| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2025-01-08 |
| タイトル |
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|
タイトル |
GFN-xTB Based Computations Provide Comprehensive Insights into Emulsion Radiation-Induced Graft Polymerization |
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言語 |
en |
| 言語 |
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|
言語 |
eng |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| 著者 |
Matsubara Kiho
Takahashi Kei
Takeshi Matsuda
Ueki Yuuji
Seko Noriaki
Ryohei Kakuchi
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
In this article, a deep insight into emulsion radiartion-induced graft polymerization (RIGP) was obtained by computing explicit solvation free energies, conformational entropy, monomer radius and dipole moments with the state-of-the-art Conformer-Rotamer Ensemble Sampling Tool (CREST) package primalily at semiempirical GFN-xTB level. By leveraging the robustness of the CREST package, above parameters provided dynamic nature of methacrylate monoers with the consideration of realistic emulsion conditions. With the chemical and physical importance of the above results, CREST-determined explanatory variables sufficiently led to the building of the prediction models for the RIGP of methacrylate monomers. The machine learning model building resulted in effective reactivity predictions and unveiled important factors for the radiation-induced graft polymerization in a chemically interpretable fashion. |
| 書誌情報 |
ChemPlusChem
巻 89,
号 4,
p. e202300480,
発行日 2023-10
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| 出版者 |
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出版者 |
Wiley |
| ISSN |
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収録物識別子タイプ |
ISSN |
|
収録物識別子 |
2192-6506 |
| DOI |
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|
識別子タイプ |
DOI |
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関連識別子 |
10.1002/cplu.202300480 |
