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Macromolecules
Article . 2003 . Peer-reviewed
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Segmental Dynamics in Miscible Polymer Blends: Modeling the Combined Effects of Chain Connectivity and Concentration Fluctuations

Authors: Eric Leroy; Juan Colmenero; A. Alegría;

Segmental Dynamics in Miscible Polymer Blends: Modeling the Combined Effects of Chain Connectivity and Concentration Fluctuations

Abstract

The dynamic heterogeneity of the segmental dynamics in miscible polymer blends has been alternatively interpreted in terms of either chain connectivity effects or thermal concentration fluctuations. Taking into account that both phenomena seem to be relevant, in this work we propose a minimal model which combines these two effects. This model basically assumes the self-concentration approach recently proposed by Lodge and McLeish [Macromolecules2000, 33, 5278] and introduces a distribution of the effective concentration around a given segment mainly due to the effect of thermal concentration fluctuations. The proposed model has been checked in two blend systems, PVME/PS and PoCLS/PS700. Each of these systems allows to selectively observe by dielectric spectroscopy either the low- or high-glass transition temperature component of the blend, respectively. The model provides a good quantitative description of the dielectric segmental relaxation in both cases with only one free parameter: the variance of the distribution of the effective concentration. This parameter results to be hardly dependent on temperature, at least in the two blends investigated.

The authors acknowledge the Basque Country Government (Project 9/UPV 00206.215-13568/2001) and the Spanish Ministry of Science and Technology (Project MAT 2001/0070) for their support.

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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).
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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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