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Machine learning glass transition temperature of polymers
As an important thermophysical property, polymers' glass transition temperature, Tg, could sometimes be difficult to determine experimentally. Modeling methods, particularly data-driven approaches, are promising alternatives to predictions of Tg in a fast and robust way. The molecular traceless...
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| Pubblicato in: | Heliyon |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7553976/ https://ncbi.nlm.nih.gov/pubmed/33083589 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.heliyon.2020.e05055 |
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