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Catalytic processes constitute the backbone of the chemical industry, facilitating the production of over 85% of the world’s chemicals. Catalysts are broadly divided into heterogeneous catalysts, consisting mainly of transition metal, alloy, or oxide surfaces, and homogeneous catalysts, composed largely of ligand-bound complexes of transition metals. More recent developments in this area include single atom catalysts, where metal atoms are atomically dispersed over oxide and other supports.

Our research is geared towards developing and utilizing quantum chemistry and machine learning methods to develop in silico design principles for these catalysts based on activity and selectivity requirements, for a wide range of applications, including shale gas conversion, automobile exhaust chemistry, and fuel cell catalysis.