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Predicting Polymer Properties via a Coupled Kinetic, Stochastic and Rheological Modeling Approach from Reaction Conditions

Zentel, Kristina M. ; Busch, Markus (2022)
Predicting Polymer Properties via a Coupled Kinetic, Stochastic and Rheological Modeling Approach from Reaction Conditions.
In: Macromolecular Reaction Engineering, 2022, 16 (1)
doi: 10.26083/tuprints-00021542
Artikel, Zweitveröffentlichung, Verlagsversion

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Kurzbeschreibung (Abstract)

A three‐step multiscale modeling approach to predict and thus control polymer properties, such as flow behavior and linear as well as non‐linear rheology, based on polymerization conditions, is developed and applied for long‐chain branched low‐density polyethylene (LDPE). The approach consists of i) a deterministic kinetic model for the description of conversion and average polymer characteristics, ii) a hybrid stochastic Monte Carlo model for the description of the polymeric microstructure, and iii) a rheology model for the evaluation of polymer melt flow properties. The modeling approach is validated via high‐pressure miniplant LDPE samples with a special focus on long‐chain branching. In the next step, the modeling approach can be successfully transferred to a tubular reactor of industrial scale. Due to its universality the approach opens up possible applications for other polymer and also copolymer systems.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Zentel, Kristina M. ; Busch, Markus
Art des Eintrags: Zweitveröffentlichung
Titel: Predicting Polymer Properties via a Coupled Kinetic, Stochastic and Rheological Modeling Approach from Reaction Conditions
Sprache: Englisch
Publikationsjahr: 2022
Ort: Darmstadt
Publikationsdatum der Erstveröffentlichung: 2022
Verlag: Wiley-VCH
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Macromolecular Reaction Engineering
Jahrgang/Volume einer Zeitschrift: 16
(Heft-)Nummer: 1
Kollation: 16 Seiten
DOI: 10.26083/tuprints-00021542
URL / URN: https://tuprints.ulb.tu-darmstadt.de/21542
Zugehörige Links:
Herkunft: Zweitveröffentlichung DeepGreen
Kurzbeschreibung (Abstract):

A three‐step multiscale modeling approach to predict and thus control polymer properties, such as flow behavior and linear as well as non‐linear rheology, based on polymerization conditions, is developed and applied for long‐chain branched low‐density polyethylene (LDPE). The approach consists of i) a deterministic kinetic model for the description of conversion and average polymer characteristics, ii) a hybrid stochastic Monte Carlo model for the description of the polymeric microstructure, and iii) a rheology model for the evaluation of polymer melt flow properties. The modeling approach is validated via high‐pressure miniplant LDPE samples with a special focus on long‐chain branching. In the next step, the modeling approach can be successfully transferred to a tubular reactor of industrial scale. Due to its universality the approach opens up possible applications for other polymer and also copolymer systems.

Freie Schlagworte: low‐density polyethylene, multiscale modeling, rheology, structure–property relationships
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-215429
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 500 Naturwissenschaften und Mathematik > 540 Chemie
Fachbereich(e)/-gebiet(e): 07 Fachbereich Chemie
07 Fachbereich Chemie > Ernst-Berl-Institut
07 Fachbereich Chemie > Ernst-Berl-Institut > Fachgebiet Technische Chemie
07 Fachbereich Chemie > Ernst-Berl-Institut > Fachgebiet Technische Chemie > Technische Chemie III
Hinterlegungsdatum: 24 Jun 2022 13:10
Letzte Änderung: 03 Jul 2024 02:55
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