In this paper, we develop a neural network-based molecular dynamics (NNMD) method for investigation into the reaction dynamics of a novel high explosive (ICM-102) . The training dataset is derived from both AIMD and VRMD simulations. The configuration spaces of datasets from different sampling methods are compared to yield a good NN potential. A set of MD simulations is performed to explore the elementary reactions in the decomposition of ICM-102 molecules. A panoramic visualization of the complex reaction networks is abstracted, and new pathways are identified from atomic trajectories for the first time.