Deep learning morphological distribution analysis of metal alloy catalysts in proton exchange membrane fuel cells-Reference-Cited by-同舟云学术

Deep learning morphological distribution analysis of metal alloy catalysts in proton exchange membrane fuel cells

Published:2023-08 Issue: Volume:36 Page:101348
ISSN:2468-6069
Container-title:Materials Today Energy
language:en
Short-container-title:Materials Today Energy

Author:

Yang Sang-Hyeok,Park Eun-Byeol,Cho Sung Yong,Kang Yun Sik,Ju Hyeon-Ah,Jeon Yerin,Yang Daehee,Yim Sung-Dae,Lee Sungchul,Kim Young-Min^ORCID

Funder

Ministry of Trade, Industry and Energy

Ministry of Science, ICT and Future Planning

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Materials Science (miscellaneous),Renewable Energy, Sustainability and the Environment

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4. Proton exchange membranes for high temperature proton exchange membrane fuel cells: challenges and perspectives;Qu;J. Power Sources,2022

5. Review of characterization and modeling of polymer electrolyte fuel cell catalyst layer: the blessing and curse of ionomer;Huang;Front. Energy,2017

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