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 NH3 biomolecular reaction and the reaction
network for a multispecies system comprising dozens of HCN and H2O molecules. The results indicated that the proposed approach
provides a valuable and effective tool for the automated exploration
of the reaction networks.