C2+ Selectivity for CO2 Electroreduction on Oxidized Cu-Based Catalysts

Design for highly selective catalysts for CO2 electroreduction to multicarbon (C2+) fuels is pressing and important. There is, however, presently a poor understanding of selectivity toward C2+ species. Here we report for the first time a method of judiciously combined quantum chemical computations, artificial-intelligence (AI) clustering, and experiment for development of a model for the relationship between C2+ product selectivity and composition of oxidized Cu-based catalysts. We 1) evidence that the oxidized Cu surface more significantly facilitates C–C coupling, 2) confirm the critical potential condition(s) for this oxidation state under different metal doping components via ab initio thermodynamics computation, 3) establish an inverted-volcano relationship between experimental Faradaic efficiency and critical potential using multidimensional scaling (MDS) results based on physical properties of dopant elements, and 4) demonstrate design for electrocatalysts to selectively generate C2+ product(s) through a co-doping strategy of early and late transition metals. We conclude that a combination of theoretical computation, AI clustering, and experiment can be used to practically establish relationships between descriptors and selectivity for complex reactions. Findings will benefit researchers in designing electroreduction conversions of CO2 to multicarbon C2+ products.