Wang Yuhang, Zhang Di, Sun Bin, Jia Xue, Zhang Linda, Cheng Hefeng, Fan Jun, Li Hao
Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, Sendai, 980-8577, Japan.
Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong, 999077, China.
Angew Chem Int Ed Engl. 2025 Feb 17;64(8):e202418228. doi: 10.1002/anie.202418228. Epub 2024 Dec 17.
Tin (Sn)-based catalysts have been widely studied for electrochemical CO reduction reaction (CORR) to produce formic acid, but the intricate influence of the structural sensitivity in single-atom Sn (e.g., Sn-N-C) and polyatomic Sn (e.g., SnO and SnS; x=1,2) on their pH-dependent performance remains enigmatic. Herein, we integrate large-scale data mining (with >2,300 CORR catalysts from available experimental literature during the past decade), ab initio computations, machine learning force field accelerated molecular dynamic simulations, and pH-field coupled modelling to unravel their pH dependence. We reveal a fascinating contrast: the electric field response of the binding strength of *OCHO on Sn-N-C and polyatomic Sn exhibits opposite behaviors due to their differing dipole moment changes upon *OCHO formation. Such response leads to an intriguing opposite pH-dependent volcano evolution for Sn-N-C and polyatomic Sn. Subsequent experimental validations of turnover frequency and current density under both neutral and alkaline conditions well aligned with our theoretical predictions. Most importantly, our analysis suggests the necessity of distinct optimization strategies for *OCHO binding energy on different types of Sn-based catalysts.
基于锡(Sn)的催化剂已被广泛研究用于电化学二氧化碳还原反应(CORR)以生产甲酸,但单原子锡(如Sn-N-C)和多原子锡(如SnO和SnS;x = 1,2)的结构敏感性对其pH依赖性性能的复杂影响仍然不明。在此,我们整合大规模数据挖掘(利用过去十年现有实验文献中的>2300种CORR催化剂)、从头算计算、机器学习力场加速分子动力学模拟和pH场耦合建模来揭示它们的pH依赖性。我们揭示了一个引人入胜的对比:由于*OCHO形成时偶极矩变化不同,OCHO在Sn-N-C和多原子锡上的结合强度电场响应呈现相反行为。这种响应导致Sn-N-C和多原子锡出现有趣的相反pH依赖性火山型演化。随后在中性和碱性条件下对周转频率和电流密度的实验验证与我们的理论预测高度吻合。最重要的是,我们的分析表明针对不同类型的Sn基催化剂上OCHO结合能需要不同的优化策略。