Chemical Descriptors for a Large-Scale Study on Drop-Weight Impact Sensitivity of High Explosives.

The drop-weight impact test is an experiment that has been used for nearly 80 years to evaluate handling sensitivity of high explosives. Although the results of this test are known to have large statistical uncertainties, it is one of the most common tests due to its accessibility and modest material requirements. In this paper, we compile a large data set of drop-weight impact sensitivity test results (mainly performed at Los Alamos National Laboratory), along with a compendium of molecular and chemical descriptors for the explosives under test. These data consist of over 500 unique explosives, over 1000 repeat tests, and over 100 descriptors, for a total of about 1500 observations. 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 many 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.

Understanding Explosive Sensitivity with Effective Trigger Linkage Kinetics.

We present a simple linear model for ranking the drop weight impact sensitivity of organic explosives that is based explicitly on chemical kinetics. The model is parameterized to specific heats of explosion, Q, and Arrhenius kinetics for the onset of chemical reactions that are obtained from gas-phase Born-Oppenheimer molecular dynamics simulations for a chemically diverse set of 24 molecules. Reactive molecular dynamics simulations sample all possible decomposition pathways of the molecules with the appropriate probabilities to provide an effective reaction barrier. In addition, the calculations of effective trigger linkage kinetics can be accomplished without prior physical intuition of the most likely decomposition pathways. We found that the specific heat of explosion tends to reduce the effective barrier for decomposition in accordance with the Bell-Evans-Polanyi principle, which accounts naturally for the well-known correlations between explosive performance and sensitivity. Our model indicates that sensitive explosives derive their properties from a combination of weak trigger linkages that react at relatively low temperatures and large specific heats of explosion that further reduce the effective activation energy.

Latent influence networks in global environmental politics.

International environmental treaties are the key means by which states overcome collective action problems and make specific commitments to address environmental issues. However, systematically assessing states' influence in promoting global environmental protection has proven difficult. Analyzing newly compiled data with a purpose-built statistical model, we provide a novel measurement of state influence within the scope of environmental politics and find strong influences among states and treaties. Specifically, we report evidence that states are less likely to ratify when states within their region ratify, and results suggesting that countries positively influence other countries at similar levels of economic development. By examining several prominent treaties, we illustrate the complex nature of influence: a single act of ratification can dramatically reshape global environmental politics. More generally, our findings and approach provide an innovative means to understand the evolution and complexity of international environmental protection.