8.23 Figure S8.9 Sodium leaching by charge neutralization (sodium hydroxide formation) (a) hydroxyl ion near surface attacks surface Na+ cation, (b) NaOH formation, (c) reactively/non-reactive diffusion of NaOH to bulk fluid. 241 Figure 8.24 Figure S8.10 Deconvolution of ATR-IR spectra in the range of 1800-1300 cm-1 for Na-Montmorillonite (a) unreacted, and reacted with (b) H2O, (c) HCOOH and (d) 1:1 mixture of H2O and HCOOH. The R-squared (R 2) values corresponding to the coefficient of determination (COD) for each deconvolution fit, representing the goodness of fits, are also reported. 242 Figure 8.25 Figure S8.11 Deconvolution of ATR-IR spectra in the range of 3800-2650 cm-1 for Na-Montmorillonite (a) unreacted, and reacted with (b) H2O, (c) HCOOH and (d) 1:1 mixture of H2O and HCOOH. The R-squared (R 2) values corresponding to the coefficient of determination (COD) for each deconvolution fit, representing the goodness of fits, are also reported. 243 Figure 8.26 Figure S8.12 Sodium leaching by charge neutralization (sodium formate formation) (a) attack on surface Na+ cation by formate ion (b) HCOONa formation (c) reactive/non-reactive diffusion of HCOONa to bulk fluid. 244 Figure 8.27 Figure S8.13 HCOONa concentration as a function of time in different regions (edge, interlayer, and facet) of Na-montmorillonite for various fluid environments (water + formic acid (1:1) and formic acid). 245 Figure 8.28 Figure S8.14 Carbon monoxide formation reaction. (a) Bond stretching in HCOOH molecule, (b) formation of intermediate species (CO, OH-, H+), and (c) formation of CO and water. 246 Figure 8.29 Figure S8.15 NaHCO3 concentration as a function of time in different regions (edge, interlayer, and facet) of Na-montmorillonite for water + formic acid (1:1) environment. 247 Figure 8.30 Figure S8.16 Na2CO3 concentration as a function of time in different regions (edge, interlayer, and facet) of Na-montmorillonite for water + formic acid (1:1) environment. 248 Figure 8.31 Figure S8.17 Carbonic acid (H2CO3) dissociation to bicarbonate ions (HCO -) and proton (H+3 ) where (a) represents O-H bond stretch in H2CO3, and (b) represents the formation of HCO -3 and H + ions. 249 Figure 8.32 Figure S8.19 Dissociation of bicarbonate ion (HCO -3 ) into carbonate ion (CO 2-3 ) and proton (H +) where (a) represent the O-H bond stretch in H2CO3, and (b) represents the formation of CO 2-3 and H + ions. 250 9 CONFINEMENT INDUCES STABLE CALCIUM CARBONATE FORMATION IN SILICA NANOPORES The contents of this chapter are currently under review in a journal as: H. Asgar,ǂ S. Mohammed, ǂ and G. Gadikota, in Nanoscale ǂ Equal Contribution 9.1 INTRODUCTION Carbonate transformations regulate carbon cycling and maintain the earth’s ecological balance. Rising anthropogenic CO2 concentrations in the air contribute to increasing global temperatures498 due to the greenhouse effect499 and threaten our ecological balance.500 Achieving tunable controls on carbon transformations is crucial for developing engineered processes for decarbonization and achieving net negative carbon emission goals.501,502 Several approaches have been proposed to capture and convert anthropogenic CO2 emissions. 503,504 Among these approaches, carbon mineralization which involves converting CO2 into solid inorganic carbonates 95 is thermodynamically downhill and can be engineered to store several gigatons of CO .96,972 Carbon mineralization can be realized through the direct chemical interactions of solid calcium and magnesium-bearing alkaline solid or aqueous resources with gaseous CO2 or by dissolving CO2 in water to produce (bi)carbonate-rich fluids that react to produce solid calcium and magnesium carbonates.382,505 The accelerated conversion of mobile CO2 into solid carbonates in subsurface geologic environments ensures permanent and safe storage and limits the need to monitor the fate of CO2 over several years. Similarly, engineered removal of CO2 from air and water to produce solid carbonates is a durable and quantifiable carbon management approach. Despite the gigaton-scale potential for storing CO2 in reactive subsurface 251 formations such as basalt98 and olivine,99 estimating the time scales of carbon mineralization is a challenge due to anomalous carbon mineralization behavior in nanoconfinement.100,101 Pore sizes in ultramafic minerals and rocks such as olivine and basalt can be smaller than 20 nm.102 In these nanoporous environments, the interfacial organization of pore fluids contributes to anomalous carbonate crystallization behavior that differs significantly from that of bulk fluids. Achieving predictive control over the formation of calcium or magnesium carbonates in confinement is crucial for several reasons. First, this approach enables the reconciliation of faster than expected carbon mineralization rates in subsurface environments as opposed to predicted rates as noted in the CarbFix project.98 Second, resolving the influence of interfacial water on the formation of metastable or stable carbonate phases is crucial for developing engineered strategies for carbon removal using porous materials. Third, the role of confinement in directing the formation of specific carbonate phases preferentially assists with determining the associated impact on storing gigaton levels of CO2 in these environments. The formation of stable carbonates such as calcite (CaCO3) or magnesite (MgCO3) is preferred since the structures of stable carbonate remain unchanged over a long period and stoichiometric utilization of Ca or Mg to produce stable carbonates is achieved. Stable carbonate phases have lower solubility compared to metastable phases.506,507 Metastable carbonates, in contrast, gradually transform into stable carbonates over time.508 Examples of metastable calcium carbonate phases include spherical vaterite (CaCO3) and rosette-shaped aragonite (CaCO ).509,5103 Examples of metastable magnesium carbonates include needle-like nesquehonite (MgCO .3 3H 511 2O), sheet-like hydromagnesite 252 ((MgCO3)3(Mg(OH)2)2·4H2O), 512 and platy lansfordite (MgCO . 