Automated self-optimization, intensification, and scale-up of photocatalysis in flow

• 成果类型: Article
• 署名作者: Slattery, Aidan; Wen, Zhenghui; Tenblad, Pauline; Sanjose-Orduna, Jesus; Pintossi, Diego; den Hartog, Tim; Noel, Timothy
• 署名单位: University of Amsterdam; Netherlands Organization Applied Science Research
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-12481
• DOI: 10.1126/science.adj1817
• 发表日期: 2024-01-26
• 关键词: catalysis

摘要

The optimization, intensification, and scale-up of photochemical processes constitute a particular challenge in a manufacturing environment geared primarily toward thermal chemistry. In this work, we present a versatile flow-based robotic platform to address these challenges through the integration of readily available hardware and custom software. Our open-source platform combines a liquid handler, syringe pumps, a tunable continuous-flow photoreactor, inexpensive Internet of Things devices, and an in-line benchtop nuclear magnetic resonance spectrometer to enable automated, data-rich optimization with a closed-loop Bayesian optimization strategy. A user-friendly graphical interface allows chemists without programming or machine learning expertise to easily monitor, analyze, and improve photocatalytic reactions with respect to both continuous and discrete variables. The system's effectiveness was demonstrated by increasing overall reaction yields and improving space-time yields compared with those of previously reported processes.