A novel continuous flow system for automated high-throughput screening, autonomous optimization, and enhanced process control of polymerizations was developed. The computer-controlled platform comprises a flow reactor coupled to size exclusion chromatography (SEC). Molecular weight distributions are measured online and used by a machine-learning algorithm to self-optimize reactions towards a programmed molecular weight by dynamically varying reaction parameters (i.e. residence time, monomer concentration, and control agent/initiator concentration). The autonomous platform allows targeting of molecular weights in a reproducible manner with unprecedented accuracy (<2.5 % deviation from pre-selected goal) for both thermal and light-induced reactions. For the first time, polymers with predefined molecular weights can be custom made under optimal reaction conditions in an automated, high-throughput flow synthesis approach with outstanding reproducibility.
Keywords: flow reactors; machine learning; monomers; polymers; synthetic methods.
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