Machine-learning-driven QSPR models for energetic molecules: A review on safety and energetic properties prediction
The performance prediction and rational design of energetic molecules (EMs) remain central challenges in their development. Traditional experimental methods are constrained by prohibitively high costs and inherent safety risks, highlighting the urgent requirement for efficient computational alternat...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Chemical Engineering Journal Advances |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666821125001012 |
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