5113 5H2O). The formation of magnesium hydroxide in hydromagnesite is a less effective use of magnesium as opposed to the complete utilization of magnesium to produce magnesite. The confinement-mediated behavior of carbonates formation has been studied in the context of biomineralization508,513–515 to understand exoskeleton growth in invertebrates. However, a mechanistic understanding of how carbonates form in subsurface abundant nano-porous (pore sizes 2 – 50 nm) siliceous matter remains unresolved despite the rising interest in engineered carbon transformations for a sustainable climate, energy, and environmental future. While prior studies reported the formation and stabilization of amorphous calcium carbonate in micron-level confinement,516 the influence of nanoscale confinement on the preferential formation of stable or metastable calcium carbonate phases has not been studied. Various carbonate crystallization mechanisms have been proposed to describe formation and growth mechanisms in bulk fluids but are applicable under limited conditions. Classical nucleation growth (CNG), which describes a first-order transition occurring via (i) nucleation of a solid phase and (ii) subsequent spontaneous growth,517 and classical crystal growth theory (CGT), which suggests a layer-by-layer growth of carbonates once a critical size is reached, are applicable in limited scenarios.518,519 Alternatively, the Ostwald Rule of Stages, in which the formation of stable crystalline phases is mediated by intermediate metastable carbonate states with lower free energy barriers to formation, explains specific observations related to stable calcite formation.520 However, this theory does not explain observations of the direct formation of stable carbonates.521 Alternatively, for crystal sizes smaller than 100 nm, size-dependent variation in 253 the enthalpic contributions of the free energy and small variations in enthalpic differences (e.g., 1–10 kJ/mol) was proposed to explain the formation of metastable vaterite, aragonite, and then calcite.522 It is hypothesized that metastable to stable carbonate changes occur via solid-state transformations and dissolution-reprecipitation mechanisms. For example, the transformations of amorphous calcium carbonate (ACC) to biominerals that occur in the absence of water are attributed to solid-state transformations.523 Alternatively, the dissolution of more soluble metastable phases to produce more stable and less soluble phases has been proposed.524 This phenomenon, which is based on the differences in the solubility of phases, is analogous to “Ostwald Ripening,” which describes size-dependent dissolution and reprecipitation behavior. Other non-classical theories such as “oriented attachment” describe the spontaneous self-assembly of nanocrystalline particles along crystallographic faces to aid particle-mediated growth of 1D, 2D, and 3D crystals.514,525,526 It was also hypothesized that differences in the ordering of the solvent at solid interfaces and around ions can create free energy minima where nanoparticles can reside without aggregating before the formation of a meso-crystalline structure.527 Despite these mechanistic insights, the dual effects of surface interactions and nanoscale confinement on carbonate formation in siliceous nanopores with sizes ranging from 2 nm to 50 nm remain unresolved. Advancing predictive controls into the carbon mineralization behavior in silica nanopores is crucial for estimating the time scales for converting mobile CO2 into stable carbonates. Conversion of mobile CO2 into mineralized solids limits the need to track the fate of fluidic CO2 and eliminates the risk of CO2 ex-solution and preferential partitioning into the atmosphere. 254 In carbon mineralization for Ca- and Mg- silicate interfaces, the reactions proceed in two steps: (i) release of Ca2+ or Mg2+ ions by the dissolution of silicate phases in acidic conditions, and (ii) formation of solid carbonates at pH > 8.528 Carbon mineralization occurs when the concentrations of the dissolved cations and carbonate species reaches supersaturation. Limiting conditions for carbon mineralization can include CO2 solvation, the insufficient concentration of dissolved Ca and Mg species, and solid carbonate precipitation. Prior work in bulk fluids has shown that dissolved carbonate concentrations from anthropogenic CO2 can be enhanced using biomimetic catalysts such as carbonic anhydrase529,530 and solvents such as amines and amino acids 531–533. Sufficiently high concentrations of dissolved carbonate ions in fluids bearing calcium ions favor calcium carbonate precipitation. In this work, the influence of nanoscale confinement and silica interfaces on directing the formation of stable or metastable calcium carbonate phases is investigated. The specific scientific questions that motivate this study are: (a) How do we architect silica nanochannels with ordered geometry and porosity to investigate the influence of confinement on carbon mineralization? (b) What are the preferred structural orientations of calcium carbonate grown in nanoscale confined environments? (c) What is the influence of the organization of ions in confinement and surface interactions on calcium carbonate formation in nanoscale confinement? To address these research questions, silica nanochannels with well-ordered vertically aligned pores with sizes of 3.7 nm were synthesized within alumina membranes using a sol-gel approach. Calcium carbonate formation in these nanopores is achieved by reacting solutions of 0.1 M calcium nitrate (Ca(NO3)2) and 0.1 M sodium bicarbonate (NaHCO3). The influence of the differences in the hydration structure of Ca 2+ ions at the 255 pore surface and in the center of the pore on the formation of calcium carbonate phases are inferred from molecular dynamics simulations. This approach of developing architected materials to investigate calcium carbonate formation in a calibrated manner sheds insights into the role of silica interfaces, interfacial fluids, and hydration structure of Ca2+ ions in confinement on the preferential formation of specific calcium carbonate phases in confinement. Figure 9.1 is a schematic representation of the research approach. These studies are particularly relevant since silica-based minerals and rocks are abundant in subsurface environments97,98 where CO2 storage via carbon mineralization at the scale of several gigatons is proposed. Figure 9.1 Schematic representation for (a) synthesis of silica nanochannels in alumina membranes, and (b) the formation of solid carbonates in silica nanochannels. (c) Radial distribution functions (RDFs) for Ca2+-Ocarbonate species ‘at the pore surface’ and ‘pore center’ obtained from molecular dynamics simulations, and the corresponding snapshots of the simulations. 