Generating transition states of isomerization reactions with deep learning

Lack of quality data and difficulty generating these data hinder quantitative understanding of reaction kinetics. Specifically, conventional methods to generate transition state structures are deficient in speed, accuracy, or scope. We describe a novel method to generate three-dimensional transition...

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Bibliographic Details
Main Authors: Pattanaik, Lagnajit (Author), Ingraham, John (Author), Grambow, Colin A. (Author), Green Jr, William H (Author)
Other Authors: Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor), Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor)
Format: Article
Language:English
Published: Royal Society of Chemistry (RSC), 2020-11-19T18:41:55Z.
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