| ID | 67683 |
| 著者 |
Suzuki, Daisuke
Graduate School of Environmental, Life, Natural Science and Technology, Okayama University
Minato, Haruka
Graduate School of Environmental, Life, Natural Science and Technology, Okayama University
Sato, Yuji
Graduate School of Environmental, Life, Natural Science and Technology, Okayama University
Namioka, Ryuji
Graduate School of Textile Science & Technology, Shinshu University
Igarashi, Yasuhiko
Faculty of Engineering, Information and Systems, University of Tsukuba
Shibata, Risako
Department of Applied Chemistry, Faculty of Science and Technology, Keio University
Oaki, Yuya
Department of Applied Chemistry, Faculty of Science and Technology, Keio University
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| 抄録 | The size of soft colloids (microgels) is essential; however, control over their size has typically been established empirically. Herein, we report a linear-regression model that can predict microgel size using a machine learning method, sparse modeling for small data, which enables the determination of the synthesis conditions for target-sized microgels.
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| 備考 | This is an Accepted Manuscript of an article published by Royal Society of Chemistry (RSC).
This fulltext file will be available in Oct. 2025.
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| 発行日 | 2024
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| 出版物タイトル |
Chemical Communications
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| 出版者 | Royal Society of Chemistry (RSC)
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| ISSN | 1364-548X
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| 資料タイプ |
学術雑誌論文
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| 言語 |
英語
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| OAI-PMH Set |
岡山大学
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| 著作権者 | © The Royal Society of Chemistry 2024
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| 論文のバージョン | author
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| PubMed ID | |
| DOI | |
| Web of Science KeyUT | |
| 関連URL | isVersionOf https://doi.org/10.1039/d4cc04386c
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| 助成機関名 |
Japan Society for the Promotion of Science
Japan Science and Technology Agency
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| 助成番号 | 24K01550
JPMJCR21L2
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