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

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.

Automated summary

In this study, computational screening and analysis were conducted to investigate the catalytic activity of single and di-atom catalysts on nitrogen-doped graphene for CO2 reduction. The research identified high-efficiency catalysts and studied their behavior and binding motifs.