Carbon dioxide (CO2) recycle as a feedstock for producing chemicals contributes to alleviate global climate changes caused by the increasing CO2 emissions. Hydrogenation of CO2 to synthesize carbon monoxide and/or methanol has attracted considerable interests. Here, we presented a combined density functional theory (DFT) and Kinetic Monte Carlo (KMC) simulation to study the conversion of CO2 and H2 to methanol and ethanol on Cu and Cu-oxide systems. The results pinpoint the effects of doping on the reaction pathways, the possible intermediates and transition states. The descriptors are identified, which can describe the catalytic activity and therefore are useful for the rational design of better of Cu-based catalysts for CO2 hydrogenation. The present work provided better understanding of CO2 conversion on Cu-based catalysts and on the basis developed the descriptor-based method for rational screening of complex catalysts at a theoretical level.

Alkali-promoted activity and selectivity toward CO2 reduction

ACS Fall 2021

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