A Physical Organic Approach towards Statistical Modeling of Tetrazole and Azide Decomposition. (17th March 2023) - Rein, Jonas; Meinhardt, Jonathan M.; Hofstra Wahlman, Julie L.; Sigman, Matthew S.; Lin, Song
Abstract: Nitrogen atom‐rich heterocycles and organic azides have found extensive use in many sectors of modern chemistry from drug discovery to energetic materials. The prediction and understanding of their energetic properties are thus key to the safe and effective application of these compounds. In this work, we disclose the use of multivariate linear regression modeling for the prediction of the decomposition temperature and impact sensitivity of structurally diverse tetrazoles and organic azides. We report a data‐driven approach for property prediction featuring a collection of quantum mechanical parameters and computational workflows. The statistical models reported herein carry predictive accuracy as well as chemical interpretability. Model validation was successfully accomplished via tetrazole test sets with parameters generated exclusively in silico. Mechanistic analysis of the statistical models indicated distinct divergent pathways of thermal and impact‐initiated decomposition. Abstract : Tetrazoles and azides find broad application in pharmaceuticals, chemical biology, and high‐energy materials. In this work multivariant linear regression and classification are leveraged to develop predictive statistical models for their decomposition temperature and impact sensitivity, which are key in evaluating the safety of a given molecule. Furthermore, interpretation of the statistical models provided rich insight into the decomposition mechanisms.