Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
Author(s)
Tu, Zhengkai; Stuyver, Thijs; Coley, Connor W
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The field of predictive chemistry relates to the development of models able to describe how molecules
interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far
more reaching and ambitious in its goals. In this review, we summarize several areas where predictive
chemistry models hold the potential to accelerate the deployment, development, and discovery of
organic reactions and advance synthetic chemistry.
Date issued
2023-01-04Department
Massachusetts Institute of Technology. Department of Chemical EngineeringJournal
Chemical Science
Publisher
Royal Society of Chemistry (RSC)
Citation
Tu, Zhengkai, Stuyver, Thijs and Coley, Connor W. 2023. "Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery." Chemical Science, 14 (2).
Version: Final published version