Models for predicting impact sensitivity of energetic materials based on the trigger linkage hypothesis and Arrhenius kinetics

Abstract

In order to predict the impact sensitivity of high explosives, we designed and evaluated several models based on the trigger linkage hypothesis and the Arrhenius equation. To this effect, we calculated the heat of detonation, temperature of detonation, and bond dissociation energy for 70 energetic molecules. The bond dissociation energy divided by the temperature of detonation proved to be a good predictor of the impact sensitivity of nitroaromatics, with a coefficient of determination (R2) of 0.81. A separate Bayesian analysis gave similar results, taking model complexity into account. For nitramines, there was no relationship between the impact sensitivity and the bond dissociation energy. None of the models studied gave good predictions for the impact sensitivity of liquid nitrate esters. For solid nitrate esters, the bond dissociation energy divided by the temperature of detonation showed promising results (R2 = 0.85), but since this regression was based on only a few data points, it was discredited when model complexity was accounted for by our Bayesian analysis. Since the temperature of detonation correlated with the impact sensitivity for nitroaromatics, nitramines, and nitrate esters, we consider it to be one of the leading predictive factors of impact sensitivity for energetic materials.

Unimolecular Decomposition Reactions of Picric Acid and Its Methylated Derivatives─A DFT Study

“…While the impact sensitivity depends on molecular properties related to the kinetics and thermodynamics of the decomposition reactions, solid-state properties such as particle size, polymorphism, crystal defects, and crystal orientation also play important roles. 13 Defects are particularly important since they may form so-called hot spots under fast compression of the material. Although the initiation of an energetic material is a complex, multiscale process, 1 , 9 , 18 , 19 one may roughly divide it into two main steps.…”

“…This hypothesis states that the first step of the initiation is a bond cleavage and that the decomposition is triggered by the homolytic fission of an X–NO 2 bond, where X is C, N, or O. 13 , 42 Hydrogen transfer reactions may be arranged into different categories based on the origin of the transferred hydrogen atom.…”

An Explosophore-Based Approach Towards the Prediction of Energetic Material Sensitivity Properties

“…As a next step, we sought to validate our tetrazole models using the trigger hypothesis, which states that the bulk decomposition of an energetic material is dominated by the initial decomposition of the explosophore with the lowest activation energy prior to the initiation of an exothermic chain reaction. 43 We explored this idea in the context of the ditetrazole HEMs in our dataset: in cases where an HEM contained two non-identical tetrazole units, we hypothesized that the molecule's bulk Tdec would be closely related to the lower predicted Tdec of either of the two tetrazole explosophores. As such, we used our statistical model for Tdec (Figure 5A) to generate predictions for an external test set of 12 non-symmetric ditetrazoles and selected the lower of the two predicted values as the predicted Tdec for the HEM.…”

A property-oriented adaptive design framework for rapid discovery of energetic molecules based on small-scale labeled datasets

“…Thus, some ML-based works were utilized to quickly predict some properties of energetic materials, such as decomposition temperature, 14 melting point, 15 autoignition temperature, 16 sensitivity and density. 17,18 However, as mentioned above, the labeled data of the energetic compounds are very limited. Consequently, the applications of ML in the energetic materials generally suffer from prediction uncertainties when extrapolated to unknown chemical space.…”