Nature Communications (Sep 2020)

Retrospective on a decade of machine learning for chemical discovery

  • O. Anatole von Lilienfeld,
  • Kieron Burke

DOI
https://doi.org/10.1038/s41467-020-18556-9
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 4

Abstract

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Standfirst Over the last decade, we have witnessed the emergence of ever more machine learning applications in all aspects of the chemical sciences. Here, we highlight specific achievements of machine learning models in the field of computational chemistry by considering selected studies of electronic structure, interatomic potentials, and chemical compound space in chronological order.