(544dr) Bayesian Chemisorption Theory of Catalysis

The spectroscopic techniques with the quantum chemical theory have led to fruitful knowledge of chemical bonding at metal surfaces. But our understanding of molecule-surface interactions is still far from being complete. As new materials systems are probed, for example, the intermediates and activated complexes at metal surfaces, established ideas within the traditional chemisorption theory often need to be modified, which might lead to new design approaches in catalysis. In this poster, we present a Bayesian learning model rooted at the Newns-Anderson type model Hamiltonian, which captures trends of chemical bonding of complex species at metal surfaces.