9.2 MATERIALS AND METHODS 9.2.1 Synthesis of Silica Nanochannels (SNCs) Silica nanochannels (SNCs) with well-defined pore sizes within anodic alumina membranes (AAMs) are synthesized using a sol-gel approach. AAMs (Cytiva WhatmanTM AnodiscTM) having a diameter of 25 mm and a thickness of 60 µm are used. Silica is hydrolyzed from tetraethylorthosilicate (TEOS) in ethanol and hydrochloric acid (HCl), while cetyltrimethylammonium bromide (CTAB) is used as the structure-directing 256 agent. In a typical synthesis method, 7.68 g of ethanol, 11.57 g of TEOS, and 1 mL of 2.8 mM HCl are mixed at 60 °C for 90 minutes under reflux to pre-hydrolyze the solution. In a separate beaker, 1.52 g of CTAB is dissolved in 4 mL of 55 mM HCl, and 15 g of ethanol under stirring for 30 minutes at 200 rpm using the magnetic stirrer. Both solutions are mixed for 15 minutes at 400 rpm. To synthesize SNCs in AAMs (pore sizes in AAM ~ 200 nm, pore length ~ 60 µm), the empty membranes are loaded on the aspiration setup (Figure 9.2), and 0.5 mL of mixture solution is added to the membrane under applied aspiration. Once the solution is passed through the membrane, 0.5 mL is added again and allowed to pass through the membrane. This step is repeated 5 times and the membranes are removed from the setup and rinsed with ethanol to avoid any precipitation on the sides of the membranes. Finally, the membranes are placed at room temperature and the reaction is allowed to proceed for 24 hours, which governs the formation of SNCs inside the pores of AAMs. CTAB is removed from the inside of SNCs by heating AAM-SNCs at 250°C for 4 hours in a benchtop muffle furnace (Thermo Scientific Thermolyne FB1410 M, Asheville, NC). The temperature corresponding to the decomposition of CTAB is estimated from the thermogravimetric analysis of AAM-SNCs, where the major weight loss associated with the degradation of CTAB is noted ~250 °C (Figure S9.1 (a)). The weight (%) changes in the samples of interest during thermal treatment are determined up to 800 °C with a ramp rate of 5 °C/min in an N2 environment (purged at 25 mL/min) using a Thermogravimetric Analyzer (TGA) (TA Instruments, SDT650, New Castle, DE). The pore size distribution and specific surface area of silica nanochannels in AAM (AAM-SNCs) are determined using the nonlocal density functional theory (NLDFT, Quantochrome AutoSorb iQ Analyzer, Boynton Beach, FL) using N2 257 adsorption isotherm at 77 K. Before measuring the isotherms, the sample is outgassed at 90 °C for 24 hours. The morphological changes during the synthesis of silica nanochannels are imaged using a scanning electron microscope (Zeiss LEO 1550 FESEM) and transmission electron microscope (FEI F20 TEM) at 200 kV. Figure 9.2 Schematic representation of steps involved in the synthesis of silica nanochannels (SNCs) inside the alumina membrane. 9.2.2 Formation of Calcium Carbonate in Confinement To investigate the formation of calcium carbonate (CaCO3) phases in confinement, 0.1 M Ca(NO3)2 and 0.1 M NaHCO3 solutions are mixed in a molar ratio of 1:1 and added to silica nanochannels (SNCs). The silica nanochannels are constructed in the pores of anodic alumina membranes (AAMs). A solution comprising 0.1 M Ca(NO3)2 and 0.1 M NaHCO3 was loaded into the silica nanochannels using an aspiration setup (Figure S9.2). The loading of the solutions into the silica nanochannels was repeated five times to ensure full penetration into SNCs. The outer surfaces of the membranes are cleaned with DI water to prevent calcium carbonate formation outside the silica nanochannels. The structural evolution of the calcium carbonate phases is determined using an X-ray diffractometer (XRD) (Bruker D8 Advance ECO Powder Diffractometer) with Cu Kα radiation, the acceleration voltage of 40 kV, and current of 25 mA. The XRD 258 patterns are obtained in the range of 2θ = 20 ̊ – 80 ̊ after 6, 18, and 30 hours of reaction time. 9.2.3 Investigation of Ion Hydration and Transport Behavior using Molecular-Scale Simulations The hypothesis that the anomalous formation of calcium carbonate phases in confinement compared to bulk fluids emerges from interactions with the silica surfaces, hydration structure of calcium ions, and organization of interfacial fluids is investigated using molecular dynamics simulations. For comparison, simulations of dissolved calcium ions in bulk fluids are performed. Briefly, 0.1 M CaCO3 solutions are simulated as bulk fluids while confined in cylindrical silica nanopores with pore diameters of 3.7 nm at 298 K and 1 bar. The simulation cell for investigating the hydration structure of calcium ions in bulk fluids has dimensions of 6 nm × 6 nm × 6 nm in x, y, and z directions, respectively. The confinement environment is composed of a cylindrical silica pore with 1 g/cm3 of 0.1 M CaCO3 solution. The pore (dia. 3.7 nm) is cleaved in an amorphous silica matrix with dimensions of 10.69 nm × 6.42 nm × 6.42 nm in x, y, and z directions, respectively. The simulation cells used for investigating the hydration structure of calcium ions in bulk and confined configurations are shown in Figure 9.3. Periodic boundary conditions are applied on bulk and confined configurations in all three dimensions. The silica surface and water molecules are modeled using parameters from CLAYFF371 and flexible SPC/E forcefields,370 respectively. The OPLS/AA forcefield is used to model Ca2+ and CO 2-3 ions.369 Table S9.1 summarizes the interatomic potentials. 