Computational Screening of a Promising Diatomic Catalyst for CO2 Electroreduction to Syngas

The escalating emission of carbon dioxide (CO2) poses significant environmental challenges, necessitating efficient strategies for its reduction to value-added products. In this work, we employed density functional theory (DFT) calculations to identify promising diatomic catalysts (DACs) for the electrochemical reduction of CO2 to syngas. Focusing on nitrogen-doped graphene as a substrate, we systematically screen various metal combinations from 3d transition metals (ranging from Ti to Zn) and particularly concentrate on Cr-Fe configuration. Our computational models rigorously evaluate the catalytic efficiency and selectivity of these DACs in both the hydrogen evolution reaction (HER) and the CO2 reduction reaction (CO2RR). The key findings reveal that CrFe@DAC2 displays balanced electrochemical selectivity and high catalytic efficiency in both reactions, with notably low overpotentials. Our approach integrates detailed computational techniques, including the constant potential method (CPM) and molecular dynamics simulations, to rigorously evaluate the dynamic stability and electronic structure of CrFe@DAC2. These methodologies offer deep insights into the catalyst's activity, particularly highlighting the role of significant charge transfer and electronic redistribution. This study not only identifies Cr-Fe as a particularly promising DAC for syngas production from CO2 but also provides deep insights into the electronic mechanisms underlying high catalytic performance.