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Equilibration of long chain polymer melts in computer simulations

Open access
Auhl, Rolf, Everaers, Ralf, Grest, Gary S., Kremer, Kurt, Plimpton, Steven J.·2003·The Journal of Chemical Physics

Abstract

Several methods for preparing well equilibrated melts of long chains polymers are studied. We show that the standard method in which one starts with an ensemble of chains with the correct end-to-end distance arranged randomly in the simulation cell and introduces the excluded volume rapidly, leads to deformation on short length scales. This deformation is strongest for long chains and relaxes only after the chains have moved their own size. Two methods are shown to overcome this local deformation of the chains. One method is to first pre-pack the Gaussian chains, which reduces the density fluctuations in the system, followed by a gradual introduction of the excluded volume. The second method is a double-bridging algorithm in which new bonds are formed across a pair of chains, creating two new chains each substantially different from the original. We demonstrate the effectiveness of these methods for a linear bead spring polymer model with both zero and nonzero bending stiffness, however the methods are applicable to more complex architectures such as branched and star polymer.

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Metadata

Authors
Auhl, R., Everaers, R., Grest, G. S., Kremer, K., & Plimpton, S. J.
Venue
The Journal of Chemical Physics
Published
2003-12-22
Volume
119
Issue
24
Pages
12718-12728
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W2062618849
Cited by
575
References
4
FWCI
7.19
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Equilibration of long chain polymer melts in computer simulations. https://app.cochat.ai/papers/10.1063/1.1628670
The paper
Auhl, R., Everaers, R., Grest, G. S., Kremer, K., & Plimpton, S. J. (2003). Equilibration of long chain polymer melts in computer simulations. The Journal of Chemical Physics. https://doi.org/10.1063/1.1628670

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.