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A3: Coarse-graining frequency-dependent phenomena and memory in colloidal systems

Theoretical frameworks of dynamic coarse-graining typically often assume that “fast” degrees of freedom adjust adiabatically to the instantaneous conformations of “slow” (coarse-grained) degrees of freedom. If the separation of time scales is not perfect, however, memory effects must be taken into account. In this project we will explore different strategies of implementing them, namely (i) direct reconstruction of memory kernels from time-dependent correlation function, and (ii) construction of equivalent Markovian models with additional “phantom” degrees of freedom. We will develop and test these strategies at the example of charged colloids in electrolyte solution


Frequency-dependent hydrodynamic interaction between two solid spheres
Gerhard Jung, Friederike Schmid
Physics of Fluids 29 (12), 126101 (2017);
doi:10.1063/1.5001565

Iterative Reconstruction of Memory Kernels
Gerhard Jung, Martin Hanke, Friederike Schmid
Journal of Chemical Theory and Computation 13 (6), 2481-2488 (2017);
doi:10.1021/acs.jctc.7b00274

In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations. In this article, we propose an iterative method for memory reconstruction from dynamical correlation functions. Compared to previously proposed noniterative techniques, it ensures by construction that the target correlation functions of the original fine-grained systems are reproduced accurately by the coarse-grained system, regardless of time step and discretization effects. Furthermore, we also propose a new numerical integrator for generalized Langevin equations that is significantly more accurate than the more commonly used generalization of the velocity Verlet integrator. We demonstrate the performance of the above-described methods using the example of backflow-induced memory in the Brownian diffusion of a single colloid. For this system, we are able to reconstruct realistic coarse-grained dynamics with time steps about 200 times larger than those used in the original molecular dynamics simulations.

Computing bulk and shear viscosities from simulations of fluids with dissipative and stochastic interactions
Gerhard Jung, Friederike Schmid
The Journal of Chemical Physics 144 (20), 204104 (2016);
doi:10.1063/1.4950760

Exact values for bulk and shear viscosity are important to characterize a fluid, and they are a necessary input for a continuum description. Here we present two novel methods to compute bulk viscosities by non-equilibrium molecular dynamics simulations of steady-state systems with periodic boundary conditions — one based on frequent particle displacements and one based on the application of external bulk forces with an inhomogeneous force profile. In equilibrium simulations, viscosities can be determined from the stress tensor fluctuations via Green-Kubo relations; however, the correct incorporation of random and dissipative forces is not obvious. We discuss different expressions proposed in the literature and test them at the example of a dissipative particle dynamics fluid.

Flows and mixing in channels with misaligned superhydrophobic walls
Tatiana V. Nizkaya, Evgeny S. Asmolov, Jiajia Zhou, Friederike Schmid, Olga I. Vinogradova
Physical Review E 91 (3), (2015);
doi:10.1103/physreve.91.033020

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