Surface Coverage as an Important Parameter for Predicting Selectivity Trends in Electrochemical CO2 Reduction

The electrochemical CO2 reduction reaction (CO2RR) is important for a sustainable future. Key insights into the reaction pathways have been obtained by density functional theory (DFT) analysis, but so far, DFT has been unable to give an overall understanding of selectivity trends without important caveats. We show that an unconsidered parameter in DFT models of electrocatalysts-the surface coverage of reacting species -is crucial for understanding the CO2RR selectivities for different surfaces. Surface coverage is a parameter that must be assumed in most DFT studies of CO2RR electrocatalysts, but so far, only the coverage of nonreacting adsorbates has been treated. Explicitly treating the surface coverage of reacting adsorbates allows for an investigation that can more closely mimic operating conditions. Furthermore, and of more immediate importance, the use of surface coverage-dependent adsorption energies allows for the extraction of ratios of adsorption energies of CO2RR intermediates (COOHads and HCOOads) that are shown to be predictive of selectivity and are not susceptible to systematic errors. This approach allows for categorization of the selectivity of several monometallic catalysts (Pt, Pd, Au, Ag, Zn, Cu, Rh, W, Pb, Sn, In, Cd, and Tl), even problematic ones such as Ag or Zn, and does so by only considering the adsorption energies of known intermediates. The selectivity of the further reduction of COOHads can now be explained by a preference for Tafel or Heyrovsky reactions, recontextualizing the nature of selectivity of some catalysts. In summary, this work resolves differences between DFT and experimental studies of the CO2RR and underlines the importance of surface coverage.

Automated summary

The electrochemical CO2 reduction reaction is essential for sustainable development, and the use of density functional theory analysis can aid in understanding selectivity trends. Surface coverage is a crucial parameter that must be considered in DFT studies, and by explicitly treating the surface coverage of reacting species, the extraction of adsorption energy ratios can help predict selectivity effectively.