Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry

作者：Austin M. Mroz, Annabel R. Basford, Friedrich Hastedt, Isuru Shavindra Jayasekera, Irea Mosquera‐Lois, Ruby Sedgwick, Pedro J. Ballester, Joshua D. Bocarsly, Ehecatl Antonio del Rio‐Chanona, Matthew L. Evans, Jarvist M. Frost, Alex M. Ganose, Rebecca L. Greenaway, King Kuok Hii, Yingzhen Li, Ruth Misener, Aron Walsh, Dandan Zhang, Kim E. Jelfs · 发表于：Chemical Society Reviews · 年份：2025 · DOI：10.1039/d5cs00146c · 被引用次数：43 · 研究领域：Machine Learning in Materials Science、Computational Drug Discovery Methods

We offer ten diverse perspectives exploring the transformative potential of artificial intelligence (AI) in chemistry, highlighting many of the challenges we face, and offering potential strategies to address them.