Department of Physics and Materials Science, University of Luxembourg, L-1511, Luxembourg, Luxembourg.
Nat Commun. 2020 Aug 17;11(1):4125. doi: 10.1038/s41467-020-17844-8.
Discovering chemicals with desired attributes is a long and painstaking process. Curated datasets containing reliable quantum-mechanical properties for millions of molecules are becoming increasingly available. The development of novel machine learning tools to obtain chemical knowledge from these datasets has the potential to revolutionize the process of chemical discovery. Here, I comment on recent breakthroughs in this emerging field and discuss the challenges for the years to come.
发现具有理想属性的化学物质是一个漫长而艰苦的过程。包含数百万个分子可靠量子力学性质的精选数据集越来越多。开发新的机器学习工具从这些数据集中获取化学知识，有可能彻底改变化学发现的过程。在这里，我评论了这一新兴领域的最新突破，并讨论了未来几年的挑战。
