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

Lu, Jia-Min; Wang, Hui-Feng; Guo, Qi-Hang; Wang, Jian-Wei; Li, Tong-Tong; Chen, Ke-Xin; Zhang, Meng-Ting; Chen, Jian-Bo; Shi, Qian-Nuan; Huang, Yi; Shi, Shao-Wen; Chen, Guang-Yong; Pan, Jian-Zhang; Lu, Zhan; Fang, Qun

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. The current throughput of conventional organic chemical synthesis is usually a few experiments for each operator per day. Here the authors develop a robotic system for ultra-high-throughput chemical synthesis, online characterization and large-scale condition screening of photocatalytic reactions.

CHEMICAL synthesis; ORGANIC synthesis; RING formation (Chemistry); ARTIFICIAL intelligence; CHEMICAL systems

Nature Communications, 2024, Vol 15, Issue 1, p1

2041-1723

Academic Journal

10.1038/s41467-024-53204-6