Memory-induced sign reversals of the spatial cross-correlation for particles in viscoelastic shear flows

Sauga, Ako; Laas, Katrin; Mankin, Romi

doi:10.1016/j.chaos.2015.09.016

Cited by 5 publications

(3 citation statements)

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“…Mankin and co-workers studied the influence of memory on the motion of trapped Brownian particles in oscillatory viscoelastic shear flow with a power-law-type memory kernel. , Among other things, they discovered a dynamic phase transition from a trapped to a diffusive state when increasing the memory exponent. Moreover, the cross-correlation of the particle motion in flow and shear direction changed sign twice with increasing exponent.…”

Section: Physical Impact Of Memorymentioning

confidence: 99%

Introducing Memory in Coarse-Grained Molecular Simulations

et al. 2021

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Preserving the correct dynamics at the coarse-grained (CG) level is a pressing problem in the development of systematic CG models in soft matter simulation. Starting from the seminal idea of simple time-scale mapping, there have been many efforts over the years toward establishing a meticulous connection between the CG and fine-grained (FG) dynamics based on fundamental statistical mechanics approaches. One of the most successful attempts in this context has been the development of CG models based on the Mori−Zwanzig (MZ) theory, where the resulting equation of motion has the form of a generalized Langevin equation (GLE) and closely preserves the underlying FG dynamics. In this Review, we describe some of the recent studies in this regard. We focus on the construction and simulation of dynamically consistent systematic CG models based on the GLE, both in the simple Markovian limit and the non-Markovian case. Some recent studies of physical effects of memory are also discussed. The Review is aimed at summarizing recent developments in the field while highlighting the major challenges and possible future directions.

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Section: Physical Impact Of Memorymentioning

confidence: 99%

Introducing Memory in Coarse-Grained Molecular Simulations

et al. 2021

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“…This model is shown to generate signals exhibiting power-law decay in statistical properties such as the steady state probability distribution and the 1/ f β power spectrum. In paper [16] a "generalized Langevin equation with a powerlaw-type memory kernel is used to model the complex structure of the viscoelastic media". The superposition of different kind of noise terms is studied: a multiplicative white Gaussian noise, an internal fractional Gaussian noise and an additive external white noise.…”

Section: Stochastic Modeling and Noise In Complexitymentioning

confidence: 99%

“…In papers [13,14,15,16,17] the modeling approach to complexity is based on the theory of stochastic processes. All these papers, with the exception of the last one, are based on the standard or generalized Langevin equation.…”

Section: Stochastic Modeling and Noise In Complexitymentioning

confidence: 99%