ReacNetGen: an Automatic Reaction Network Generator for Reactive Molecular Dynamic Simulations

The reactive molecular dynamics is widely used in the field of computational chemistry to study the reaction mechanisms in molecular systems. However, complex trajectories that are difficult to analyze have become a major obstacle to its application in large-scale systems. In this work, a new approach named ReacNetGen is developed to obtain reaction networks based on reactive MD simulations. Molecular species can be automatically generated from the 3D coordinates of atoms in the trajectory. The hidden Markov model is used to filter the noises in the trajectory, which makes the analysis process easier and more accurate. Compared with manual analysis, the advantage of this method in terms of efficiency is very obvious for large-scale simulation trajectories. It has been successfully used in the analysis of the simulated oxidation of 4-component RP-3 and methane.