Anand Verma

Abstract Heterogeneous catalytic pathways for clean energy conversion involve thousands of elementary steps, but most models involve only a few dozen reactions. We combine extensive density functional theory calculations, machine learning for activation barrier prediction, and human intelligence-inspired elementary reaction enumeration and identification. This enables automated kinetic modeling of CO2 hydrogenation on copper, a key process to produce fuels and chemicals.