Computational Screening of Single and Di-Atom Catalysts for Electrochemical CO₂ Reduction

Abstract

Supported single atom catalysts on defected graphene show great potential for electrochemical reduction of CO₂ to CO. In this study, we perform a computational screening of single and di-atom catalysts (MNCs and FeMNC respectively) with M varying from Sc to Zn on nitrogen-doped graphene for CO₂ reduction using hybrid-density functional theory and potential dependent micro-kinetic modeling. The formation energy calculations reveal several stable single and di-atom doping site motifs. We consider the kinetics of CO₂ using the binding energies of CO₂* and COOH* intermediates as the descriptors to analyze the activity of these catalysts. In comparison to (211) transition metal (TM) surfaces, both MNCs and FeMNCs show a variety of binding motifs of the reaction intermediates on different metal dopants. We find four MNCs as CrNC, MnNC, FeNC, and CoNC with high catalytic efficiency for CO₂R. Among the different FeMNCs with varying doping geometry and surrounding N-coordination, we have identified 11 candidates having high TOF for CO production and lower selectivity for the hydrogen evolution reaction. FeMnNC shows the highest activity for CO₂R. Large CO₂* dipole-field interactions in both the MNCs and FeMNCs give rise to deviations in scaling from TM surfaces.