Harnessing machine learning enabled quickly predicting density of CHON molecules for discovering new energetic materials
The application of machine learning in the research and development of energetic materials is becoming increasingly widespread for performance prediction and inverse design. Many advances have been achieved, especially in the discovery of various new energetic materials. However, the research of mai...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2025-04-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0260616 |
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