Relaxation by reptation and tube enlargement: A model for polydisperse polymers

Marrucci, G.

doi:10.1002/pol.1985.180230115

Cited by 288 publications

(389 citation statements)

References 15 publications

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“…Figure 19 shows the tube survivability, Ψ (t), zero-rate shear viscosity, η 0 , and the storage, G (ω), and loss, G (ω), moduli of PE (C 500 H 1002 ) polymer melts at 450 K. In Figure 19a, the Ψ (t) is compared with the double reptation model [295,296] and dual constraint model [297,298]. Although all three of these models give similar trends in Ψ(t), the double reptation model is found to overestimate the data obtained by direct PP analysis, due to the neglect of the CLF effect, while the dual constraint model is found to underestimate the data given by the PP analysis, due to the overestimation of CLF effect.…”

Section: Dynamic Mapping Onto Tube Modelmentioning

confidence: 99%

“…Figure 19. Results of (a) tube survivability function, Ψ (t); (b) zero-rate shear viscosity, η 0 ; (c) storage, G (ω), modulus; and (d) loss, G (ω), modulus of PE (C 500 H 1002 ) polymer melts at 450 K. In (a), (c) and (d), the double reptation and dual constraint models are given by [295,296] and [297,298], respectively. In (b), the unfilled symbols are given by experiments.…”

Section: Dynamic Mapping Onto Tube Modelmentioning

confidence: 99%

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Challenges in Multiscale Modeling of Polymer Dynamics

et al. 2013

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The mechanical and physical properties of polymeric materials originate from the interplay of phenomena at different spatial and temporal scales. As such, it is necessary to adopt multiscale techniques when modeling polymeric materials in order to account for all important mechanisms. Over the past two decades, a number of different multiscale computational techniques have been developed that can be divided into three categories: (i) coarse-graining methods for generic polymers; (ii) systematic coarse-graining methods and (iii) multiple-scale-bridging methods. In this work, we discuss and compare eleven different multiscale computational techniques falling under these categories and assess them critically according to their ability to provide a rigorous link between polymer chemistry and rheological material properties. For each technique, the fundamental ideas and equations are introduced, and the most important results or predictions are shown and discussed. On the one hand, this review provides a comprehensive tutorial on multiscale computational techniques, which will be of interest to readers newly entering this field; on the other, it presents a critical discussion of the future opportunities and key challenges in the multiscale geometric mapping matrix between all-atomistic and coarse-grained models N number of monomers per chain N e entanglement length, which is the number of monomers between two entanglements n v number of polymer chains per unit volume n ij (n 0 (r ij )) entanglement number (at equilibrium) between particle pairs i and j p r , P R configurational probability distributions in all-atomistic and coarse-grained models, respectively R ee end-to-end distance of polymer chain R G radius of gyration of polymer chain s segment index/contour length variable along primitive chain S(q) single chain coherent dynamic scattering function Z number of entanglements per chain, defined as Z = N/N e α exponent in standard Mittag-Leffler function σ

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Section: Dynamic Mapping Onto Tube Modelmentioning

confidence: 99%

Section: Dynamic Mapping Onto Tube Modelmentioning

confidence: 99%

Challenges in Multiscale Modeling of Polymer Dynamics

et al. 2013

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“…Two main boosts in the tube motion were proposed: a constraint released (CR) mechanism de Gennes (1975) and a dynamic tube dilation (DTD) mechanism by Marrucci (1985). The first mechanism is activated by the slow tube dynamic in which some of the entaglements' constraints along the chain are re-leased allowing more freedom in the lateral movements of the test chain.…”

Section: Introductionmentioning

confidence: 99%

Stress relaxation of bi-disperse polystyrene melts

et al. 2016

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We present start-up of uniaxial extension followed by stress relaxation experiments of a bi-disperse 50% by weight blend of 95k and 545k molecular weight polystyrene. We also show, for comparison, stress relaxation measurements of the polystyrene melts with molecular weight 95k and 545k, which are the components of the bi-disperse melt. The measurements show three separated relaxation regimes: a fast regime, a transition regime and a slow regime. In the fast regime the orientation of the long chains is frozen and the stress relaxation is due to stretch relaxation of the short chains primarily. Conversely in the slow regime the long chains have retracted and undergo relaxation of orientation in fully relaxed short chains.

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“…We refer to these models as tube rearrangement models. An alternative picture for modeling the effect of constraint release (CR) on stress relaxation was introduced by Marrucci 17 . Marrucci suggested the previously relaxed fraction of the melt should be considered as an effective solvent for still oriented chain segments.…”

Section: Introductionmentioning

confidence: 99%

Understanding Effect of Constraint Release Environment on End-to-End Vector Relaxation of Linear Polymer Chains

et al. 2017

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In this study we propose and verify methods based on the slip-spring (SSp) model (Likhtman, 2005) 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 2 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., 1991) and refine the effective chain friction in the thin and fat tubes based on (Read et al., 2012). The derived analytical equations form a basis for generalizing the proposed methodology to polydisperse mixtures of linear and branched polymers. The consistency between the the SSp model and tube model predictions is a strong indicator of the compatibility between these two distinct mesoscopic frameworks.

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Relaxation by reptation and tube enlargement: A model for polydisperse polymers

Cited by 288 publications

References 15 publications

Challenges in Multiscale Modeling of Polymer Dynamics

Challenges in Multiscale Modeling of Polymer Dynamics

Stress relaxation of bi-disperse polystyrene melts

Understanding Effect of Constraint Release Environment on End-to-End Vector Relaxation of Linear Polymer Chains

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