Tetrazole Decomposition Temperature Prediction from Conformational Searches: Motivated by our initial success in identifying QSPR models for the decomposition temperature of structurally diverse tetrazole HEMs using descriptor sets constructed from crystallographic data, we sought to extend our methods to accommodate ab initio virtual screening of HEMs. Our reliance on crystal structure data would necessitate time-consuming and potentially hazardous laboratory work to test model predictions. To this end, we developed a second workflow for QSPR modeling of tetrazole sensitivity properties wherein 2D structural formulae were converted into 3D conformers using molecular mechanics with MacroModel version 11.8. All conformers within a 5.0 kcal/mol energy difference of the lowest energy conformer were subjected to the same DFT optimizations and single point calculations for parameter acquisition as described in the original workflow. With multiple conformations for each compound in hand, we generated two descriptor datasets for statistical applications: 1) the minimum energy conformer of each HEM according to DFT calculations and 2) Boltzmann averaging of descriptor values across all conformations.