Simulation of claylike colloids

Hecht, Martin; Harting, Jens; Ihle, Thomas; Herrmann, Hans J.

doi:10.1103/physreve.72.011408

Cited by 134 publications

(237 citation statements)

References 33 publications

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“…(More extensive discussions of SRD (25,27) and MPC (28) can be found elsewhere.) These methods represent the fluid with a number of tracer particles whose dynamics conserve mesoscopic hydrodynamic flows.…”

Section: Srd Dynamicsmentioning

confidence: 99%

“…The algorithm presented here requires a thermostat that conserves the mesoscopic flow field-i.e., the mean collision cell momenta-while maintaining the proper thermodynamic ensemble. For MPC algorithms, these conditions are satisfied by a Monte Carlo-type thermostat similar to that described in (25), which operates on each collision cell independently in the following manner. A scaling factor, S, is chosen, with equal probability, to be either ð1 þ εÞ or ð1 þ εÞ À1 , where ε is an input parameter significantly less than one.…”

Section: Lipid-srd Interactionsmentioning

confidence: 99%

“…This thermostat produces an ensemble of SRD particles with a Maxwellian velocity distribution (25). The thermostat, with ε ¼ 0.1, is applied to the SRD particles immediately after each collision step.…”

Section: Lipid-srd Interactionsmentioning

confidence: 99%

“…Constant-temperature schemes that involve gross randomization of velocities must be avoided, as such algorithms do not locally preserve momenta, as required to capture hydrodynamic flows (24). SRD particles are subject to a separate thermostat (25) that conserves mesoscopic hydrodynamic flows, described in more detail below. Simulations are run at constant volume, at an area chosen to enforce zero surface tension.…”

Section: Molecular Dynamicsmentioning

confidence: 99%

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Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini

Zgorski

Lyman

2016

Biophysical Journal

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Solvent hydrodynamics are incorporated into simulations of the solvent-free Dry Martini model. The solvent hydrodynamics are modeled with the stochastic rotation dynamics (SRD) algorithm, a particle-based method for resolving fluid hydrodynamics. SRD does not require calculation of particle-particle distances in the solvent, and so is scalable to arbitrary volumes of solvent with minimal additional computational overhead. The viscosity of the solvent is easily tuned via parameters of the algorithm to span an order of magnitude in viscosity around the viscosity of water at room temperature. The combination ''Stochastic Thermostatted Rotation Dynamics (STRD) with Martini'' was implemented in Gromacs v.5.01. Simulations of an SRD/palmitoyloleoylphosphatidylcholine membrane demonstrate that the solvent may be included without reparametrizing the lipid model, with minimal perturbation to the thermodynamics. A recent generalization of Saffman-Delbruck theory to periodic geometries by Camley and Brown indicates that lipid dynamics are contaminated by a finite-size effect in typical molecular dynamics (MD) simulations, and that very large systems are required for quantitative simulation of dynamics. Analysis of lipid translational diffusion in this work shows good agreement with the theory, and with explicitly solvated simulations. This indicates that STRD Martini is a viable approach for quantitative simulation of membrane dynamics and does not require massive computational overhead to model the solvent.

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Section: Srd Dynamicsmentioning

confidence: 99%

Section: Lipid-srd Interactionsmentioning

confidence: 99%

Section: Lipid-srd Interactionsmentioning

confidence: 99%

Section: Molecular Dynamicsmentioning

confidence: 99%

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Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini

Zgorski

Lyman

2016

Biophysical Journal

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“…An important advantage of SRD is that its simplified dynamics has enabled the analytical calculation of the transport coefficients and made it possible to obtain a rather complete theoretical understanding of the time-dependent correlation functions, the relaxation to equilibrium [4,5], and the behavior in shear flow, including shear thinning at high shear rates [6]. Because the algorithm correctly includes long-ranged hydrodynamic interactions and Brownian fluctuations-both of which are generally required for a proper statistical treatment of the dynamics of mesoscopic suspended particles-it has been used to study the behavior of polymers [7,8,9], colloids [10,11], including sedimentation [12,13,14], and vesicles in flow [15,16].…”

Section: Introductionmentioning

confidence: 99%

Dynamic correlations in stochastic rotation dynamics

2006

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The dynamic structure factor, vorticity and entropy density dynamic correlation functions are measured for Stochastic Rotation Dynamics (SRD), a particle based algorithm for fluctuating fluids. This allows us to obtain unbiased values for the longitudinal transport coefficients such as thermal diffusivity and bulk viscosity. The results are in good agreement with earlier numerical and theoretical results, and it is shown for the first time that the bulk viscosity is indeed zero for this algorithm. In addition, corrections to the self-diffusion coefficient and shear viscosity arising from the breakdown of the molecular chaos approximation at small mean free paths are analyzed. In addition to deriving the form of the leading correlation corrections to these transport coefficients, the probabilities that two and three particles remain collision partners for consecutive time steps are derived analytically in the limit of small mean free path. The results of this paper verify that we have an excellent understanding of the SRD algorithm at the kinetic level and that analytic expressions for the transport coefficients derived elsewhere do indeed provide a very accurate description of the SRD fluid.

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Multiparticle Collision Dynamics: Simulation of Complex Systems on Mesoscales

Kapral

2008

Advances in Chemical Physics

312

303

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Complex systems can display complex phenomena that are not easily described at a microscopic level using molecular dynamics simulation methods. Systems may be complex because some or all of their constituents are complex molecular species, such as polymers, large biomolecules, or other molecular aggregates. Such systems can exhibit the formation of patterns arising from segregation of constituents or nonequilibrium effects and molecular shape changes induced by flows and hydrodynamic interactions. Even when the constituents are simple molecular entities, turbulent fluid motions can exist over a range of length and time scales.Many of these phenomena have their origins in interactions at the molecular level but manifest themselves over mesoscopic and macroscopic space and time scales. These features make the direct simulation of such systems difficult because one must follow the motions of very large numbers of particles over very long times. These considerations have prompted the development of coarse-grain methods that simplify the dynamics or the system in different ways in order to be able to explore longer length and time scales. The use of mesoscopic dynamical descriptions dates from the foundations of nonequilibrium statistical mechanics. The Boltzmann equation [1] provides a field description on times greater than the time of a collision and the Langevin equation [2] replaces a molecular-level treatment of the solvent with a stochastic description of its properties.The impetus to develop new types of coarse-grain or mesoscopic simulation methods stems from the need to understand and compute the dynamical properties of large complex systems. The method of choice usually depends on the type of information that is desired. If properties that vary on very long distance and time scales are of interest, the nature of the dynamics can be altered, while still preserving essential features to provide a faithful representation of these properties. For example, fluid flows described by the Navier-Stokes equations will result from dynamical schemes that preserve the basic conservation laws of mass, momentum, and energy. The details of the molecular interactions may be unimportant for such applications. Some coarsegrain approaches constructed in this spirit, such as the lattice Boltzmann method [3] and direct simulation Monte Carlo [4], are based on the Boltzmann equation. In dissipative particle dynamics [5, 6], several atoms are grouped into simulation sites whose dynamics is governed by conservative and frictional 90 raymond kapral 92 raymond kapral

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Simulation of claylike colloids

Cited by 134 publications

References 33 publications

Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini

Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini

Dynamic correlations in stochastic rotation dynamics

Multiparticle Collision Dynamics: Simulation of Complex Systems on Mesoscales

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