Computational Discovery And Synthesis Of Two-Dimensional Materials
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The discovery of graphene in 2004 has led to an explosion in research efforts towards other 2D materials. 2D materials not only represent the ultimate scaling in the vertical direction, but also show a variety of novel and useful electronic, optical, and mechanical properties. This thesis presents computational studies which can be categorized in four areas; first, the study of ripples in graphene, second the discovery of structure and properties of 2D materials, specifically, group-IV monochalcogenides; third, the substrate assisted synthesis routes for the synthesis of 2D materials, specifically group-III-V materials and hexagonal GaN; and lastly, the application of 2D materials as photocatalyst for water splitting. First, we show using Molecular Dynamics simulations that thermally induced dynamic ripples in graphene lead to angular deviations of the surface normal that agree with previous electron diffraction experiments (from static ripples), settling a long-standing debate about the nature of ripples in graphene and multi-layer graphene. The ripples can be both dynamic and static in nature and the magnitudes of both types of ripples are similar as they are controlled by the same energetics. Primarily, the static ripples correspond to the low-energy deformation modes of graphene, which are most easily formed due to small strains. These low-energy deformation modes are equivalent to static longwavelength out-of-plane phonon modes, typical of dynamic ripples. We also discover scaling relationships for the average angular deviations as a function of size of the graphene sheet L and averaging radius R and show that temperature, strain, and layer numbers can be used to manipulate these deviations. Our work provides guidance to the optimization of properties that are sensitive to out-of-plane distortions. Second, we use Density Functional Theory calculations to determine the structure, stability and electronic properties of 2D materials in family of groupIV monochalcogenides. The computational screening approach undertaken in this study provides a generic approach for a broader discovery and characterization of, as yet, hypothetical 2D materials using computational methods. To assess their potential in electronic applications, we also predict their electronic properties, such as band gaps, bandedge positions and effective masses using the HSE06 functional which accurately predicts the electronic structure of materials by including some fraction of exact exchange and correct part of the selfinteraction error. The 2D group IV-monochalcogenides materials show useful electronic properties suited for optoelectronics and solar energy conversion Third, the discovery of a novel material requires not only the identification of the materials composition, but also suitable synthesis conditions. We present a generic computational approach to identify suitable substrates for the stabilization of 2D materials and apply the method to the recently predicted 2D III-V compounds. We identify several lattice-matched substrates for their epitaxial growth, stabilization, and functionalization. These substrates make the 2D materials thermodynamically stable and lead to charge doping due to the workfunction difference. Our approach allows to select substrates which not only stabilize the 2D materials, but results in the smallest distortion of their structure and control over the electronic doping of the 2D materials. And lastly, we summarize recent successes in the field of solar water splitting using 2D materials. We review a computational-based screening approach to rapidly and efficiently discover many more 2D materials that possess properties ideal for solar water splitting. Computational tools for the determination of intrinsic properties of potential photocatalyst, such as electronic properties, optical absorbance and solubility in aqueous solutions are discussed. Further possibilities of enhanced photocatalytic activity of these 2D materials is explored by use of mechanical strain, bias potential, dopants and pH.
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