High entropy alloy electrocatalysts

被引:7
|
作者
Gao, Guoliang [1 ]
Yu, Yangyang [1 ]
Zhu, Guang [1 ]
Sun, Bowen [2 ]
He, Ren [3 ,4 ]
Cabot, Andreu [3 ,5 ]
Sun, Zixu [2 ]
机构
[1] Suzhou Univ, Anhui Higher Educ Inst, Key Lab Spin Electron & Nanomat, Suzhou 234000, Anhui, Peoples R China
[2] Henan Univ, Sch Mat Sci & Engn, Key Lab Special Funct Mat, Minist Educ, Kaifeng 475004, Peoples R China
[3] Catalonia Inst Energy Res IREC St Adria de Besos, Barcelona 08930, Spain
[4] Univ Barcelona, Dept Engn Elect & Biomed, Barcelona 08028, Spain
[5] Catalan Inst Res & Adv Studies ICREA, Pg Lluis Companys 23, Barcelona 08010, Spain
来源
基金
中国国家自然科学基金;
关键词
High entropy alloys; Electrocatalysis; Synthesis strategies; Energy conversion reactions; CORROSION BEHAVIOR; GENERAL-SYNTHESIS; OXYGEN EVOLUTION; NANOPARTICLES; EFFICIENT; METAL; CARBON; PERFORMANCE; DESIGN; STRATEGIES;
D O I
10.1016/j.jechem.2024.07.049
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Compared to traditional pure metals or alloys based on just one principal element, high entropy alloys (HEAs) exhibit notable structural and physical characteristics, drawing significant attention. While significant advancements have been made in the synthesis and utilization of HEAs, there is a lack of comprehensive understanding and systematic approach towards the rational design of electrocatalysts. This review begins by introducing the fundamental principles and impacts of HEAs, followed by an overview of traditional and emerging synthesis techniques; in particular, we categorize and critically analyze approaches. Subsequently, a detailed examination of the advancements and comparative performance of HEAs in specific electrocatalytic reactions is presented. The paper concludes by outlining the current challenges and opportunities associated with HEAs catalysts, along with offering personal insights on potential future developments. (c) 2024 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:335 / 364
页数:30
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