Machine learning-guided property prediction of energetic materials: Recent advances, challenges, and perspectives
Predicting chemical properties is one of the most important applications of machine learning. In recent years, the prediction of the properties of energetic materials using machine learning has been receiving more attention. This review summarized recent advances in predicting energetic compounds’ p...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2022-09-01
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| Series: | Energetic Materials Frontiers |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666647222000628 |