The electrochemical reduction of CO₂ is known to be influenced by the identity of the alkali metal cation in the electrolyte; however, a satisfactory explanation for this phenomenon has not been developed. Here we present the results of experimental and theoretical studies aimed at elucidating the effects of electrolyte cation size on the intrinsic activity and selectivity of metal catalysts for the reduction of CO₂. Experiments were conducted under conditions where the influence of electrolyte polarization is minimal in order to show that cation size affects the intrinsic rates of formation of certain reaction products, most notably for HCOO^-, C₂H₄, and C₂H₅OH over Cu(100)- and Cu(111)-oriented thin films, and for CO and HCOO^- over polycrystalline Ag and Sn. Interpretation of the findings for CO₂ reduction was informed by studies of the reduction of glyoxal and CO, key intermediates along the reaction pathway to final products. Density functional theory calculations show that the alkali metal cations influence the distribution of products formed as a consequence of electrostatic interactions between solvated cations present at the outer Helmholtz plane and adsorbed species having large dipole moments. The observed trends in activity with cation size are attributed to an increase in the concentration of cations at the outer Helmholtz plane with increasing cation size.

While the search for catalysts capable of directly converting methane to higher value commodity chemicals and liquid fuels has been active for over a century, a viable industrial process for selective methane activation has yet to be developed. Electronic structure calculations are playing an increasingly relevant role in this search, but large-scale materials screening efforts are hindered by computationally expensive transition state barrier calculations. The purpose of the present letter is twofold. First, we show that, for the wide range of catalysts that proceed via a radical intermediate, a unifying framework for predicting C-H activation barriers using a single universal descriptor can be established. Second, we combine this scaling approach with a thermodynamic analysis of active site formation to provide a map of methane activation rates. Our model successfully rationalizes the available empirical data and lays the foundation for future catalyst design strategies that transcend different catalyst classes.