Revealing the role of double-layer microenvironments in pH-dependent oxygen reduction activity over metal-nitrogen-carbon catalysts

被引:106
作者
Li, Peng [1 ]
Jiao, Yuzhou [1 ]
Ruan, Yaner [2 ]
Fei, Houguo [1 ]
Men, Yana [1 ]
Guo, Cunlan [1 ]
Wu, Yuen [2 ]
Chen, Shengli [1 ]
机构
[1] Wuhan Univ, Coll Chem & Mol Sci, Hubei Key Lab Electrochem Power Sources, Wuhan 430072, Hubei, Peoples R China
[2] Univ Sci & Technol China, Sch Chem & Mat Sci, Collaborat Innovat Ctr Chem Energy Mat iChEM, Hefei 230026, Anhui, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
WATER; ELECTROCATALYSTS; PROTONATION; INTERFACE; INSIGHT; DESIGN; FE/N/C;
D O I
10.1038/s41467-023-42749-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
A standing puzzle in electrochemistry is that why the metal-nitrogen-carbon catalysts generally exhibit dramatic activity drop for oxygen reduction when traversing from alkaline to acid. Here, taking FeCo-N6-C double-atom catalyst as a model system and combining the ab initio molecular dynamics simulation and in situ surface-enhanced infrared absorption spectroscopy, we show that it is the significantly distinct interfacial double-layer structures, rather than the energetics of multiple reaction steps, that cause the pH-dependent oxygen reduction activity on metal-nitrogen-carbon catalysts. Specifically, the greatly disparate charge densities on electrode surfaces render different orientations of interfacial water under alkaline and acid oxygen reduction conditions, thereby affecting the formation of hydrogen bonds between the surface oxygenated intermediates and the interfacial water molecules, eventually controlling the kinetics of the proton-coupled electron transfer steps. The present findings may open new and feasible avenues for the design of advanced metal-nitrogen-carbon catalysts for proton exchange membrane fuel cells. By combining theoretical simulations and spectroscopic measurements, Peng Li et al. demonstrated that distinct interfacial double-layer structures play a key role in the pH-dependent oxygen reduction kinetics over metal-nitrogen-carbon catalysts.
引用
收藏
页数:12
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共 58 条
[1]   Building better batteries [J].
Armand, M. ;
Tarascon, J. -M. .
NATURE, 2008, 451 (7179) :652-657
[2]   PROJECTOR AUGMENTED-WAVE METHOD [J].
BLOCHL, PE .
PHYSICAL REVIEW B, 1994, 50 (24) :17953-17979
[3]   Electrochemical Barriers Made Simple [J].
Chan, Karen ;
Norskov, Jens K. .
JOURNAL OF PHYSICAL CHEMISTRY LETTERS, 2015, 6 (14) :2663-2668
[4]   Potential Dependence of Electrochemical Barriers from ab Initio Calculations [J].
Chant, Karen ;
Norskov, Jens K. .
JOURNAL OF PHYSICAL CHEMISTRY LETTERS, 2016, 7 (09) :1686-1690
[5]   Active and Stable Liquid Water Innovatively Prepared Using Resonantly Illuminated Gold Nanoparticles [J].
Chen, Hsiao-Chien ;
Hwang, Bing-Joe ;
Mai, Fu-Der ;
Liu, Yu-Chuan ;
Lin, Chun-Mao ;
Kuo, Hsien-Shou ;
Chou, Duen-Suey ;
Lee, Ming-Jer ;
Yang, Kuang-Hsuan ;
Yu, Chung-Chin ;
Chen, Jiun-Rong ;
Lo, Tsui-Yun ;
Tsai, Hui-Yen ;
Yang, Chih-Ping ;
Wang, Chi ;
Hsieh, Hsiao-Ting ;
Rick, John .
ACS NANO, 2014, 8 (03) :2704-2713
[6]   Pseudo-adsorption and long-range redox coupling during oxygen reduction reaction on single atom electrocatalyst [J].
Chen, Jie-Wei ;
Zhang, Zisheng ;
Yan, Hui-Min ;
Xia, Guang-Jie ;
Cao, Hao ;
Wang, Yang-Gang .
NATURE COMMUNICATIONS, 2022, 13 (01)
[7]   Electrocatalytic volcano relations: surface occupation effects and rational kinetic models [J].
Chen, Yongting ;
Chen, Junxiang ;
Chen, Shengli .
CHINESE JOURNAL OF CATALYSIS, 2022, 43 (01) :2-10
[8]   Explanation of Dramatic pH-Dependence of Hydrogen Binding on Noble Metal Electrode: Greatly Weakened Water Adsorption at High pH [J].
Cheng, Tao ;
Wang, Lu ;
Merinov, Boris, V ;
Goddard, William A., III .
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2018, 140 (25) :7787-7790
[9]   Theoretical Resolution of the Exceptional Oxygen Reduction Activity of Au(100) in Alkaline Media [J].
Duan, Zhiyao ;
Henkelman, Graeme .
ACS CATALYSIS, 2019, 9 (06) :5567-5573
[10]   Molecular insight into the GaP(110)-water interface using machine learning accelerated molecular dynamics [J].
Fan, Xue-Ting ;
Wen, Xiao-Jian ;
Zhuang, Yong-Bin ;
Cheng, Jun .
JOURNAL OF ENERGY CHEMISTRY, 2023, 82 :239-247