Precise Polymer Synthesis by Autonomous Self‐Optimizing Flow Reactors

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...

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Vydáno v:Angewandte Chemie International Edition Ročník 58; číslo 10; s. 3183 - 3187
Hlavní autoři: Rubens, Maarten, Vrijsen, Jeroen H., Laun, Joachim, Junkers, Tanja
Médium: Journal Article
Jazyk:angličtina
Vydáno: Germany Wiley Subscription Services, Inc 04.03.2019
Vydání:International ed. in English
Témata:
Algorithms
Automation
Chemical synthesis
Continuous flow
flow reactors
Flow system
Ions
Learning algorithms
Machine learning
Molecular weight
monomers
Optimization
Polymers
Process control
Reactors
Reproducibility
Size exclusion chromatography
synthetic methods
polymers
monomers
machine learning
synthetic methods
flow reactors
ISSN:1433-7851, 1521-3773, 1521-3773
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Shrnutí: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. 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.
Bibliografie:These authors contributed equally to this work.
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ISSN:1433-7851
1521-3773
1521-3773
DOI:10.1002/anie.201810384