Roboticized AI-assisted microfluidic photocatalytic synthesis and screening up to 10,000 reactions per day
Jia-Min Lu, Huifeng Wang, Qi-Hang Guo, Jianwei Wang, Tongtong Li, Kexin Chen, Mengting Zhang, Jianbo Chen, Qian-Nuan Shi, Yi Huang, Shao-Wen Shi, Guangyong Chen, Jian‐Zhang Pan, Zhan Lu, Qun Fang
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. 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.