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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
Published on: September 26, 2016
Reentanglement dynamics of a highly stretched polymer chain in fixed networks and polymer melts
Nuofei Jiang1, Evelyne van Ruymbeke1
1Bio and Soft Matter, Institute on Condensed Matter and Nano-science, Université Catholique de Louvain, Louvain-la-Neuve 1348, Belgium. nuofei.jiang@uclouvain.be.
Abstract:
The reentanglement dynamics of a polymer melt which is well entangled at equilibrium but becomes disentangled after large deformation represent a key aspect of polymer entanglement dynamics that cannot be addressed from the classic reptation model that assumes constant topological constraints. In this work, we contribute to this subject by presenting a comprehensive comparison of reentanglement dynamics between a highly stretched polymer probe in fixed networks and polymer melts containing equally stretched chains, from theoretical analysis and computer simulations. Whereas the relaxation of a polymer probe in networks can be well explained by the reptation theory, a new theoretical picture is proposed to describe the reentanglement process of a polymer melt, which predicts a relaxation pathway distinct from the network case. Nevertheless, the full recovery time in the melt remains consistent with the disentanglement time. These theoretical predictions are subsequently tested against two sets of simulations. Our single-chain Langevin simulations in networks show quantitative agreement with reptation theory for both equilibrium and reentanglement dynamics. In contrast, multi-chain melt simulations confirm qualitative differences from the network case when relaxing from a highly stretched state, consistent with our theoretical predictions. Other similarities and distinctions are examined through primitive path analysis and stress relaxation. Overall, our combined theoretical and simulation results enhance the understanding of experimental observations of reentanglement dynamics and provide new insights into out-of-equilibrium behavior across multiple time scales.
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