AIが液体水素キャリアの候補を数十億個から約40個に絞り込むのに役立つ(AI helps whittle down candidates for hydrogen carriers in liquid form from billions to about 40)

ad

2024-01-10 アルゴンヌ国立研究所(ANL)

◆米エネルギー省のアーゴンヌ国立研究所の科学者たちが、AIを活用した計算研究で約1600億の有機分子の中から、将来的に車両の燃料やエネルギー源となる可能性のある約40の液体水素キャリアを特定しました。
◆これにより、水素を液体の形で輸送・貯蔵できるため、安全性やエネルギー密度の向上が期待されます。これにはAIと最新の材料特性解析の計算方法が組み合わされ、約14時間で1600億の分子をスクリーニングできるようになりました。得られた結果は、液体の水素キャリアとして有望な有機分子を特定する上での効率的な手法を提供しています。

<関連情報>

新規液体有機水素キャリアの発見:ケムインフォマティクスと量子化学的手法を用いた化合物空間の系統的探索 Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods

Hassan Harb,Sarah N. Elliott,Logan Ward,Ian T. Foster,Stephen J. Klippenstein, Larry A. Curtiss and  Rajeev Surendran Assary
Digital Discovery  Published:11 Oct 2023
DOI:https://doi.org/10.1039/D3DD00123G

Abstract

We present a comprehensive, in silico-based discovery approach to identifying novel liquid organic hydrogen carrier (LOHC) candidates using cheminformatics methods and quantum chemical calculations. We screened over 160 billion molecules from ZINC15 and GDB-17 chemical databases for structural similarity to known LOHCs and employed a data-driven selection criterion connecting molecular features with dehydrogenation enthalpy. This scoring criterion effectively predicts dehydrogenation enthalpies from SMILES strings, streamlining the LOHC screening process. After rigorous screening and down-selection, we compiled a database of 3000 dehydrogenation reactions for the most promising LOHC candidates, setting the stage for future selection based on kinetics and catalysis. This work demonstrates the significant impact of integrating quantum chemistry and cheminformatics in materials discovery, accelerating the selection process while reducing experimental efforts and time. By proposing new molecules as prospective LOHC candidates, our study provides a valuable resource for researchers and engineers in the development of advanced LOHC systems and showcases a successful approach for high-throughput discovery, contributing to more efficient and sustainable energy storage solutions.

AIが液体水素キャリアの候補を数十億個から約40個に絞り込むのに役立つ(AI helps whittle down candidates for hydrogen carriers in liquid form from billions to about 40)

0503燃料及び潤滑油
ad
ad
Follow
ad
タイトルとURLをコピーしました