Motivation

Sustainable energy and chemical production largely hinges on the development of catalysts that efficiently transfer energy into molecules for storage (e.g. H2O oxidation or CO2 or N2 reduction into feedstocks for fuels or fertilizers). Doing so would open doors for renewable technologies to produce useful fuels and chemicals from O2, water, CO2, and N2.

KeithGroup cycle

Figure adapted with permission from 
(Olah, G. A.; Prakash, G. K. S.; Goeppert, A.  J. Am. Chem. Soc. 2011, 133, 12881-12898). 
Copyright (2011) American Chemical Society. 

A key hurdle in all of these processes is understanding how to drive multi-proton and electron transfers in a way so that products are made efficiently (i.e. with low overpotentials and high faradaic efficiencies). Having a quantum-level understanding of when and why good catalysts function and to what extent they can be improved would give guidance for rationally designing more sustainable processes. 

We approach this problem using a variety of computational chemistry tools to enable predictions of potential energy surfaces to better understand reaction pathways and ensembles of mechanisms. Our group carries out computational investigations to determine the underlying thermodynamic energies and kinetics of reaction steps under their actual operating conditions. With this information we bridge a continuous understanding of homogeneous, heterogeneous, and biomimetic reaction mechanisms to aid the design of next-generation catalysts.