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機械学習アルゴリズムを用いた自己組み立て光触媒CO2の多変数多メトリック最適化

Shannon A Bonke1, Giovanni Trezza2, Luca Bergamasco2

  • 1Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom.

Journal of the American Chemical Society
|May 20, 2024
PubMed
まとめ

この研究は,二酸化炭素の削減効率を向上させ,光触媒システムを最適化するための機械学習アプローチを導入します. 新しい方法は従来の方法とは異なり,複数のパフォーマンスメトリックを同時に総合的に改善します.

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