UC Berkeley

Surface properties can behave drastically different from bulk properties. Moreover, these properties are harder to model and compute. However, key industrial processes such as catalysis, plasma etching, and solution-processed assembly techniques are surface driven, and thus computing, modeling, and exploring these surface phenomena are of importance. In this dissertation, the surface driven phenomena of photocatalytic CO2 reduction is explored through the lens of high-throughput density functional theory. Methodology is developed to screen potential photocatalysts and applied to novel tellurium-containing semiconductors. As a result, important chemisorption, charge transfer, and bonding trends are discovered. Additionally, a high-throughput methodology is developed to screen potential etchant gases on amorphous materials. This methodology is critical to the processing of microelectronic devices. Finally, in the realm of semiconductor processing, an experimental methodology to assemble perovskite nanoparticles into superlattices is researched. Emergent properties of these superlattices are explored. The processing techniques exploits surface driven phenomena. The findings discovered and presented in this dissertation will be impactful for two critical areas of industry: catalysis and semiconductor processing.