Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis
In this study, machine learning (ML)-assisted regression modeling was conducted to predict the thermal decomposition temperatures and explore the factors that correlate with the thermal stability of energetic materials (EMs). The modeling was performed based on a dataset consisting of 885 various co...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2024-12-01
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| Series: | Energetic Materials Frontiers |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266664722300043X |
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