Fast explosive performance prediction via small-dose energetic materials based on time-resolved imaging combined with machine learning

Fast, reproducible, and quantitative performance evaluation of monomolecular energetic materials (EMs) is a significant challenge that limits the tailored applications of EMs and the development of new high-energy-density materials.