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Insights from modeling into structure, entanglements, and dynamics in attractive polymer nanocomposites

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Abstract

Conformations, entanglements and dynamics in attractive polymer nanocomposites are investigated in this work by means of coarse-grained molecular dynamics simulation, for both weak and strong confinements, in the presence of nanoparticles (NPs) at NP volume fractions ϕ up to 60%. We show that the behavior of the apparent tube diameter dapp in such nanocomposites can be greatly different from nanocomposites with nonattractive interactions. We find that this effect originates, based on a mean field argument, from the geometric confinement length dgeo at strong confinement (large ϕ) and not from the bound polymer layer on NPs (interparticle distance ID <2Rg) as proposed recently based on experimental measurements. Close to the NP surface, the entangled polymer mobility is reduced in attractive nanocomposites but still faster than the NP mobility for volume fractions beyond 20%. Furthermore, entangled polymer dynamics is hindered dramatically by the strong confinement created by NPs. For the first time using simulations, we show that the entangled polymer conformation, characterized by the polymer radius of gyration Rg and form factor, remains basically unperturbed by the presence of NPs up to the highest volume fractions studied, in agreement with various experiments on attractive nanocomposites. As a side-result we demonstrate that the loose concept of ID can be made a microscopically well defined quantity using the mean pore size of the NP arrangement.

Graphical abstract: Insights from modeling into structure, entanglements, and dynamics in attractive polymer nanocomposites

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Article information


Submitted
08 May 2021
Accepted
08 Jun 2021
First published
09 Jun 2021

This article is Open Access

Soft Matter, 2021, Advance Article
Article type
Paper

Insights from modeling into structure, entanglements, and dynamics in attractive polymer nanocomposites

A. Moghimikheirabadi, M. Kröger and A. V. Karatrantos, Soft Matter, 2021, Advance Article , DOI: 10.1039/D1SM00683E

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