Predicting the performance and stability parameters of energetic materials (EMs) using a machine learning-based q-RASPR approach

Abstract

The performance and stability are the two major areas of concern related to energetic materials (EMs). Balancing both the performance and stability simultaneously can result in the development of new advanced compounds that will not only perform better but at the same time be highly stable to physical/chemical/thermal stress. In this study, we aimed to predict some of the properties related to detonation performance (density, n = 12 805; gas-phase heat of formation, n = 2565) and thermal stability (decomposition temperature, n = 656; melting point, n = 19 667) of EMs using the quantitative Read-Across Structure–Property Relationship (q-RASPR) approach. q-RASPR, a combined application of quantitative structure–property relationship (QSPR) and RA methodologies, has shown an enhancement in the model predictivity, compared to the traditional QSPR method. The data sets collected from various sources were first curated to prepare high-quality data. After the structural representation of the data points and descriptor calculation, each data set was divided into the respective training and test sets. Different methodologies were employed to train the model, and the models so developed were validated based on the Organization for Economic Cooperation and Development (OECD) principles. Also, the developed models’ predictivity was checked using different ML algorithms. All the developed models showed good statistical quality with R² values (training set) ranging from 0.64 for decomposition temperature and 0.75 for the melting point to 0.94 for density and heat of formation data sets. Also, the external validation results were quite promising, which indicates that the predictive power of our developed models was significant. The models so developed can be used for examining the performance and heat resistance capacity of the newly developed compounds, screening of databases, modification of older derivatives, and/or the development of heat-resistant (non-thermo-labile) and impactful EMs.