ReacNetwork: A method for large-scale reaction network analysis of energetic materials

The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics. While reactive molecular dynamics has been extensively employed to investigate the reaction dynamics of energetic materials, its utility is often constrained to capturing only fundamental reaction events and species information, thereby limiting mechanistic investigations of complex reaction pathways. To elucidate the topological features of energetic material reaction networks and identify critical reaction pathways with high fidelity, this study presents ReacNetwork - an advanced large-scale reaction network analysis methodology that synergistically integrates complex network theory with molecular simulation techniques. Specifically, we have developed a multi-dimensional feature screening protocol based on node centrality metrics and K-shell decomposition algorithms. Taking α-Hexahydro-1,3,5-trinitro-1,3,5-triazine (α-RDX) as the subject, we successfully constructed a comprehensive high-temperature thermal decomposition reaction network consisting of 1,134 distinct chemical species and 3,626 elementary reactions. Through systematic application of community detection algorithms and global topological feature extraction techniques, we achieved effective dimensionality reduction and successfully identified the dominant reaction pathway within the α-RDX thermal decomposition network. The computational results not only validate the well-established initial reaction mechanism dominated by N-NO₂ homolytic bond cleavage, but also provide unprecedented visualization of α-RDX framework ring-opening dynamics and subsequent radical chain propagation networks.