Subsurface hydrogen as a hidden driver of copper surface reconstruction in CO2 electroreduction

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Authors: Siwang Zhang, Hang-Biao Lv, Zhong-Zhang Shi, Ruoxuan Wang, Shisheng Zheng, Jian-Feng Li
Cited by: 6
References: 69

Abstract

ABSTRACT Copper (Cu) undergoes significant surface reconstruction during CO2 electroreduction, which is strongly modulated and accelerated by reaction intermediates, yet the atomic-scale mechanism remains far behind the experimental observations. By integrating machine-learning interatomic potentials with large-scale grand canonical Monte Carlo simulations, we systematically investigated *CO- and *H-induced surface roughening across various Cu facets. Our simulations demonstrate that high surface *H (*Hsur) coverage facilitates subsurface hydrogen (*Hsub) incorporation on (100)-dominated Cu facets under typical working conditions (−1 V vs. reversible hydrogen electrode), while such penetration is negligible on (111)-like surfaces. This facet dependence is primarily attributed to a *H-induced hexagonal surface reconstruction observed on (100)-dominated facets, a process driven primarily by geometric rather than electronic effects. Specifically, high *H coverage triggers a partial transition of Cu atoms from ideal 4-fold hollow sites to more closely packed 3-fold arrangements. The local densification expands the spacing at the remaining 4-fold sites, thereby reducing the energy barrier for *Hsub migration into the subsurface. Further analysis reveals that *Hsub alone is sufficient to induce Cu adatom formation, even in the absence of nearby *CO, uncovering a revised structural evolution paradigm for Cu surface roughening. We propose an alloying strategy using low hydrogen affinity metals (Zn, Al, Ga) to effectively suppress *Hsur incorporation, offering a promising pathway for designing Cu-based catalysts with long-term stability.

Fields of Study & Subjects

CO2 Reduction Techniques and Catalysts Machine Learning in Materials Science Electrocatalysts for Energy Conversion

Publication details

Journal / source
National Science Review
Publisher
Oxford University Press (OUP)
Volume
13
Issue
9
Pages
nwag128–nwag128
Publication date
5 March 2026
Language
EN