論文 Efficient discovery of large magnetic anisotropy with thermodynamically stable materials via multi-objective Bayesian optimization

Kohei Nakamura ; Daigo Furuya ; Yoshio Miura SAMURAI ORCID (National Institute for Materials Science) ; Takahiro Yamazaki ; Alexandre Lira Foggiatto ; Yuma Iwasaki SAMURAI ORCID (National Institute for Materials Science) ; Masato Kotsugi

Efficient discovery of large magnetic anisotropy with thermodynamically stable materials via multi-objective Bayesian optimization.pdf
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引用
Kohei Nakamura, Daigo Furuya, Yoshio Miura, Takahiro Yamazaki, Alexandre Lira Foggiatto, Yuma Iwasaki, Masato Kotsugi. Efficient discovery of large magnetic anisotropy with thermodynamically stable materials via multi-objective Bayesian optimization. Science and Technology of Advanced Materials: Methods. 2025, 5 (1), 2485025. https://doi.org/10.1080/27660400.2025.2485025

説明:

(abstract)

This study presents an efficient magnetic material exploring method with large magnetocrystalline anisotropy (MCA) and thermodynamic stability by combining multi-objective Bayesian optimization (MBO) with first principles calculations.

権利情報:

キーワード: materials informatics

刊行年月日: 2025-12-31

出版者: Informa UK Limited

掲載誌:

  • Science and Technology of Advanced Materials: Methods (ISSN: 27660400) vol. 5 issue. 1 2485025

研究助成金:

  • Japan Science and Technology Agency JPMJCR21O1
  • Japan Society for the Promotion of Science 21H04656

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1080/27660400.2025.2485025

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更新時刻: 2025-12-12 08:30:29 +0900

MDRでの公開時刻: 2025-12-12 08:24:06 +0900

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