Understanding impact sensitivity of energetic molecules by supervised machine learning
Open Access
- 3 October 2025
- journal article
- research article
- Published by Royal Society of Chemistry (RSC) in Digital Discovery
- Vol. 4 (11) , 3260-3269
Abstract
Machine learning models have been developed to rationalise correlations between molecular structure and sensitivity to initiation by mechanical impact for a data set of 485 energetic molecules.Keywords
Funding Information
- Ministry of Defence (WSTC1079)
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