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Electroreduction of CO 2 (eCO 2 RR) has emerged as a promising alternative for production of renewable fuels and important commodity chemicals such as ethylene and ethanol. Simultaneously, it opens an economically attractive path to mitigate point sources of CO 2 , a potent greenhouse gas. Despite decades of research efforts, Cu remains the only catalyst capable of producing significant amounts of desirable C 2+ products, containing more than one carbon atom. However, further improvement is needed for industrial applications. It is known that roughened copper-based electrocatalysts surfaces exhibit enhanced selectivity towards C 2+ products during electroreduction of CO 2 . This poses a challenge for modeling efforts aiming to find a rationale for the enhanced selectivity. In this work, we use an innovative modeling approach to investigate roughened copper surfaces derived from cuprous oxide on structures of 100x100 nm 2 size with atomic resolution and accuracy compared to density functional theory (DFT). We combine semilocal DFT (RPBE) in VASP, effective medium theory (EMT), and linear scaling relationships via the recently proposed alpha parameter scheme to investigate the site-resolved catalytic selectivity of copper sites. Electrode potential-dependence is included via the use of the VASPsol implicit solvation and a grand canonical potential approach. The approach allows us to investigate the effect of varied macroscopic roughness on the intrinsic catalytic activity of copper by comparing surfaces exposed to simulated sputtering and electropolishing, respectively. The study highlights i) the challenge for designing improved copper catalysts for CO 2 RR with monodisperse active site selectivity, ii) the need for careful experimentation when comparing to theory, and iii) the limitations of macroscopic roughness in controlling atomic scale activity.
Stenlid et al. (Fri,) studied this question.
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