Predictive control and verification of conversion kinetics and polymer molecular weight in semi-batch free radical homopolymer reactions
Polymer molar mass distributions critically affect macroscopic characteristics and performance of polymeric materials. While multi-detector methods coupled to size exclusion chromatography (SEC) are widely used to measure endproduct mass distributions, less progress has been made in simultaneously c...
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Veröffentlicht in: | European polymer journal 2009-08, Vol.45 (8), p.2288-2303 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Polymer molar mass distributions critically affect macroscopic characteristics and performance of polymeric materials. While multi-detector methods coupled to size exclusion chromatography (SEC) are widely used to measure endproduct mass distributions, less progress has been made in simultaneously controlling and verifying the evolution of these distributions during synthesis. This work focuses on quantitative predictions and online verification of conversion kinetics and of molecular weight during free radical homopolymerization of acrylamide, where reagents were fed into the reactor during the reaction. The central task is to establish and experimentally test a formalism combining free radical polymerization kinetics with time dependent processes related to flows of material into and out of the reactor. Monomer feed experiments were performed that alternately hold molecular weight constant and ramp the weight up, in contrast to batch reactions, where molecular weight decreases. Three types of initiator feed ‘tapers’ were also used to produce predictable conversion kinetics and mass distributions: (i) constant initiator feed, (ii) linearly stepped feed to produce Gaussian conversion kinetics, and (iii) booster shots to produce multi-modal masses. Automatic Continuous Online Monitoring of Polymerization reactions (ACOMP) was used to follow the conversion and evolution of the average mass distribution, and multi-detector SEC was used to cross-check results and measure full distributions of endproducts. In general, there was good agreement between the predictions and results. In future work this approach can be used as an Ansatz for reaction trajectory prediction, and the online monitoring signals exploited to make feedback controlled corrections to the reagent flows and other reaction conditions. |
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ISSN: | 0014-3057 1873-1945 |
DOI: | 10.1016/j.eurpolymj.2009.05.006 |