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Exploring ultrafast flow chemistry by autonomous self-optimizing platform

Author(s)
Ahn, Gwang-NohKang, Ji-HoLee, Hyune-JeaPark, Byung EonKwon, MinjunNa, Gi-SuKim, HeejinSeo, Dong-HwaKim, Dong-Pyo
Issued Date
2023-02
DOI
10.1016/j.cej.2022.139707
URI
https://scholarworks.unist.ac.kr/handle/201301/59787
Citation
CHEMICAL ENGINEERING JOURNAL, v.453, pp.139707
Abstract
The rapid development of novel synthetic routes for pharmaceutical compounds is highly attractive for overcoming pandemic and epidemic-prone diseases like COVID-19. Herein, we report an automated microreactor platform (AMP) with Bayesian optimization (BO) that can autonomously explore the optimal conditions for ultrafast synthesis of biologically active thioquinazolinone. First, AMP operation is successfully demonstrated with full control of quantitative variables, specifically reaction volume, temperature, and flow rate, allowing to sequentially conduct a total of 80 experiments planned by the user. Next, BO enables the AMP to autonomously self-optimize the reaction conditions, demonstrating the high efficiency of the fully automated AMP. The fully automated approach is extended to optimize more complex variables including a categorical variable (i.e. the type of organolithium for synthesis), revealing that phenyllithium (PhLi) gives superior yield for synthesizing thioquinazolinone. In addition, the autonomous AMP is utilized for combinatorial chemistry to sequentially synthesize a library composed of nine types of S-benzylic thioquinazolinone under autonomously optimized conditions within only 20 min.
Publisher
Elsevier BV
ISSN
1385-8947

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