259 Figure 9.3 Snapshots of the initial configurations of (a) bulk and (b) confined CaCO3 solutions in cylindrical silica nanopores with diameter of 3.7 nm. Calcium and carbonate atoms are shown in VDW drawing method while water and silica atoms are shown in Lines drawing method implemented in VMD software. The bulk and confined configurations are optimized through energy minimization using the “steepest descent” approach for 50,000 steps. NVT simulations are performed on the bulk and confined solutions for 50 ns. The temperature is held constant at 298 K using a Nose-Hoover thermostat with a relaxation time of 0.1 ps.376,377 The intermolecular interactions of the simulated systems are calculated as the sum of the electrostatic contributions for all Coulomb interactions between the partial atomic charges and a short- range van der Waals dispersive interactions, given by the Lennard-Jones potential. The equation of motion is integrated using the leapfrog algorithm with a time step of 1 fs. The short-range interactions are calculated within a cutoff of 1.4 nm, while the long-range electrostatic interactions are treated using Particle Mesh Ewald (PME).534 The non- bonded van der Waals and electrostatic interactions are modeled using 12-6 Lennard- Jones and coulombic models, respectively. The bonded interactions are accounted for in bond stretching, angles bending and dihedrals, except for silica matrix where only OH bond stretching is considered. All the simulations are conducted using GROningen Machine for Chemical Simulations (GROMACS 2018) simulation package.378 260 9.3 RESULTS AND DISCUSSION 9.3.1 Synthesis of Silica Nanochannels (SNCs) Sol-gel synthesis approaches provide unprecedented tunable controls on the particle and pore morphologies of architected siliceous materials.535,536 The concept of dissolving a surfactant (e.g., CTAB) and introducing and condensing silica around surfactant templates to direct sol-gel formation has opened opportunities to synthesize particle and pore morphologies with specific shapes and sizes. For example, amorphous silica,535 forsterite (Mg2SiO 536 4), and wollastonite (CaSiO3) 537 with ordered pores ranging from 2–20 nm can be architected based on advances in sol-gel and hydrothermal syntheses. One of the less explored approaches involves creating silica nanochannels in existing porous templates to develop predictive controls over carbon mineralization in confinement. Architecting these materials to study carbon mineralization pathways will unlock unprecedented controls into the mechanisms underlying carbonate formation in nanoconfined environments. To address this challenge, architected silica nanochannels are developed in alumina membranes (Figure 9.2). The absence of any crystallinity in Amorphous Alumina Membranes (AAMs) (by Cytiva WhatmanTM AnodiscTM and procured from Fisher Scientific) is evident from the XRD patterns in Figure S9.3 (a)). These commercially available AAM materials have pore sizes of ~200 nm as evident from the SEM image in Figure. S9.3 (b). The changes in the weight % of as-synthesized SNCs in AAMs before and after CTAB removal were determined using thermogravimetric analysis (TGA) are shown in Figure S9.1 (a). For comparison, the TGA curve of as-received AAM is also shown. The major weight loss for as-prepared SNCs in AAMs is noted around 250 °C, corresponding 261 to the removal of CTAB.538–541 The SNCs formed inside the pores of AAMs were imaged by dissolving the amorphous alumina components in 10 wt.% H3PO4 solution for 24 hours and recovering SNCs via centrifugation. The SEM image of SNCs obtained from dissolving the surrounding anodic alumina constituents is shown in Figure 9.4 (a). The formation of SNCs along the length of the membrane is noted in this image. The cylindrical orientation of SNCs is evident from the TEM image in Figure 9.4 (b). The outer diameter of the nanochannels formed inside the pores of AAMs is ~200 nm which is comparable to the pore size in AAMs. The uniformity and consistent lengths of the silica nanochannels throughout the membranes evident from the TEM and SEM images in Figure 9.4 show the complete filling of AAM pores with the sol-gel precursor leading to the formation of morphologically and chemically uniform SNCs. Figure 9.4 (a) Silica nanochannels (SNCs) formed inside the alumina membrane as viewed using Scanning Electron Microscopy (SEM) after the dissolution of alumina membrane using 10 wt.% H3PO4. (b) High-resolution imaging of SNCs using Transmission Electron Microscope (TEM). (c) The pore size distribution of SNCs determined using N2 adsorption-desorption measurements. The average pore size, pore volume, and specific surface area of SNCs in AAMs are 3.77 nm, 0.11 cc/g, and 57.17 m2/g, respectively. These parameters are determined using the NLDFT method with cylindrical silica pores model at 77 K for liquid N2. The uniformity of pore size distributions of SNCs with a pore diameter of 3.7 nm is evident in Figure 9.4 (c). 262 9.3.2 Formation of Calcium Carbonates in Silica Nanochannels (SNCs) The hypothesis that nanoscale confinement contributes to the oriented growth of calcium carbonate is investigated by injecting a solution comprising a mixture of 0.1 M Ca(NO3)2 and 0.1 M NaHCO3 solutions into silica nanochannels to grow calcium carbonate. The formation of calcium carbonate in silica nanochannels is evident from thermogravimetric analyses. The weight loss associated with the dissociation of calcium carbonate on heating is evident from Figure S9.1 (b). Calcium carbonate formation is determined by collecting X-Ray Diffraction (XRD) data at 6, 18, and 30 hours after loading the calcium nitrate and sodium bicarbonate solutions into silica nanochannels. The XRD patterns (Figure 9.5) reveal the dominant growth of the (104) plane of calcium carbonate followed by the (214) plane. In rhombohedral calcite, the typical dominant planes are (104), (113), (018), and (116). In contrast, the dominant planes in orthorhombic aragonite are (111), (021), (012), (112), and (221). In metastable vaterite with hexagonal crystal habitat, the dominant planes are (100), (101), (102), and (110). Complete XRD patterns of these polymorphs of calcium carbonate are shown in Figure S9.4 for comparison. The prominent planes that distinguish calcite, aragonite, and vaterite phases are (104), (111), and (101), corresponding to the d-spacings of 3.03 Å, 3.39 Å, and 3.29 Å, respectively.542,543 The distinct formation of (104) planes and the absence of (111) and (101) planes in this study is indicative of the formation of calcite in silica nanochannels (Figure 9.5). The preferential growth of calcite along the (104) plane is attributed to the lowest density of surface broken bonds among the other calcite surfaces544,545 