Return
Precise Polymer Synthesis by Autonomous Self-Optimizing Flow Reactors
DOI:10.1002/anie.201810384.png)
Abstract
En 中文
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
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
16.9
Papers:
5.7W
Citations:
53.0W
Organization
Cited Papers
Photoinduced Organocatalyzed Atom Transfer Radical Polymerization Using Continuous Flow
MACROMOLECULES
IF5.2

