Deep reinforcement learning of transition states

Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach, called RL ‡ , to automatically unravel chemical reaction mechanisms. In RL ‡ , locating the transition state of a chemical reaction is formulated as a game, and two functions are op...

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Veröffentlicht in:	Physical chemistry chemical physics : PCCP 2021-03, Vol.23 (11), p.6888-6895
Hauptverfasser:	Zhang, Jun, Lei, Yao-Kun, Zhang, Zhen, Han, Xu, Li, Maodong, Yang, Lijiang, Yang, Yi Isaac, Gao, Yi Qin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Chemical reactions Computer simulation Machine learning Molecular dynamics Reaction mechanisms
Online-Zugang:	Volltext
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