and surface energy,544,546,547 and an equal number of positive and negative charges.548 Further, the (104) plane follows a flat (F) character as shown in Figure 9.5 (c).549 The (214) plane becomes statistically significant after reaction for 30 hours. The reflections from the (214) 263 plane can emerge from the particle growing in the vicinity of the nanochannel wall and appears to develop its characteristic “step-like” (S) nature as the growth along the dominant (104) plane proceeds. The schematic comparison of flat (F) and “step-like” (S) profiles for (104) and (214) planes along [441] zone axis is shown in Figure 9.5 (c)). The crystallite sizes of 1.3 nm, 1.8 nm, and 1.9 nm after 6 hours, 18 hours, and 30 hours, respectively, indicate a sluggish growth after first 6 hours (Figure 9.5 (b)). The growth of the calcite phases is slower between 18 hours and 30 hours likely due to pore size constraints 544. These measurements show the preferential formation of stable calcite phases over metastable calcium carbonates in nanoscale confinement several hours after loading the initial solution bearing calcium and bicarbonate ions into the nanochannels. Figure 9.5 (a) Identification of stable calcite phases inside silica nanochannels (SNCs) acquired at different time intervals using X-ray Diffraction (XRD). (b) Crystallite sizes determined using Scherrer equation. (c) Schematic representation of calcite structure and growing (104) and (214) plane projected along the [441] zone axis.549 The sizes of the calcium carbonate crystallites are estimated from the XRD data using the Scherrer equation (shown in equation (9.1)).550,551 In equation (i), D represents the average crystallite size, K = 0.9 is Scherrer constant, λ is the wavelength of X-ray source used (Cu Kα = 0.154 nm), 2θ is Bragg angle, and B(2θ) is the Full Width at Half Maximum (FWHM). The units of θ and B(2θ) are radians. 𝐾 . 𝜆 𝐷 = (9.1) 𝐵(2𝜃) . cos𝜃 264 Based on this expression, the crystallite sizes of calcite are estimated to be 1.3 nm, 1.8 nm, and 1.9 nm after 6 hours, 18 hours, and 30 hours of reaction time, respectively (Figure 9.5 (b)). The growth of the calcite phases is slower between 18 hours and 30 hours likely due to spatial constraints of the pore size.544 These measurements directly suggest the formation of stable calcite phases preferentially over metastable calcium carbonates in nanoscale confinement several hours after loading the initial solution bearing calcium and bicarbonate ions into the nanochannels. The preferential orientation planes of calcite are (104) and (214) planes (Figure 9.5 (a) and 9.5 (c)). Prior studies investigating the formation of calcium carbonate in confinement showed that in Track Etch (TE) – membrane polycarbonate with micrometer-sized pores552 and fungal hyphae tubular cells, amorphous calcium carbonate (ACC) is formed initially.553 The amorphous calcium carbonate eventually transforms into calcite and aragonite phases. In TE-membrane polycarbonate with pore diameters of 25 nm, 50 – 800 nm, and 1200 nm, respective aragonite, aragonite and calcite, and calcite are formed at room temperature.554 The formation of calcite in cylindrical pores of TE-membranes reported by Lotte and co-workers552 is consistent with the findings of this study. Moreover, pH has a significant impact on the formation of calcium carbonate polymorphs. For example, calcite-like ACC and vaterite-like ACC are obtained at pH ~ 8.75 and 9.8 or higher, respectively. Aragonite-like ACC is obtained in multi-component ionic environments including in the presence of Mg2+ ions.555 The pH of the solution in the silica nanochannels is closer to 8.75, which aligns with the initial formation of calcite- like ACC structure before transforming into calcite. Fewer water molecules in the coordination environment of Ca2+ ions556–558 in confinement compared to bulk fluids 265 contribute to the formation of stable calcium carbonate. Fewer carbonate ions in the first coordination shell of Ca2+ ions favor stable calcite formation over metastable aragonite.559 Additional factors to consider in the context of selective calcium carbonate polymorphs include confinement-induced ion transport, concentration profiles, and changes in the probability of formation.516 The influence of ion transport, cation hydration behavior, and concentration profiles on the formation of specific calcium carbonate polymorphs are investigated using molecular dynamics simulations and discussed in the section below. 9.3.3 Influence of Ion Hydration and Transport on Calcium Carbonate Formation Fundamental mechanistic insights into the organization, hydration, and transport of ions in confinement leading to calcium carbonate (CaCO3) formation in silica nanopores are investigated using molecular dynamics simulations. Simulations are performed in bulk and confined fluids to contrast ion organization, hydration, and transport behavior leading to calcium carbonate formation in these environments. The static structure of the pre-nucleated CaCO3 solutions in bulk and confined fluids is described by the radial distribution function (g(r)) (Figure 9.6) and the corresponding coordination number (n(r)) (Figure 9.7) of water-oxygen (Owater) and carbonate-oxygen (OCarbonate) atoms in the first coordination shell of Ca2+ ions. The number of water molecules in the first coordination shell of Ca2+ ions in bulk environments is about 7.2, which is consistent with reported X-ray scattering measurements and molecular simulation studies.560 It is interesting to note that a higher number of oxygen atoms corresponding to CO 2-3 ions are evident in the first coordination shell of Ca2+ ions compared to oxygen atoms corresponding to water molecules (Figure 9.7 (a) and Table 9.1). The number of oxygen atoms corresponding to the carbonate ions in the first coordination shell of Ca2+ cations 266 is 4.23 ± 0.03 (Figure 9.7 (b) and Table 9.1), which is in agreement with the findings of Wang and co-workers after accounting for the difference in the solutions’ concentrations.561 Figure 9.6 Radial distribution function [g(r)] as a function of radius. (a) Calcium (Ca2+)- water oxygen (OW) in bulk fluid. Inset: water in the first coordination shell of Ca 2+ ion. (b) Ca2+-carbonate oxygen (OR) in bulk fluid. Inset: