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http://hdl.handle.net/1942/27567
Title: | Precise Polymer Synthesis by Autonomous Self-Optimizing Flow Reactors | Authors: | RUBENS, Maarten VRIJSEN, Jeroen LAUN, Joachim JUNKERS, Tanja |
Issue Date: | 2019 | Publisher: | WILEY-V C H VERLAG GMBH | Source: | Angewandte Chemie International edition, 58 (10), p. 3183-3187 | 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. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. | Notes: | Junkers, T (reprint author), Hasselt Univ, Martelarenlaan 42, B-3500 Hasselt, Belgium. tanja.junkers@monash.edu | Keywords: | flow reactors;machine learning;monomers;polymers;synthetic methods | Document URI: | http://hdl.handle.net/1942/27567 | ISSN: | 1433-7851 | e-ISSN: | 1521-3773 | DOI: | 10.1002/anie.201810384 | ISI #: | 000459709300040 | Rights: | 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
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