Automated Exploration of Reaction Networks and Mechanisms Based on Metadynamics Nanoreactor Simulations.

We developed an automated approach to construct a complex reaction network and explore the reaction mechanisms for numerous reactant molecules by integrating several theoretical approaches. Nanoreactor-type molecular dynamics was used to generate possible chemical reactions, in which the metadynamics was used to overcome the reaction barriers, and the semiempirical GFN2-xTB method was used to reduce the computational cost. Reaction events were identified from trajectories using the hidden Markov model based on the evolution of the molecular connectivity. This provided the starting points for further transition-state searches at the electronic structure levels of density functional theory to obtain the reaction mechanism. Finally, the entire reaction network containing multiple pathways was built. The feasibility and efficiency of the automated construction of the reaction network were investigated using the HCHO and NH biomolecular reaction and the reaction network for a multispecies system comprising dozens of HCN and HO molecules. The results indicated that the proposed approach provides a valuable and effective tool for the automated exploration of the reaction networks.