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Roboticized AI-assisted microfluidic photocatalytic synthesis and screening up to 10,000 reactions per day

Author

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  • Jia-Min Lu

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Hui-Feng Wang

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Qi-Hang Guo

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center
    Zhejiang University)

  • Jian-Wei Wang

    (ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Tong-Tong Li

    (Zhejiang University
    Zhejiang University)

  • Ke-Xin Chen

    (Zhejiang Lab
    The Chinese University of Hong Kong)

  • Meng-Ting Zhang

    (Zhejiang University)

  • Jian-Bo Chen

    (Zhejiang University)

  • Qian-Nuan Shi

    (ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Yi Huang

    (ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Shao-Wen Shi

    (ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Guang-Yong Chen

    (Zhejiang Lab)

  • Jian-Zhang Pan

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center)

  • Zhan Lu

    (Zhejiang University
    Zhejiang University)

  • Qun Fang

    (Zhejiang University
    ZJU-Hangzhou Global Scientific and Technological Innovation Center
    Zhejiang University)

Abstract

The current throughput of conventional organic chemical synthesis is usually a few experiments for each operator per day. We develop a robotic system for ultra-high-throughput chemical synthesis, online characterization, and large-scale condition screening of photocatalytic reactions, based on the liquid-core waveguide, microfluidic liquid-handling, and artificial intelligence techniques. The system is capable of performing automated reactant mixture preparation, changing, introduction, ultra-fast photocatalytic reactions in seconds, online spectroscopic detection of the reaction product, and screening of different reaction conditions. We apply the system in large-scale screening of 12,000 reaction conditions of a photocatalytic [2 + 2] cycloaddition reaction including multiple continuous and discrete variables, reaching an ultra-high throughput up to 10,000 reaction conditions per day. Based on the data, AI-assisted cross-substrate/photocatalyst prediction is conducted.

Suggested Citation

  • Jia-Min Lu & Hui-Feng Wang & Qi-Hang Guo & Jian-Wei Wang & Tong-Tong Li & Ke-Xin Chen & Meng-Ting Zhang & Jian-Bo Chen & Qian-Nuan Shi & Yi Huang & Shao-Wen Shi & Guang-Yong Chen & Jian-Zhang Pan & Zh, 2024. "Roboticized AI-assisted microfluidic photocatalytic synthesis and screening up to 10,000 reactions per day," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53204-6
    DOI: 10.1038/s41467-024-53204-6
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    References listed on IDEAS

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