A fully automated platform for photoinitiated RAFT polymerization
A fully automated platform for photoinitiated RAFT polymerization
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DOI：
10.1039/d2dd00100d
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发表时间：
2023-02-13
期刊：
影响因子：
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通讯作者：
Gormley，Adam J.
中科院分区：
文献类型：
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作者：
Lee，Jules;Mulay，Prajakatta;Gormley，Adam J.
包括光诱导电子/能量转移-可逆加成-断裂链转移（PET-RAFT）聚合的耐氧聚合允许在工作台上并行地高通量合成不同的聚合物结构。最近的发展已经使用液体处理机器人来使试剂处理和分配自动化到孔板中，从而使得能够组合合成大型聚合物文库，从而进一步提高了通量。虽然液体处理机器人可以实现在孔板中自动分配聚合物试剂，但是光引发和反应监测需要自动化以提供能够以高通量可靠和稳健地合成各种聚合物组合物的平台，其中获得具有所需分子量和低分散性的聚合物。在这里，我们描述了一个机器人平台的发展，完全自动化PET-RAFT聚合，并提供个人控制的反应中进行的孔板。在我们的平台上，试剂自动分配到孔板中，使用定制设计的灯箱在单个威尔斯孔中进行光引发，直到聚合完成，并通过跟踪荧光板读数器上的荧光强度进行实时在线监测，通过机械臂在仪器之间进行孔板转移。我们发现，该平台能够实现丙烯酸酯和丙烯酰胺均聚物的稳健并行聚合物合成和共聚物，具有高的单体转化率和低的分散性。在此平台上获得的成功聚合使其成为组合聚合物化学的有效工具。此外，通过包含机器学习协议来帮助将聚合物空间导航到感兴趣的特定属性，这个机器人平台最终可以成为一个自动驾驶实验室，可以分配，合成和监控大型聚合物库。
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 PET-RAFT 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 via 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.