0000000000338025

AUTHOR

Gerhard Jung

0000-0002-6739-1603

showing 9 related works from this author

Computing bulk and shear viscosities from simulations of fluids with dissipative and stochastic interactions

2016

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 (NEMD) 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 pro…

PhysicsCauchy stress tensorForce profileShear viscosityDissipative particle dynamicsGeneral Physics and AstronomyFOS: Physical sciences02 engineering and technologyMechanicsCondensed Matter - Soft Condensed Matter021001 nanoscience & nanotechnology01 natural sciencesMolecular dynamicsShear (geology)0103 physical sciencesDissipative systemPeriodic boundary conditionsSoft Condensed Matter (cond-mat.soft)Physical and Theoretical Chemistry010306 general physics0210 nano-technology
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Generalized Langevin dynamics: construction and numerical integration of non-Markovian particle-based models.

2018

We propose a generalized Langevin dynamics (GLD) technique to construct non-Markovian particle-based coarse-grained models from fine-grained reference simulations and to efficiently integrate them. The proposed GLD model has the form of a discretized generalized Langevin equation with distance-dependent two-particle contributions to the self- and pair-memory kernels. The memory kernels are iteratively reconstructed from the dynamical correlation functions of an underlying fine-grained system. We develop a simulation algorithm for this class of non-Markovian models that scales linearly with the number of coarse-grained particles. Our GLD method is suitable for coarse-grained studies of syste…

PhysicsSpeedup010304 chemical physicsDiscretizationFOS: Physical sciencesMarkov processGeneral ChemistryCondensed Matter - Soft Condensed MatterComputational Physics (physics.comp-ph)Condensed Matter Physics01 natural sciencesNumerical integrationsymbols.namesake0103 physical sciencessymbolsSoft Condensed Matter (cond-mat.soft)ParticleSoft matterStatistical physics010306 general physicsLangevin dynamicsPhysics - Computational PhysicsOrder of magnitudeSoft matter
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Frequency-dependent hydrodynamic interaction between two solid spheres

2017

Hydrodynamic interactions play an important role in many areas of soft matter science. In simulations with implicit solvent, various techniques such as Brownian or Stokesian dynamics explicitly include hydrodynamic interactions a posteriori by using hydrodynamic diffusion tensors derived from the Stokes equation. However, this equation assumes the interaction to be instantaneous which is an idealized approximation and only valid on long time scales. In the present paper, we go one step further and analyze the time-dependence of hydrodynamic interactions in a compressible fluid on the basis of the linearized Navier-Stokes equation. The theoretical results show that the compressibility of the…

Fluid Flow and Transfer ProcessesPhysics010304 chemical physicsStokesian dynamicsMechanical EngineeringComputational MechanicsFOS: Physical sciencesMechanicsCondensed Matter - Soft Condensed MatterStokes flowCondensed Matter Physics01 natural sciencesCompressible flow010305 fluids & plasmasMolecular dynamicsMechanics of Materials0103 physical sciencesCompressibilitySoft Condensed Matter (cond-mat.soft)Hydrodynamic theoryNavier–Stokes equationsBrownian motionPhysics of Fluids
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Introducing Memory in Coarse-Grained Molecular Simulations

2021

[Image: see text] 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…

010304 chemical physicsComputer scienceMarkov processEquations of motionContext (language use)Statistical mechanics010402 general chemistry01 natural sciencesField (computer science)0104 chemical sciencesSurfaces Coatings and Filmssymbols.namesakeSimple (abstract algebra)0103 physical sciencesMaterials ChemistrysymbolsStatistical physicsLimit (mathematics)Physical and Theoretical ChemistryFocus (optics)
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Correction: Generalized Langevin dynamics: construction and numerical integration of non-Markovian particle-based models.

2018

Correction for ‘Generalized Langevin dynamics: construction and numerical integration of non-Markovian particle-based models’ by Gerhard Jung et al., Soft Matter, 2018, DOI: 10.1039/c8sm01817k.

Physicssymbols.namesakesymbolsMarkov processParticleGeneral ChemistrySoft matterStatistical physicsCondensed Matter PhysicsLangevin dynamicsNumerical integrationSoft matter
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Wall slip and bulk yielding in soft particle suspensions

2021

We simulate a dense athermal suspension of soft particles sheared between hard walls of a prescribed roughness profile, using a method that fully accounts for the fluid mechanics of the solvent between the particles, and between the particles and the walls, as well as for the solid mechanics of changes in the particle shapes. We thus capture the widely observed phenomenon of elastohydrodynamic wall slip, in which the soft particles become deformed in shear and lift away from the wall slightly, leaving behind a thin lubricating solvent layer of high shear. For imposed stresses below the material's bulk yield stress, we show the observed wall slip to be dominated by this thin solvent layer. A…

Materials scienceMechanical EngineeringFOS: Physical sciencesFluid mechanicsSlip (materials science)MechanicsCondensed Matter - Soft Condensed MatterCondensed Matter PhysicsSuspension (chemistry)Shear (sheet metal)Condensed Matter::Soft Condensed MatterPhysics::Fluid DynamicsRheologyMechanics of MaterialsSolid mechanicsShear stressParticleSoft Condensed Matter (cond-mat.soft)General Materials Science
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Model reduction techniques for the computation of extended Markov parameterizations for generalized Langevin equations

2021

Abstract The generalized Langevin equation is a model for the motion of coarse-grained particles where dissipative forces are represented by a memory term. The numerical realization of such a model requires the implementation of a stochastic delay-differential equation and the estimation of a corresponding memory kernel. Here we develop a new approach for computing a data-driven Markov model for the motion of the particles, given equidistant samples of their velocity autocorrelation function. Our method bypasses the determination of the underlying memory kernel by representing it via up to about twenty auxiliary variables. The algorithm is based on a sophisticated variant of the Prony metho…

Markov chainComputer scienceAutocorrelationFOS: Physical sciences02 engineering and technologyCondensed Matter - Soft Condensed Matter021001 nanoscience & nanotechnologyCondensed Matter PhysicsMarkov model01 natural sciencesExponential functionKernel (statistics)0103 physical sciencesProny's methodApplied mathematicsSoft Condensed Matter (cond-mat.soft)General Materials Science010306 general physics0210 nano-technologyRealization (systems)Interpolation
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Frequency-Dependent Dielectric Polarizability of Flexible Polyelectrolytes in Electrolyte Solution: A Dissipative Particle Dynamics Simulation

2019

Materials scienceRenewable Energy Sustainability and the EnvironmentChemical physicsPolarizabilityDissipative particle dynamicsMaterials ChemistryElectrochemistryElectrolyteDielectricCondensed Matter PhysicsPolyelectrolyteSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsJournal of The Electrochemical Society
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Iterative Reconstruction of Memory Kernels.

2017

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 disc…

Mathematical optimization010304 chemical physicsDiscretizationGeneralizationComputer scienceIterative methodFOS: Physical sciences02 engineering and technologyIterative reconstructionConstruct (python library)Condensed Matter - Soft Condensed Matter021001 nanoscience & nanotechnology01 natural sciencesComputer Science ApplicationsKernel (image processing)Integrator0103 physical sciencesVerlet integrationSoft Condensed Matter (cond-mat.soft)Physical and Theoretical Chemistry0210 nano-technologyAlgorithmJournal of chemical theory and computation
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