Machine learning-based q-RASPR predictions of detonation heat for nitrogen-containing compounds
Shubham Kumar Pandey, Arkaprava Banerjee, Kunal Roy
Abstract
The study aims to predict the detonation heat of different classes of nitrogen-containing compounds by utilizing various in silico approaches such as QSPR, Read-across, q-RASPR, and ML.
Topics & Concepts
DetonationIn silicoNitrogenQuantitative structure–activity relationshipChemistryThermodynamicsComputer scienceMachine learningOrganic chemistryBiochemistryPhysicsExplosive materialGeneThermal and Kinetic AnalysisComputational Drug Discovery MethodsMachine Learning in Materials Science