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Development of Pd-immobilized porous polymer catalysts via Bayesian optimization
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- Zhou, Xincheng
- Department of Chemical Engineering, Kyushu University
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- Matsumoto, Hikaru
- Department of Chemical Engineering, Kyushu University
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- Nagao, Masanori
- Department of Chemical Engineering, Kyushu University
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- Hironaka, Shuji
- Department of Chemical Engineering, Kyushu University
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- Miura, Yoshiko
- Department of Chemical Engineering, Kyushu University
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Description
In this study, a Pd-polymeric porous immobilized catalyst is prepared for the Suzuki–Miyaura coupling reactions by employing a Bayesian optimization method to optimize the catalyst. This research represents the first endeavor to utilize machine learning for the optimization of polymer-immobilized catalysts and provides a novel perspective on utilizing machine learning for the optimization of complex materials.
Journal
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- Polymer Journal
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Polymer Journal 56 (9), 865-872, 2024-06-06
Springer Nature
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Keywords
Details 詳細情報について
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- CRID
- 1050021846545482880
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- NII Book ID
- AA00777013
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- ISSN
- 13490540
- 00323896
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- HANDLE
- 2324/7337522
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- NDL BIB ID
- 033806562
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- Text Lang
- en
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- Article Type
- journal article
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- Data Source
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- IRDB
- NDL Search
