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Journal of Rheology
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
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A tube model for predicting the stress and dielectric relaxations of polydisperse linear polymers

Authors: Chinmay Das; Daniel J. Read;

A tube model for predicting the stress and dielectric relaxations of polydisperse linear polymers

Abstract

We present an algorithm to predict the linear relaxation spectra for linear polymers of fully general and arbitrary polydispersity. As is common in the tube theory descriptions of linear polymers, we assume that the stress relaxation is affected by both the constraint release and tube escape modes, but unlike most existing descriptions we consider how these two modes of relaxation affect each other. We argue that the proper description for relaxation in an arbitrary blend of linear polymers requires consideration of multiple embedded tubes affecting the different relaxation pathways; we propose a novel but minimal description involving five embedded tubes. Building on prior work for binary blends, we derive the scaling level descriptions of the relaxation pathways. We use a large number of existing experimental results on the stress and dielectric relaxations to validate our model, ensuring we explore a very broad range of parameter space.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
hybrid