Abstract
Understanding the synergistic effect of Cu-based alloys on the adsorption behavior and selectivity of the CO2 reduction reaction is a crucial step toward directional catalyst design. To this end, density functional theory calculations are employed to investigate Cu-based alloys with diverse doping elements and contents. The results show that the scaling relation still holds in the alloy system, and the strategies to improve the selectivity are put forward based on the adsorption strength of *C and *OCHO intermediates. Further, a model combining the adsorption theory and machine learning algorithm is proposed to capture the relationship between the adsorption energy and the geometric environment. It explains that the difference in d-band centers between the doped metals and Cu affects the variation trend of the adsorption strength and reveals that the intermetallic synergistic effect can be quantified by the bonding distance and d orbital radius on both the adsorbate and metal side.
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