carbonate in the first coordination shell of Ca2+ ion. (c) Ca2+- OW in confinement (silica nanochannel). (d) Ca 2+- OR in confinement. Insets in (c & d): Ca2+ and CO 2-3 ions in the pore center and at pore surface. Table 9.1 The number of water oxygen (OWater) and carbonate oxygens (OCarbonate) in the first coordination shell of Ca2+. Error bars represent the standard deviation from the mean values of three different simulations. Bulk Fluid Away from Pore Surface At Pore Surface O 3.60 ± 4×10-2 3.03 ± 3×10-2Water 2.55 ± 5×10-2 OCarbonate 4.23 ± 3×10-2 4.51 ± 1×10-2 4.08 ± 3×10-2 The dehydration of calcium carbonates, mainly by heating, promotes the transformation of amorphous to crystalline morphologies such as the transformation of 267 amorphous calcium carbonate (ACC) to mesostructured calcite.556–558 Thus, fewer water molecules in the coordination environment of Ca2+ ions in confined fluids provide another dehydration pathway to tune the transformation of metastable amorphous carbonate structures to crystalline calcite morphologies. Confinement was also found to have a significant influence on the transport behavior of ions. Significant differences are noted in the self-diffusion coefficients and the local distribution of Ca2+, CO 2-3 and water in bulk fluids and those confined in pores. In bulk fluids, the diffusion coefficients of Ca2+, CO 2-3 and water molecules are (0.63 ± 0.03) × 10 -5, (0.63 ± 0.02) × 10-5 and (2.51 ± 0.12) × 10-5 cm2/sec, respectively (Table 9.2). These values are consistent with the diffusion coefficients reported by Wang and co-workers.561 Table 9.2 The self-diffusion coefficient (10-5 cm2/sec) of Ca2+, CO 2-3 and water in bulk and in confined systems. Error bars represent the standard deviation from the mean values of three different simulations. Confinement Bulk Fluid Away from Pore Surface At Pore Surface Ca2+ 63.0×10-2 ± 3×10-2 10.6×10-2 ± 4×10-3 0.24×10-3 ± 4×10-5 CO 2-3 62.8×10-2 ± 2×10-2 13.8×10-2 ± 6×10-3 4.92×10-3 ± 2×10-4 Water 251.0×10-2 ± 12×10-2 67.7×10-2 ± 9×10-3 21.10×10-3 ± 8×10-4 268 Figure 9.7 Coordination number [n(r)] as a function of radius. (a) Calcium (Ca2+)-water oxygen (OW) in bulk fluid. (b) Ca 2+-carbonate oxygen (OR) in bulk fluid. (c) Ca 2+- OW in confinement (silica nanochannel). (d) Ca2+- OR in confinement. Significant differences in the diffusion coefficients of ions in bulk and confined fluids were noted. The diffusivity of Ca2+ and CO 2- 3 ions at the pore surface is more than two orders of magnitude lower compared in the center of the pore due to surface diffusion. The formation and growth of calcium carbonate crystals are directly related to the diffusion of calcium and carbonate ions. Prior MD simulations and experiments showed that the formation rate of CaCO3 crystals in bulk solvents increases exponentially with the enhanced diffusion of ions.562 The diffusion of Ca2+ and CO 2-3 ions have been controlled by using various additives including other ions such as Na+, Cl- and OH-,563 glycerol,562 and poly(acrylic acid) (PAA).564 Reduced diffusivity of Ca2+ and CO 2-3 ions 269 observed on adding these additives to the aqueous solutions is attributed to the formation of ion pairs between Ca2+ and CO 2-3 with the added ions, enhanced solution viscosity on adding glycerol and controlled the directional diffusion of ions in hydrogels using PAA. Furthermore, the morphology of the formed carbonate crystals can be tuned by controlling ion diffusion. In addition to the formation enhancement, slowing the diffusion of ions enables tuning the morphology of the formed carbonate crystals. In this context, Wang and co-workers565 showed that a decrease in the diffusion of calcium and carbonate ions promotes the formation of vaterite and aragonite crystals and the joint effect of the diffusion-reaction leads to the formation of cubic and needle-like particles. Similarly, Jo and co-workers566 found that the gradual decrease in the diffusion of ions results in morphological transitions from hopper-like to rosette-like and otoconia-like calcite structures. Kim and co-workers demonstrated that controlling the diffusion of the ions by adding poly(acrylic acid) in hydrogel results in a variety of calcite morphologies including elliptical and spherical calcite structures.564 These studies support our finding that significantly reduced diffusivities of ions at the pore surface contributes to the formation of stable calcite phases. 9.4 CONCLUSIONS Understanding the pathways of carbon mineralization in subsurface-related, silica-rich reservoirs is essential to meet the future goals of energy landscape. In this context, the mineralization mechanisms in reservoirs with nanoscale confinements needs investigation due to their abundance at the proposed mineralization sites. In this work, we study the formation of calcium carbonate in silica nanochannels having diameter = 3.7 nm and report the preferential formation of stable calcite phase over metastable 270 aragonite or vaterite phases. From molecular dynamics simulations, we note relatively fewer water molecules of hydration and a higher number of carbonate ions surrounding calcium ion (Ca2+) in confinement compared to bulk fluid. The number of oxygen atoms around Ca2+ in confinement is 6, which is a suitable condition for calcite formation compared to aragonite formation (9 oxygen atoms). The formation of stable carbonates is favorable for the permanent storage of CO2, especially in silica-rich reservoirs. 271 9.5 SUPPLEMENTARY MATERIAL Figure 9.8 Figure S9.1 Estimation of weight changes using thermogravimetric analysis (TGA). (a) Changes in the weight loss of the as-received anodic alumina membrane (AAM) and silica nanochannels (SNCs) prepared using the sol-gel approach. Weight loss at 250 °C corresponds to CTAB removal from SNCs. (b) Changes in the weight associated with the dissociation of calcium carbonate formed in SNCs. 272 Figure 9.9 Figure S9.2 Loading of Ca2+ and CO 2-3 containing solutions in silica nanochannels. Schematic representation of sample preparation approach for carbonate formation inside silica nanochannels and organization of the formed carbonate crystals. 