Precise Polymer Synthesis by Autonomous Self‐Optimizing Flow Reactors. Issue 10 (21st November 2018)

• Record Type: Journal Article
• Authors: Rubens, Maarten; Vrijsen, Jeroen H.; Laun, Joachim; Junkers, Tanja
• Is Part Of: Angewandte Chemie international edition. Volume 58:Issue 10(2019)
• Page Start: 3183
• Page End: 3187
• Publication Date: 2018-11-21
• Subjects: flow reactors -- machine learning -- monomers -- polymers -- synthetic methods; Chemistry -- Periodicals; 540
• DOI: 10.1002/anie.201810384
• Languages: English
• ISSNs: 1433-7851

Abstract

Abstract: 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. Abstract : Polymers made by an artificial brain : An autonomous continuous flow system for polymerizations is presented. Reaction parameters (i.e., residence time, monomer and control agent/initiator concentrations) are dynamically and autonomously varied with a self‐optimizing algorithm to obtain predefined molecular weights. This novel platform can target molecular weights with unprecedented accuracy in a reproducible manner.