Who We Are
Our research uses computational chemistry to design new catalysts for greener chemical transformations and to study materials with interesting catalytic, magnetic, or chemical applications. We commonly use periodic and non-periodic Density Functional Theory (DFT) and various atomic population analysis methods. We also develop algorithms and distribute software codes for computing net atomic charges, atomic spin moments, effective bond orders, and other atomistic descriptors using the Density Derived Electrostatic and Chemical (DDEC) method. Currently, we have a NSF Career Award project to computationally design mixed matrix membranes for purifying (a) helium from natural gas sources and (b) hydrogen from solar water splitting. This project involves developing better techniques to automate the construction of polarizable, flexible, force-fields for atomistic simulations of gas separations in metal-organic frameworks. We are developing computational techniques to efficiently compute atomic polarizabilities, dispersion coefficients, and dispersion inclusive DFT functionals for materials modeling. In another project, we are using computations and experiments to develop organometallic complexes that will be more efficient selective oxidation catalysts. For more information, please click on one of the above menu items.