Understanding the intracellular processing and biological response of ultrasmall fluorescent silica nanoparticles is critical to improving their therapeutic potency, however most imaging methodologies cannot resolve the structures containing nanoparticles. Using the superior optical properties of ultrabright silica nanoparticles in optical super-resolution microscopy is one such way to quantify biological response at the subcellular level. This dissertation describes the optimization of fluorescent silica nanoparticles followed by the synthesis and optical characterization of novel super-resolution nanoprobes. Additionally, the dissertation introduces imaging buffer free nanoprobes for live cell super-resolution imaging and a methodology for quantifying cellular compartments containing such probes. First, the surface chemical properties of ultrasmall (sub-10 nm) amorphous silica nanoparticles (SNPs) covalently encapsulating organic fluorophores are optimized by switching negatively charged dyes to positively charged dyes and tuning the ammonia content in the synthesis reaction. The resulting particles are then characterized using gel permeation chromatography (GPC) and high performance liquid chromatography (HPLC). The optical properties of such particles, referred to as Cornell Prime dots (C’ dots), can be altered by the introduction of different moieties, such as sulfur and iodine, within the silica matrix producing therapeutic particles for photodynamic therapy and nanoprobes for optical super-resolution microscopy. Using block-copolymers as templates, these nanoparticles are shown to provide an increase in signal-to-noise ratio, as compared to free dyes, leading to sharper super-resolved structures. These super-resolution nanoprobes, referred to as srC’ dots, were further simplified by the discovery that aluminosilicate C’ dots (aC’ dots) intrinsically blink using a single laser excitation source and no additional buffer additives, thus indicating ideal candidates for live cell super-resolution microscopy. We expanded our understanding of cell processing of these particles by using nearest neighbor analysis to determine the size of cellular compartments and the number of particles within them.