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Cyclopropyl-ML-20210208.pdf (946.66 kB)

Machine Learning Classification of Disrotatory IRC and Conrotatory Non-IRC Trajectory Motion for Cyclopropyl Radical Ring Opening

preprint
submitted on 08.02.2021, 17:27 and posted on 09.02.2021, 13:19 by Steven Maley, Jesse Melville, Spencer Yu, Cal Hargis, Reid Hamilton, Benjamin Grant, Matthew Teynor, Daniel Ess
Transition-state features from trajectories were used for supervised machine learning analysis of the cyclopropyl radical ring opening reaction. Quantitative and qualitative assessment of features controlling disrotatory IRC versus conrotatory non-IRC motion and revealed that there are two key vibrational modes where their directional combination provides prediction of pathway motion.

Funding

NSF CSDM-B (CHE 1952420)

History

Email Address of Submitting Author

dhe@chem.byu.edu

Institution

Brigham Young University

Country

USA

ORCID For Submitting Author

0000-0001-5689-9762

Declaration of Conflict of Interest

No conflict of interest

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