Determining the mechanical and decomposition properties of high energetic materials (α-RDX, β-HMX, and ε-CL-20) using a neural network potential

Molecular simulations of high energetic materials (HEMs) are limited by efficiency and accuracy. Recently, neural network potential (NNP) models have achieved molecular simulations of millions of atoms while maintaining the accuracy of density functional theory (DFT) levels. Herein, an NNP model covering typical HEMs containing C, H, N, and O elements is developed. The mechanical and decomposition properties of 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), hexahydro-1,3,5-trinitro-1,3,5-triazine (HMX), and 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20) are determined by employing the molecular dynamics (MD) simulations based on the NNP model. The calculated results show that the mechanical properties of α-RDX, β-HMX, and ε-CL-20 agree with previous experiments and theoretical results, including cell parameters, equations of state, and elastic constants. In the thermal decomposition simulations, it is also found that the initial decomposition reactions of the three crystals are N-NO2 homolysis, corresponding radical intermediates formation, and NO2-induced reactions. This decomposition trajectory is mainly divided into two stages separating from the peak of NO2: pyrolysis and oxidation. Overall, the NNP model for C/H/N/O elements in this work is an alternative reactive force field for RDX, HMX, and CL-20 HEMs, and it opens up new potential for future kinetic study of nitramine explosives.

Insight into melting point differences of dinitroimidazoles and dinitropyrazoles from the perspective of intermolecular interactions

Dinitroimidazole (DNI) and dinitropyrazole (DNP), along with their congeners, possess similar molecular structures but exhibit distinct melting points. To analyse and elucidate the fundamental reasons for property differences from the perspective of intermolecular interactions, we proposed a simplified approach named binding energy in clusters (BEC) in computing weak interactions within complex crystal systems. Based on the results of the symmetry-adapted perturbation theory (SAPT) calculations, an approximate estimation of the melting point range can be derived by taking into account the cumulative effect (energy of electrostatic, dispersion and induction terms) and repulsive effect (energy of exchange term) values. We have also proposed a formula for calculating the specific melting point, which indicates that stronger intermolecular interactions have a major impact on the melting point, while the distribution of weak interactions also affects the melting point. This work would provide an effective reference for molecular design and structure-performance analysis.

Revealing the thermal decomposition mechanism of RDX crystals by a neural network potential

A neural network potential (NNP) is developed to investigate the complex reaction dynamics of 1,3,5-trinitro-1,3,5-triazine (RDX) thermal decomposition.