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Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
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モレキュラーライブラリのCr前端のXANESから軌道分析と監督された機械学習によるフィリップス触媒の解読

David Trummer1, Keith Searles1, Alexander Algasov2,3

  • 1Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, CH-8093 Zürich, Switzerland.

Journal of the American Chemical Society
|May 11, 2021
PubMed
まとめ

この研究では,機械学習とカスタマイズされたクロム (Cr) 分子複合体を用いて,触媒の表面部位を分析する新しい方法を開発しました. フィリップス触媒のクロム酸化状態と局所環境を正確に予測する.

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