Liu, Hongwei (2022) Modeling the Rheology of Ordinary and Associating Unentangled Polymer Melts. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Resource language: English
Title: Modeling the Rheology of Ordinary and Associating Unentangled Polymer Melts
Creators:
CreatorsEmail
Liu, Hongweihongwei.liu@unina.it
Date: 11 January 2022
Number of Pages: 173
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Chimica, dei Materiali e della Produzione Industriale
Dottorato: Ingegneria dei prodotti e dei processi industriali
Ciclo di dottorato: 33
Coordinatore del Corso di dottorato:
nomeemail
D'Anna, Andreaandrea.danna@unina.it
Tutor:
nomeemail
Ianniruberto, GiovanniUNSPECIFIED
Date: 11 January 2022
Number of Pages: 173
Keywords: Sticky Rouse Model; Associating Polymers; Coarse-grained Modeling; Friction Reduction; Fast Flow
Settori scientifico-disciplinari del MIUR: Area 02 - Scienze fisiche > FIS/02 - Fisica teorica, modelli e metodi matematici
Area 08 - Ingegneria civile e Architettura > ICAR/11 - Produzione edilizia
Date Deposited: 28 Jan 2022 09:21
Last Modified: 07 Jun 2023 11:22
URI: http://www.fedoa.unina.it/id/eprint/13532

Collection description

We are aiming at studying the rheological behavior of ordinary and associating polymers. Ordinary polymers refer to polymers without stickers but under fast flows. Associating polymers are a group of polymers which are held together through reversible non covalent bonds, such as ionic interactions, metal-ligand, $\pi$-$\pi$ stacking, and hydrogen bonds. Both topics have attracted enormous attention either due to the non-universal features in fast flows of polymer melts or because of their unique abilities for working as self-healing, stimuli-sensitive, and shape-memory materials. Fast flows and large deformation rates typically are involved in polymer processing operations and no general constitutive equation can be written that describes these nonlinear rheological behavior exhibited by polymer flows. Therefore, molecular modeling of the rheology of polymers in fast flow was developed many years ago. The friction reduction due to coalignment of polymer chains has been confirmed both through molecular dynamics simulations and extensional flow experiments. In spite of the results achieved by the friction reduction model, the flow-induced reduction of the friction coefficient is still highly controversial. For instance, the Einstein relationship between $\zeta$ and the diffusion coefficient probably does not hold true away from equilibrium. This thesis partly focuses on enhancing our understanding of the mechanisms behind the nonlinear responses of the unentangled polymer melts under fast shear flow through a coarse-grained modeling approach. We take advantage of the rich set of data of Kremer-Grest melts in fast steady shear flows. First, we apply the data to the latest Watanabe's model. Then we reproduce them by suitable Brownian dynamics simulations, where the beads are endowed with isotropic and anisotropic friction separately. Likewise, molecular modeling is typically used to study the viscoelastic response of associating polymers as well. The most famous one is the sticky Rouse model. This model is capable of accounting for the slowing down of the relaxation caused by reversible bonds. However, the effects of the lifetime, density, and distribution of stickers on the dynamics of associating polymers is still a matter of some debate. For instance, a mismatch between data and predictions of this model at the intermediate frequencies always appears. The rest of this thesis concentrates on studying the dynamics of associating polymers. A multi-chain model and a single-chain model are proposed. The predictions of the multi-chain model are able to describe the topological structure of polymer networks. Meanwhile, those effects on rheological behavior are studied. The results are compared with the predictions of the sticky Rouse model. The single-chain model, which was designed to save running time, allows stickers to be distributed randomly. The predictions are compared with data.

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