Chemical determinants of drop-weight impact sensitivity in high explosives

A common experiment to evaluate handling sensitivity of high explosives is the drop-weight impact test. Although this test is known to be noisy, it is one of the most common tests used to evaluate handling sensitivity. In this paper, we compile the largest known data set of drop-weight impact sensitivity test results (mainly performed at Los Alamos National Laboratory), along with a compendium of molecular and chemical properties for the explosives under test. These data consist of over 1,000 unique explosives and over 100 properties. We use random forest methods to estimate a model of explosive handling sensitivity as a function of chemical and molecular properties of the explosives under test. Our model predicts well across a wide range of explosive types, spanning a broad range of explosive performance and sensitivity. We find that properties related to explosive performance, such as heat of explosion, oxygen balance, and functional group, are highly predictive of explosive handling sensitivity. Yet, models that omit some of these properties still perform well. Our results suggest that there is not one, or even several, factors that explain explosive handling sensitivity, but that there are many complex, interrelated effects at play.