电化学
溶剂化电子
化学
电子转移
化学物理
量子
水溶液
反应机理
还原(数学)
工作(物理)
势能面
氢
电子
反应速率常数
电极电位
蒙特卡罗方法
电化学电位
原子物理学
计算化学
电极
路径积分公式
标准氢电极
可逆氢电极
势能
物理
选择性
物理化学
曲面(拓扑)
分子物理学
机制(生物学)
吉布斯自由能
路径积分蒙特卡罗
路径(计算)
动能
氧化还原
产品(数学)
质子耦合电子转移
热力学
作者
Xiaolong Yang,Shenzhen Xu
摘要
The initial hydrogenation step of *CO on Cu(111) dictates product selectivity in electrochemical CO2 reduction, yet its mechanism remains controversial. Here, at an acidic aqueous Cu(111) interface, we systematically compute the free energy profiles for *CHO and *COH formation via multiple pathways, including direct *H transfer, water-assisted shuttling, and proton-coupled electron transfer (PCET), using machine learning force fields to enable statistical sampling within a grand canonical constrained path integral hybrid Monte Carlo framework that incorporates constant electrode potential, explicit solvation, and nuclear quantum effects (NQEs). At the investigated potential of U = -0.4 V vs SHE and 300 K, *COH does not remain a stable intermediate within the present explicit-solvent Cu(111) model and spontaneously dissociates into *CO and solvated H3O+. For *CHO formation, solvated protons are identified as the primary hydrogen source, predominantly proceeding via the PCET pathway. Surface-adsorbed *H atoms can also reduce *CO, but only through a two-step water-assisted shuttling mechanism rather than concerted transfer. Incorporating NQEs, the activation free energy of the PCET step exhibits a 30% reduction (by 0.12 eV) relative to the quantum barrier, indicating a non-negligible difference in the estimated reaction rate. This work highlights the synergistic importance of explicit solvation, constant-potential conditions, and NQEs in modeling electrochemical interfaces.
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