273 Figure 9.10 Figure S9.3 Characterization of the as-received Anodic Alumina Membrane (AAM). (a) The amorphous structure of the as-received anodic alumina membrane (AAM) determined using XRD. (b) Morphology of as-received membrane imaged using SEM. 274 Figure 9.11 Figure S9.4 X-ray diffraction (XRD) patterns of different polymorphs of calcium carbonate. Identification of different planes in polymorphs of calcium carbonate (CaCO3) as reported in the American Mineralogist Crystal Structure Database (AMCSD). (a) XRD pattern of calcite. (b) Aragonite. (c) vaterite. The referred AMCSD datasets are also mentioned. 275 Table 9.3 Table S9.1 The forcefields parameters of the atoms in silica pores, water molecules, and ions are obtained from the references listed in Ref. column. Atom  (nm)  (kJ/mol) q (e) Ref. Silica Si 0.302 7.700610-6 2.1000 371 O bridging 0.316 0.650190 -1.0500 371 O nonbridging 0.316 0.650190 -0.9500 371 H 0.000 0.000000 0.4250 371 SPCE O 0.316 0.6502 -0.82 370 H 0.000 0.000 0.41 370 Ions Ca2+ 0.2412 1.88136 2.000 369 C (CO3) 0.356 0.29288 1.420 369 O (CO3) 0.303 0.50208 -1.140 369  is the finite distance at which the interatomic potential is zero.  is the depth of the potential well. q is the atomic charge. 276 10 CONCLUSIONS AND OUTLOOKS In this dissertation, the behavior of fluids in the subsurface-related natural and architected siliceous materials, comprising nanosized confinements, and interfaces are studied using cross-scale X-ray scattering, IR spectroscopy, gas adsorption-desorption advanced imaging tools, and molecular dynamics simulations. To develop a calibrated understanding of reactivity in the subsurface environments, the first part of the dissertation is dedicated to understanding the design considerations for architected siliceous materials and the evolution of structural and microstructural changes in natural materials. Further, the organization of macromolecules at siliceous interfaces is studied, which are relevant for carbon dioxide uptake in such systems in subsurface environments. Finally, the anomalous reactivity in natural siliceous materials of organic acid (formic acid), hydrochloric acid, and nucleation of stable carbonates in architected silica nanochannels are investigated. These studies provide detailed insights into the factors that can influence the formation of nanoscale confinements, interfacial organization of fluids, and the fate of dissolved or nucleated species in subsurface-related reservoirs. The synthesis of silica nanoparticles using the Stöber method has been investigated extensively and can be used as model geo-architected materials to understand the phenomenon related to the subsurface. However, the effect of thermal treatments to tune the pore sizes in these particles remains less studied. The changes in the pore radii during calcination (600 °C) and sintering (1050 °C) processes are studied using in- operando USAXS/SAXS measurements, as reported in Chapter 2. Calcining the particles does not have a significant effect on the pore radii while sintering the particles can reduce the pore size from 2.2 nm to ∼1.8  nm. The thermal treatment also caused a transition of 277 the pore-solid interface from rough to smooth. These changes at the pore-solid are attributed to the formation of siloxane (Si-O-Si) bridges resulting from dehydroxylation. The pore sizes are also determined using N2-adsorption measurements and remain in good agreement with USAXS/SAXS measurements. Moreover, the reaction mechanisms related to the organization and formation of mesoporous silica during colloidal synthesis can be tuned by altering the chemistries and compositions of the reactants. The fast polymerization of Si-O-Si species during hydrolysis and condensation, to form the skeleton of mesoporous particles, in the presence of nitrate ions is noted using transmission and grazing-incidence SAXS measurements, which accelerates the onset of 2D hexagonal structure (Chapter 3). The micron-scale morphologies of the particles are found to be influenced by the aging in the synthesis solution, where in the presence of magnesium nitrate salt the plate-like particles changed to spherical particles. The experimental methodologies developed in these studies can be used to advance the predictive controls on the synthesis, and chemo-morphological changes in siliceous materials for different scientific and engineering applications. The microstructural and structural evolutions in naturally occurring aluminosilicate, halloysite, having nanotubular morphology during thermal treatment to temperatures as high as 875 °C are determined using in-operando USAXS/SAXS/WAXS measurements and discussed in Chapter 4. The interlayer water is expelled from the halloysite structure at around 125 °C, as noted by the change in the interlayer spacing (from 9.8 Å to 7.2 Å). Halloysite goes through dehydroxylation between 400 °C – 625 °C, resulting in the formation of amorphous meta-halloysite. The heating also affects the pore size and curvature of halloysite nanotubes. The slight expansion of the nanotube 278 diameter is caused by dehydroxylation, which also increases the nanotube wall thickness. The average pore sizes in the consolidated halloysite samples, informed by nano-X-ray computed tomography, and N2 adsorption-desorption characterizations. Finally, the comparison of changes in the morphological and structural evolution in nanotubular halloysite and planar kaolinite reveals that the pore space in halloysite is preserved upon thermal treatment, while in the case of kaolinite, it collapses due to dehydroxylation. The insights from this study about the thermally induced transformations of aluminosilicates with different morphologies but similar compositions can help in deciding the right material for specific applications. Leveraging the subsurface-related chemistries to facilitate the capture and utilization of carbon dioxide as phase-changing fluids for applications related to resource recovery is also important. The functionalization of silica nanoparticles using poly(allylamine) (PAA) polymeric chains can assist the uptake of carbon dioxide via weak hydrogen bonds, leading to the formation of hydrogels in these systems (Chapter 5). The carbon dioxide uptake is governed by the formation of carbamate ions along with protonated primary and secondary amines and bicarbonates in PAA functionalized silica hydrogels. The carbon dioxide capture is found to be enhanced in PAA functionalized silica nanoparticles, compared to pure polymer, which is attributed to the formation of swollen branched polymers with increased exposure to carbon dioxide, originating from both enthalpic and entropic contributions. The research methodology presented in Chapter 5 can be used to inform the morphological evolution in polymeric hydrogels using in-operando USAXS measurements and develop the chemo-morphological basis of carbon dioxide mediated hydrogel formations in subsurface-related chemistries. 