首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Understanding Alkaline Hydrogen Oxidation Reaction on PdNiRuIrRh High-Entropy-Alloy by Machine Learning Potential
Authors:Dr Yana Men  Dean Wu  Youcheng Hu  Dr Lei Li  Dr Peng Li  Dr Shuangfeng Jia  Prof Dr Jianbo Wang  Prof Dr Gongzhen Cheng  Prof Dr Shengli Chen  Prof Dr Wei Luo
Institution:1. College of Chemistry and Molecular Sciences, Wuhan University, Wuhan, Hubei, 430072 P. R. China

These authors contributed equally to this work.;2. Core Facility of Wuhan University, Wuhan University, Wuhan, Hubei, 430072 P.R. China;3. College of Chemistry and Molecular Sciences, Wuhan University, Wuhan, Hubei, 430072 P. R. China;4. School of Physics and Technology, Center for Electron Microscopy, MOE Key Laboratory of Artificial Micro- and Nano-structures, and Institute for Advanced Studies, Wuhan University, Wuhan, Hubei, 430072 P.R. China

Abstract:High-entropy alloy (HEA) catalysts have been widely studied in electrocatalysis. However, identifying atomic structure of HEA with complex atomic arrangement is challenging, which seriously hinders the fundamental understanding of catalytic mechanism. Here, we report a HEA-PdNiRuIrRh catalyst with remarkable mass activity of 3.25 mA μg−1 for alkaline hydrogen oxidation reaction (HOR), which is 8-fold enhancement compared to that of commercial Pt/C. Through machine learning potential-based Monte Carlo simulation, we reveal that the dominant Pd−Pd−Ni/Pd−Pd−Pd bonding environments and Ni/Ru oxophilic sites on HEA surface are beneficial to the optimized adsorption/desorption of *H and enhanced *OH adsorption, contributing to the excellent HOR activity and stability. This work provides significant insights into atomic structure and catalytic mechanism for HEA and offers novel prospects for developing advanced HOR electrocatalysts.
Keywords:Atomic Structure  High-Entropy Alloys  Hydrogen Oxidation Reaction  Machine Learning  Monte Carlo Simulation
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号