Lee Jules, Mulay Prajakatta, Tamasi Matthew J, Yeow Jonathan, Stevens Molly M, Gormley Adam J
Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Department of Materials, Department of Bioengineering, and Institute of Biomedical Engineering, Imperial College London, London, SW7 2AZ, UK.
Digit Discov. 2023 Jan;2:219-233. doi: 10.1039/D2DD00100D. Epub 2023 Jan 5.
Oxygen tolerant polymerizations including Photoinduced Electron/Energy Transfer-Reversible Addition-Fragmentation Chain-Transfer (PET-RAFT) polymerization allow for high-throughput synthesis of diverse polymer architectures on the benchtop in parallel. Recent developments have further increased throughput using liquid handling robotics to automate reagent handling and dispensing into well plates thus enabling the combinatorial synthesis of large polymer libraries. Although liquid handling robotics can enable automated polymer reagent dispensing in well plates, photoinitiation and reaction monitoring require automation to provide a platform that enables the reliable and robust synthesis of various polymer compositions in high-throughput where polymers with desired molecular weights and low dispersity are obtained. Here, we describe the development of a robotic platform to fully automate PETRAFT polymerizations and provide individual control of reactions performed in well plates. On our platform, reagents are automatically dispensed in well plates, photoinitiated in individual wells with a custom-designed lightbox until the polymerizations are complete, and monitored online in real-time by tracking fluorescence intensities on a fluorescence plate reader, with well plate transfers between instruments occurring a robotic arm. We found that this platform enabled robust parallel polymer synthesis of both acrylate and acrylamide homopolymers and copolymers, with high monomer conversions and low dispersity. The successful polymerizations obtained on this platform make it an efficient tool for combinatorial polymer chemistry. In addition, with the inclusion of machine learning protocols to help navigate the polymer space towards specific properties of interest, this robotic platform can ultimately become a self-driving lab that can dispense, synthesize, and monitor large polymer libraries.
包括光诱导电子/能量转移-可逆加成-断裂链转移(PET-RAFT)聚合在内的耐氧聚合反应,能够在实验台上并行地高通量合成各种聚合物结构。最近的进展通过使用液体处理机器人进一步提高了通量,以实现试剂处理和分配到微孔板中的自动化,从而实现大型聚合物文库的组合合成。尽管液体处理机器人可以实现微孔板中聚合物试剂的自动分配,但光引发和反应监测需要自动化,以提供一个平台,能够在高通量条件下可靠且稳健地合成各种聚合物组合物,从而获得具有所需分子量和低分散度的聚合物。在此,我们描述了一个机器人平台的开发,该平台能够使PET-RAFT聚合反应完全自动化,并对微孔板中进行的反应进行单独控制。在我们的平台上,试剂自动分配到微孔板中,通过定制设计的灯箱在各个孔中进行光引发,直到聚合反应完成,并通过在荧光酶标仪上跟踪荧光强度进行实时在线监测,仪器之间的微孔板转移由机器人手臂完成。我们发现,该平台能够稳健地并行合成丙烯酸酯和丙烯酰胺均聚物及共聚物,具有高单体转化率和低分散度。在该平台上成功进行的聚合反应使其成为组合聚合物化学的有效工具。此外,通过纳入机器学习协议来帮助探索聚合物空间以获得感兴趣的特定性能,这个机器人平台最终可以成为一个能够分配、合成和监测大型聚合物文库的自动驾驶实验室。