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Machine Learning Approach for Prediction of the Grafting Yield in Radiation-Induced Graft Polymerization
https://repo.qst.go.jp/records/84792
https://repo.qst.go.jp/records/847929fff72c0-983d-4d25-a152-4afcb7f40154
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2021-08-16 | |||||
タイトル | ||||||
タイトル | Machine Learning Approach for Prediction of the Grafting Yield in Radiation-Induced Graft Polymerization | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
Yuuji, Ueki
× Yuuji, Ueki× Noriaki, Seko× Yasunari, Maekawa× Yuuji, Ueki× Noriaki, Seko× Yasunari, Maekawa |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Grafting yields for the radiation-induced graft polymerization of a methacrylate ester monomer to give a polyethylene-coated polypropylene nonwoven fabric were predicted as an objective variable by a machine learning approach. The degrees of grafting were obtained from actual experiments. Monomer structure information, atomic charge information, atomic NMR shift information, and infrared absorption wavenumber information, derived from density functional theory calculations, were adopted as explanatory variables of a grafting yield prediction model. Among machine learning algorithms as a prediction model on the grafting yield, XGBoost and random forest models showed higher prediction accuracy, compared to a multiple linear regression model. The prediction accuracies of the various algorithm decreased in the order: XGBoost > random forest > multiple linear regression/LASSO > decision tree > multiple linear regression. The monomer polarizability and the O2 NMR shift were found to be important explanatory variables for predicting the grafting yield in the XGBoost model. This is probably because the polarizability, which represents a miscibility indicator of the monomer to the trunk polymer, and the O2 NMR shift, which represents a diffusivity indicator of the monomer into the trunk polymer, remarkably reflect the difference in the substituent structure of the methacrylate ester monomers. | |||||
書誌情報 |
Applied Materials Today 巻 25, p. 101158-1-101158-9, 発行日 2021-09 |
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出版者 | ||||||
出版者 | Elsevier | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 2352-9407 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1016/j.apmt.2021.101158 | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | https://www.sciencedirect.com/science/article/abs/pii/S2352940721002225?via%3Dihub |