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

Supported single atom catalysts on defected graphene show great potential for electrochemical reduction of CO 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 CO 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 CO using the binding energies of CO* 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 COR. 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 COR. Large CO* dipole-field interactions in both the MNCs and FeMNCs give rise to deviations in scaling from TM surfaces.