High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications

Abstract

Abstract An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H2S, HCl, HCN, K2O, KCl, NH3) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al2O3, MgO, anatase-TiO2, rutile-TiO2, ZnO, ZrO2) catalysts and supports. Approximately 3,000 unique adsorption geometries and corresponding adsorption energies were obtained.