Synergizing Experimentation and Computation: Predicting Energetic Potential in New Cyclo-Peroxide Compounds.

Abstract

This manuscript explores the synthesis of new cyclo-peroxide compounds (CPs) through a systematic approach involving 10 different ketones and two concentrations of H2O2. Following spectroscopic analysis and calorimetric tests on 10 selected compounds, the percentage of Power Index (%PI) was calculated. The study introduces a computational methodology based on the Iterative Stochastic Elimination (ISE) algorithm. The newly constructed ISE model, with demonstrated robust predictive capabilities indicated by its statistical parameters, was employed to screen and score the CPs, assessing their potential as energetic materials. Comparison between %PI obtained experimentally, and the ISE index derived computationally revealed consistent assessments of the new CPs' energetic potential. The research emphasizes that, particularly in the synthesis of cyclic peroxides, the ISE model is a preferable and efficient tool for predicting a compound's potential as an energetic substance. Utilizing the ISE model ensures faster, more cost-effective, and safer decision-making in experimental examinations, focusing attention only on compounds with the highest ISE scores. Furthermore, the manuscript suggests an intriguing avenue for future research by proposing the investigation of ester nitrates. The study advocates a comprehensive approach that combines experimental methods (synthesis, spectroscopy, and DSC) with computational evaluation using the ISE model to identify potential high-energy compounds. This integrated approach promises to enhance the efficiency and reliability of the energetic materials discovery process.