微流控
光催化
纳米技术
材料科学
化学
催化作用
有机化学
作者
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
标识
DOI:10.1038/s41467-024-53204-6
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI