Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning
Computational modelling of chemical systems requires a balance between accuracy and computational cost. Here the authors use transfer learning to develop a general purpose neural network potential that approaches quantum-chemical accuracy for reaction thermochemistry, isomerization, and drug-like mo...
Main Authors: | Justin S. Smith, Benjamin T. Nebgen, Roman Zubatyuk, Nicholas Lubbers, Christian Devereux, Kipton Barros, Sergei Tretiak, Olexandr Isayev, Adrian E. Roitberg |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2019-07-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-019-10827-4 |
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