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About this paper
Mingjie Wen, Jiahe Han, Zihan Zhou, Hao Wang, Xueyong Guo, Qingzhao Chu, Dongping Chen
The authors compare thermolysis and shock decomposition across 10 energetic materials using the same reactive machine-learning potential. They align trajectories by normalized reaction progress and measure overlap between species-abundance distributions, alongside local structures. Mean similarity falls from 94.0% at 20% progress to 25.9% at trajectory endpoints, indicating different chemical evolution associated with combined loading histories, not one isolated cause.
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