  We developed an automated approach to construct the complex reaction network
and explore the reaction mechanism for several reactant molecules. The
nanoreactor type molecular dynamics was employed to generate possible chemical
reactions, in which the meta-dynamics was taken to overcome reaction barriers
and the semi-empirical GFN2-xTB method was used to reduce computational cost.
The identification of reaction events from trajectories was conducted by using
the hidden Markov model based on the evolution of the molecular connectivity.
This provided the starting points for the further transition state searches at
the more accurate electronic structure levels to obtain the reaction mechanism.
Then the whole reaction network with multiply pathways was obtained. The
feasibility and efficiency of this automated construction of the reaction
network was examined by two examples. The first reaction under study was the
HCHO + NH3 biomolecular reaction. The second example focused on the reaction
network for a multi-species system composed of dozens of HCN and H2O compounds.
The result indicated that the proposed approach was a valuable and effective
tool for the automated exploration of reaction networks.

Chemical Physics