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Methodologies: Data Mining, Data, Statistics and Stochastic Methods, Physics-Specific Methods

Bryan Goldsmith

Assistant Professor, Chemical Engineering

Bryan Goldsmith is an Assistant Professor in the Department of Chemical Engineering. His works focus on theĀ development of novel catalysts and materials. The world is facing a growing population, mass consumerism, and rising greenhouse gas levels, all the while people strive to increase their standard of living. Computational modeling of catalysts and materials, and making use of its synergy with experiments, facilitates the process to design new systems since it provides a valuable way to test hypotheses and understand design criteria. HisĀ research team focuses on obtaining a deep understanding of catalytic systems and advanced materials for use in sustainable chemical production, pollution abatement, and energy generation. They use first-principles modeling (e.g., density-functional theory and wave function based methods), molecular simulation, and data analytics tools (e.g., statistical learning and data mining) to extract key insights of catalysts and materials under realistic conditions, and to help create a platform for their design.

A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)

A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)