Deep Potential Molecular Dynamics Study of Chapman-Jouguet Detonation Events of Energetic Materials

Detonation of energetic materials (EMs) is of great importance for military applications, while the understanding of detailed events and mechanisms for the detonation process is scarce. In this study, the first deep neural network potential NNP_Shock for molecular dynamics (MD) simulation of shock-induced detonation of EMs was generated based on a deep potential model, providing DFT accuracy but 10⁶ times the computational efficiency. On this basis, we employ our deep potential to perform MD simulations of shock-induced detonation of high-performance EM material 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20, C₆H₆N₁₂O₁₂) and obtain the theoretical Chapman-Jouguet (C-J) detonation velocities and pressures directly by multiscale shock technique (MSST) for the first time, which are in good agreement with experiment. In addition, the Hugoniot curves and initial reaction mechanisms were successfully obtained. Therefore, the NNP_Shock potential is competent in research of the detonation performance and shock sensitivity of CL-20, and the method can also be transplanted to studies of other EMs.