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Understanding Effect of Constraint Release Environment on End-to-End Vector Relaxation of Linear Polymer Chains
journal contribution
posted on 2017-05-26, 20:18 authored by Maksim E. Shivokhin, Daniel J. Read, Dimitris Kouloumasis, Rok Kocen, Flanco Zhuge, Christian Bailly, Nikos Hadjichristidis, Alexei E. LikhtmanWe
propose and verify methods based on the slip-spring (SSp) model
[Macromolecules 2005, 38, 14] for predicting the effect of any monodisperse, binary, or ternary
environment of topological constraints on the relaxation of the end-to-end
vector of a linear probe chain. For this purpose we first validate
the ability of the model to consistently predict both the viscoelastic
and dielectric response of monodisperse and binary mixtures of type
A polymers, based on published experimental data. We also report the
synthesis of new binary and ternary polybutadiene systems, the measurement
of their linear viscoelastic response, and the prediction of these
data by the SSp model. We next clarify the relaxation mechanisms of
probe chains in these constraint release (CR) environments by analyzing
a set of “toy” SSp models with simplified constraint
release rates, by examining fluctuations of the end-to-end vector.
In our analysis, the longest relaxation time of the probe chain is
determined by a competition between the longest relaxation times of
the effective CR motions of the fat and thin tubes and the motion
of the chain itself in the thin tube. This picture is tested by the
analysis of four model systems designed to separate and estimate every
single contribution involved in the relaxation of the probe’s
end-to-end vector in polydisperse systems. We follow the CR picture
of Viovy et al. [Macromolecules 1991, 24, 3587] and refine the effective chain friction in the thin and fat tubes
based on Read et al. [J.
Rheol. 2012, 56, 823]. The derived analytical equations form a basis for generalizing
the proposed methodology to polydisperse mixtures of linear and branched
polymers. The consistency between the SSp model and tube model predictions
is a strong indicator of the compatibility between these two distinct
mesoscopic frameworks.