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Machine learning discovery of high-temperature polymers
To formulate a machine learning (ML) model to establish the polymer's structure-property correlation for glass transition temperature [Formula: see text] , we collect a diverse set of nearly 13,000 real homopolymers from the largest polymer database, PoLyInfo. We train the deep neural network (...
Tallennettuna:
| Julkaisussa: | Patterns (N Y) |
|---|---|
| Päätekijät: | , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Elsevier
2021
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8085602/ https://ncbi.nlm.nih.gov/pubmed/33982020 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.patter.2021.100225 |
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