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Energy Renormalization Method for the Coarse-Graining of Polymer Viscoelasticity.


ABSTRACT: Developing temperature transferable coarse-grained (CG) models is essential for the computational prediction of polymeric glass-forming (GF) material behavior, but their dynamics are often greatly altered from those of all-atom (AA) models mainly because of the reduced fluid configurational entropy under coarse-graining. To address this issue, we have recently introduced an energy renormalization (ER) strategy that corrects the activation free energy of the CG polymer model by renormalizing the cohesive interaction strength ? as a function of temperature T, i.e., ?(T), thus semiempirically preserving the T-dependent dynamics of the AA model. Here we apply our ER method to consider-in addition to T-dependency-the frequency f-dependent polymer viscoelasticity. Through smallamplitude oscillatory shear molecular dynamics simulations, we show that changing the imposed oscillation f on the CG systems requires changes in ? values (i.e., ?(T, f)) to reproduce the AA viscoelasticity. By accounting for the dynamic fragility of polymers as a material parameter, we are able to predict ?(T, f) under coarse-graining in order to capture the AA viscoelasticity, and consequently the activation energy, across a wide range of T and f in the GF regime. Specifically, we showcase our achievements on two representative polymers of distinct fragilities, polybutadiene (PB) and polystyrene (PS), and show that our CG models are able to sample viscoelasticity up to the megahertz regime, which approaches state-of-the-art experimental resolutions, and capture results sampled via AA simulations and prior experiments.

SUBMITTER: Song J 

PROVIDER: S-EPMC6463302 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Energy Renormalization Method for the Coarse-Graining of Polymer Viscoelasticity.

Song Jake J   Hsu David D DD   Shull Kenneth R KR   Phelan Frederick R FR   Douglas Jack F JF   Xia Wenjie W   Keten Sinan S  

Macromolecules 20180101


Developing temperature transferable coarse-grained (CG) models is essential for the computational prediction of polymeric glass-forming (GF) material behavior, but their dynamics are often greatly altered from those of all-atom (AA) models mainly because of the reduced fluid configurational entropy under coarse-graining. To address this issue, we have recently introduced an energy renormalization (ER) strategy that corrects the activation free energy of the CG polymer model by renormalizing the  ...[more]

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