Bayesian optimization-driven parallel-screening of multiple parameters for the flow synthesis of biaryl compounds

Autor: Masaru Kondo, H. D. P. Wathsala, Mohamed S. H. Salem, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washio, Hiroaki Sasai, Shinobu Takizawa
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Communications Chemistry, Vol 5, Iss 1, Pp 1-9 (2022)
Druh dokumentu: article
ISSN: 2399-3669
DOI: 10.1038/s42004-022-00764-7
Popis: Data-driven methodology plays an important role in the rapid identification of appropriate chemical conditions, however, optimization of multiple variables in the flow reaction remains challenging. Here, the authors report a Bayesian optimization-assisted multi-parameter screening to predict the suitable conditions to achieve the efficient synthesis of biaryl compounds in a flow system.
Databáze: Directory of Open Access Journals
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