Bayesian optimization with constraint on passed charge for multiparameter screening of electrochemical reductive carboxylation in a flow microreactor

Yuki Naito; Masaru Kondo; Yuto Nakamura; Naoki Shida; Kazunori Ishikawa; Takashi Washio; Shinobu Takizawa; Mahito Atobe

doi:10.1039/d2cc00124a

Bayesian optimization with constraint on passed charge for multiparameter screening of electrochemical reductive carboxylation in a flow microreactor

Chem Commun (Camb). 2022 Mar 22;58(24):3893-3896. doi: 10.1039/d2cc00124a.

Authors

Yuki Naito¹, Masaru Kondo^{2

3}, Yuto Nakamura¹, Naoki Shida¹, Kazunori Ishikawa⁴, Takashi Washio^{4

5}, Shinobu Takizawa^{3

5}, Mahito Atobe¹

Affiliations

¹ Graduate School of Science and Engineering, Yokohama National University, Yokohama, Kanagawa 240-8501, Japan. [email protected].
² Department of Materials Science and Engineering, Graduate School of Science and Engineering, Ibaraki University, Hitachi 316-8511, Ibaraki, Japan.
³ Department of Synthetic Organic Chemistry, SANKEN, Osaka University, Mihogaoka, Ibaraki, Osaka 567-0047, Japan. [email protected].
⁴ Department of Reasoning for Intelligence, SANKEN, Osaka University, Japan. [email protected].
⁵ Artificial Intelligence Research Center, SANKEN, Osaka University, Japan.

PMID: 35226032
DOI: 10.1039/d2cc00124a

Abstract

Multiparameter screening of reductive carboxylation in an electrochemical flow microreactor was performed using a Bayesian optimization (BO) strategy. The developed algorithm features a constraint on passed charge for the electrochemical reaction, which led to suitable conditions being instantaneously found for the desired reaction. Analysis of the BO-suggested conditions underscored the physicochemical validity.