To overcome the limits imposed by existing resource heavy, CO2 intensive processes, we need to identify novel materials that are more efficient. Our research group focuses on developing methods that go beyond the status quo of exploring static properties and perform screening of the material space based on thermodynamics and kinetics. This will enable the prediction of dynamic properties for large material spaces leading to better identification of materials for target applications.

Finding more efficient manufacturing processes and finding alternate manufacturing processes using electricity as two of the key targets to achieve a net-zero carbon emission by 2050. To achieve the emission target, we need to concurrently focus on understanding the basic science behind these alternate processes while making them technology ready. Our group adopts a bottoms up approach when approaching these research problems. Quantum chemistry calculations and molecular dynamics simulations provide the essential atomistic understanding of the fundamental chemistry. The insights gained from the atomistic perspectives such as rate constants can then be applied to device scale simulations. Our bottoms up approach allows us to perform predictive and quantitative modeling of the non-equilibrium and dynamic processes.