Rheological predictions of network systems swollen with entangled solvent

Katzarova, Maria; Andreev, Marat; Sliozberg, Yelena R.; Mrozek, Randy A.; Lenhart, Joseph L.; Andzelm, Jan; Schieber, Jay D.

doi:10.1002/aic.14370

Cited by 16 publications

(9 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An unknown fraction of network imperfections allowed only qualitative agreement with experimental observations. Katzarova et al (2014) were able to estimate composition and predict nonlinear rheology of swollen network using DSM. Andreev et al (2013) showed that the DSM can be applied without any adjustments to shear flow and yield agreement over a wide range of deformation rates, while agreement with elongational flow data at large strains remains elusive.…”

Section: Introductionmentioning

confidence: 99%

Universality and speedup in equilibrium and nonlinear rheology predictions of the fixed slip-link model

Andreev¹,

Feng²,

Yang³

et al. 2014

Journal of Rheology

Self Cite

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Universality and speedup in equilibrium and nonlinear rheology predictions of the fixed slip-link model

Andreev¹,

Feng²,

Yang³

et al. 2014

Journal of Rheology

Self Cite

View full text Add to dashboard Cite

“…Typically, they either i) directly sample an ensemble of n c polymers from the target MWD (the subscript "c" stands for chains), [14][15][16][17] or ii) consider a BMF with n f fractions that is derived from the MWD. [18][19][20][21] In the limit of large n c or n f , both approximations converge to the expected polydisperse behavior.…”

Section: Polydispersity In Molecular Simulationsmentioning

confidence: 64%

How Many Monodisperse Fractions are Required to Discretize Polydisperse Polymers?

Shanbhag

2020

Macro Theory & Simulations

View full text Add to dashboard Cite

The linear viscoelasticity of polydisperse samples and their discretization into a blend of nf monodisperse fractions is compared. The molecular weight distribution of the polydisperse sample is described using a lognormal distribution, which has two parameters that are related to the weight‐averaged molecular weight, Zw, and the polydispersity index, ρ. Due to its success on similar systems, a variant of the double reptation model is used to describe the linear rheology. Given Zw and ρ, the optimal number of monodisperse fractions nf∗ is obtained using the Bayesian information criterion. It quantifies and negotiates the tradeoff between accuracy (discrepancy with the response of the polydisperse sample) and complexity (number of fractions). The optimal number of fractions was found to be somewhat insensitive to Zw; however, it increased with ρ from about 6 for ρ = 1.01 to about 20 for ρ = 2.0. Changing the underlying viscoelastic model had only a weak effect on the conclusions. Furthermore, using a blend of monodisperse fractions was found to be preferable to direct sampling even when an ensemble of chains was requested.

show abstract

“…Popular implementations of the TM deal with polydispersity by creating an ensemble of chains from the MWD [37][38][39]. The same approach can be employed with multi-chain SLMs, although it is less common due to increased computational cost [26,[40][41][42]. Recent work on discretizing nearly monodisperse MWD (polydispersity index 1.1) recommends using a "blend of monodisperse fractions" of f = 5 − 10 suitably selected chain lengths [43].…”

Section: The Problem With Polydispersitymentioning

confidence: 99%

Temporal Coarse-Graining in a Slip Link Model for Polydisperse Polymer Melts

Shanbhag

2020

Front. Phys.

View full text Add to dashboard Cite

For ecoSLM-an ultra coarse-grained slip link model-the ability to use a time-step that increases with chain molecular weight is an important source of efficiency in modeling the linear rheology of monodisperse chains. This feature is labeled "temporal coarse-graining" in this paper. It is compromised for blends of linear chains, where the time-step is set by the short chains, but the length of the simulation run is determined by the long chains. The problem is present for any polydisperse sample, and is particularly acute for binary blends with widely separated molecular weights. To recover temporal coarse-graining, we propose an adaptive time-step algorithm, where the time-step is determined by the shortest unrelaxed chains in the ensemble, which increases as the simulation proceeds. It involves two additional steps: recalibration, which is triggered when any component relaxes completely, and re-equilibration, in which slip links on completely relaxed components are renewed. We obtain reasonable settings for these steps, and validate the adaptive time-step algorithm by comparing it with the original, constant time-step ecoSLM for binary, ternary, and polydisperse blends. Speedups ranging from 50 to 1,500% are obtained when molecular weights of the components are widely separated, without a significant loss of accuracy. Conversely, the adaptive time-step algorithm is not recommended when molecular weights are not well-separated, since it can be slower than the constant time-step method.

show abstract

Rheological predictions of network systems swollen with entangled solvent

Cited by 16 publications

References 26 publications

Universality and speedup in equilibrium and nonlinear rheology predictions of the fixed slip-link model

Universality and speedup in equilibrium and nonlinear rheology predictions of the fixed slip-link model

How Many Monodisperse Fractions are Required to Discretize Polydisperse Polymers?

Temporal Coarse-Graining in a Slip Link Model for Polydisperse Polymer Melts

Contact Info

Product

Resources

About