期刊
NATURE COMMUNICATIONS
卷 11, 期 1, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/s41467-020-17844-8
关键词
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资金
- European Research Council (ERC-CoG grant BeStMo)
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.
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