Intelligent prediction of heat capacity of polyethylene glycol polymer
Abstract Polyethylene glycol (PEG) exhibits tunable molar heat capacity, making it essential for thermal management and materials processing. Using an experimental databank of 528 observations, this study applies machine learning to develop predictive models based on temperature and molar mass. Data...
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| Auteurs principaux: | , , , , , , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Nature Portfolio
2025-11-01
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| Collection: | Scientific Reports |
| Sujets: | |
| Accès en ligne: | https://doi.org/10.1038/s41598-025-25326-4 |
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