279 The understanding of the shape and structure of assembled macromolecules, such as micelles, which can alter the interfacial properties of oil-water interfaces in subsurface environments, at siliceous interfaces remains less explored and can influence the organization of these macromolecules and eventually determine the extent of application of these micelles for the cases of interest. In Chapter 6, the organization of CTAB and CTAB + P123 micelles is investigated on quartz surfaces and in the bulk fluid using MD simulations, SAXS, GI-SAXS measurements. The quartz surface causes the ellipsoid core-shell CTAB micelles to elongate as compared to bulk fluid. The addition of P123 molecules results in elongation of ellipsoid core-shell micelles in bulk fluid, while at the quartz surface, in the presence of P123, cylindrical core-shell micelles are formed. MD simulations reveal that the quartz surface assists the faster aggregation of micelles for both CTAB and CTAB + P123. These insights provide a basis to tune the morphologies of macromolecular micelles at solid interfaces relevant to geological environments for applications related to carbon dioxide storage and utilization for subsurface energy applications. Understanding the feedback effects on the mineralogy of depleted shale reservoirs is important in the context of permanent carbon dioxide storage in the reservoirs. Chapter 7 provides the report on chemo-morphological changes in three different shale samples with varying silica, carbonate, and clay contents after reaction with 1M hydrochloric acid. The effects of phase dissolution and evolution in the porosity of shales are determined using IR spectroscopy, X-ray scattering, and X-ray tomography measurements. The dissolution of carbonate and clay phases in silica-lean and carbonate/clay-rich shales reduces the relative amorphous content of silica, while the corresponding crystalline 280 content is enhanced. However, the amorphous silica content is increased relative to crystalline silica in silica-rich – carbonate/clay lean, and silica, carbonate, and clay- bearing shales corresponding to the dissolution of clays, which results in the precipitation of amorphous silica particles in the pore spaces. Further, the dissolution of phases and reprecipitation of silica results in the non-monotonic porosity in silica-rich – carbonate/clay lean shale. The findings in this study provide a crucial understanding to develop predictive controls over the fate of fluids in subsurface shale-rich reservoirs for applications related to sustainable technologies. Na-montmorillonite clay offers a difference in reactivities at the edge, interlayer, and facet regions, which can lead to a difference in the speciation behavior in these regions. The speciation behavior of Na-montmorillonite is investigated upon reaction with water, formic acid, and a 1:1 mixture of water + formic acid using IR spectroscopy, X-ray scattering measurements, and ReaxFF/MD simulations in Chapter 8. The experimental IR spectra of Na-montmorillonite, before and after reactions, are reproduced from simulation results with exceptional accuracy. The Na+ ions in the interlayer of montmorillonite clays can react with bicarbonate (HCO -3 ) and carbonate (CO 2- 3 ) ions to produce NaHCO3 and Na2CO3 precipitates, respectively, which results in a slight increase in the interlayer spacing. The formation of NaOH and HCOONa from WAXS patterns is also noticed. The interlayer is found to preferentially aid the carbonate, CO, and CO2 formation, compared to facets and edges, which is attributed to the presence of Na+ counterions in the interlayer. The combinatorial simulation and experimental approach used in this study to develop the forcefields for fluid-clay interaction in reactive 281 environments can be transferred to other fluid-clay systems to advance the calibrated science for a range of applications related to subsurface fluid storage and recovery. The nucleation of solid carbonates in architected silica nanochannels (SNCs), representative of subsurface reservoirs, is investigated (Chapter 9). SNCs having a diameter of 3.7 nm facilitate the formation of stable calcite phases instead of metastable vaterite or aragonite phases as revealed by X-ray diffraction measurements. The formation of stable calcite is attributed to the presence of relatively fewer water molecules of hydration in the vicinity of calcium ion (Ca2+). Moreover, a higher number of carbonate ions (CO -3 ) are also found surrounding Ca 2+ ion, which facilitates the nucleation of calcite. The study shows that the nanoscale confinements (< 5 nm) favor the formation of stable carbonates, which is desirable for the permanent storage of CO2 in silica-rich subsurface reservoirs. The results reported in this dissertation filled several knowledge gaps about the synthesis and design of geo-architected siliceous materials, evolution in the structural and microstructural features of natural aluminosilicates, organization, and interfacial behavior of macromolecules at siliceous interfaces, anomalous reactivity of naturally occurring siliceous materials in the presence of different acids, and the formation of stable carbonate in subsurface-related nanoconfinement. These findings are significant to develop a fundamental understanding of the design of model geo-architected materials, and their use for many energy and environmental applications. The tunable controls over the structural and microstructural features of hierarchical geomaterials can help in designing the desired substrates to study the effects of confinements on fluid properties related to thermodynamics, flow, and reactivity. 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