機械学習によるサクリフィシャル・水素進化のための三次有機ヘテロジャンクション光触媒の加速探索

Haofan Yang¹, Yu Che¹, Andrew I Cooper¹

¹Leverhulme Research Centre for Functional Materials Design, Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L7 3NY, U.K.

Journal of the American Chemical Society

|December 1, 2023

まとめ

研究者は,機械学習と高通量スクリーニングを使用して,三元有機ヘテロ結合光触媒 (TOHP) の発見を加速しました. オーガニック光触媒の性能を大幅に向上させました

科学分野:

材料科学
光触媒
再生可能エネルギー

背景:

ドナー-受容体のヘテロ結合を持つ有機光触媒は,電荷分離を強化し,活性性を向上させます.
最適な三元有機ヘテロ結合光触媒 (TOHP) の設計は,膨大な材料の組み合わせのために困難です.

研究の目的:

高効率のTOHPの発見と設計を加速する.
優れた光触媒性水素生成率を持つ新しいTOHPを特定する.

主な方法:

機械学習と実験的なスクリーニングを組み合わせたものです
可能な 4320 のうち 736 の三元組合せを評価した.
有機物質内のドナー-受容体のヘテロ結合に焦点を当てた.

主要な成果:

犠牲用水素生成において500 mmol g^-1 h^-1を超える10の高活性TOHPを特定した.
最高性能のTOHPは,1日の照明下で749.8 mmol g−1 h−1の速度を達成した.
三次相空間を探索する際の重要な加速を証明した.

結論:

機械学習と高通量スクリーニングは,高度なTOHPの発見を効果的に加速します.
開発されたTOHPは,有機光触媒の最も高い水素生成率を示しています.
このアプローチは次世代の光触媒材料の設計に有力な戦略を提供します

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