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

09 February 2021, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


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.


Machine Learning
Quasiclassical dynamics
Quasiclassical trajectories
Density functional theory
cyclopropyl radical
Post-transition state bifurcation


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