ジャーナル論文 Accelerated Electrocatalyst Degradation Testing by Accurate and Robust Forecasting of Multidimensional Kinetic Model with Bayesian Data-Assimilation
Miao Wang (author) (この著者で検索)
ORCID https://orcid.org/0000-0001-9483-6877
National Institute for Materials Science Research Center for Energy and Environmental Materials (GREEN)/Hydrogen Technology Materials Field/Electrochemical Energy Conversion Team
SAMURAI NIMS Researchers Directory SAMURAI
ORCID SAMURAI ;
Akimitsu Ishii (author) (この著者で検索)
ORCID https://orcid.org/0000-0002-9261-4047
National Institute for Materials Science International Center for Young Scientists
SAMURAI NIMS Researchers Directory SAMURAI
ORCID SAMURAI ;
Ken Sakaushi (author) (この著者で検索)
ORCID https://orcid.org/0000-0003-4797-9087
National Institute for Materials Science Research Center for Energy and Environmental Materials (GREEN)/Hydrogen Technology Materials Field/Electrochemical Energy Conversion Team
SAMURAI NIMS Researchers Directory SAMURAI
ORCID SAMURAI
コレクション

引用
Miao Wang, Akimitsu Ishii, Ken Sakaushi. Accelerated Electrocatalyst Degradation Testing by Accurate and Robust Forecasting of Multidimensional Kinetic Model with Bayesian Data-Assimilation. ACS Energy Letters. 2025, 10 (), 22-29. https://doi.org/10.1021/acsenergylett.4c02868

説明:

(abstract)

Degradation test represents a significant bottleneck in the electrochemical technology development, requiring occasionally tens of thousands of hours. Thus, a reliable degradation forecasting in short timeframe is a game-changer in accelerating the establishment of future electrochemical devices. Herein, we show a multidimensional kinetic model for electrocatalyst degradation by quantifying the relationship among potential, current, and time, applicable under various conditions.

権利情報:

キーワード: Bayesian Data Assimilation, Electrocatalysts, Kinetic Model

刊行年月日: 2025-01-10

出版者: American Chemical Society

掲載誌:

  • ACS Energy Letters (ISSN: 23808195) vol. 10 p. 22-29

研究助成金:

  • 文部科学省 JPMXP1122712807

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1021/acsenergylett.4c02868

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更新時刻: 2024-12-10 16:56:51 +0900

MDRでの公開時刻: 2025-02-17 18:32:17 +0900

ファイル名 サイズ
ファイル名 wang-et-al-2024-accelerated-electrocatalyst-degradation-testing-by-accurate-and-robust-forecasting-of-multidimensional.pdf
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サイズ 2.23MB 詳細
ファイル名 nz4c02868_si_001.pdf (サムネイル)
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サイズ 1.59MB 詳細