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Related papers: Coarse-Graining and Scaling in Dissipative Particl…

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Dissipative particle dynamics (DPD) belongs to a class of models and computational algorithms developed to address mesoscale problems in complex fluids and soft matter in general. It is based on the notion of particles that represent…

Statistical Mechanics · Physics 2017-05-24 Pep Español , Patrick B Warren

Dissipative particle dynamics (DPD) is a well-established mesoscale simulation method. However, there have been long-standing ambiguities regarding the dependence of its (purely repulsive) force field parameter on temperature as well as the…

Chemical Physics · Physics 2019-02-25 Peter Vanya , Jonathan Sharman , James A. Elliott

We present a promising coarse-graining strategy for linking micro- and mesoscales of soft matter systems. The approach is based on effective pairwise interaction potentials obtained from detailed atomistic molecular dynamics (MD)…

Soft Condensed Matter · Physics 2007-05-23 A. P. Lyubartsev , M. Karttunen , I. Vattulainen , A. Laaksonen

Dissipative particle dynamics (DPD) is a novel particle method for mesoscale modeling of complex fluids. DPD particles are often thought to represent packets of real atoms, and the physical scale probed in DPD models are determined by the…

Chemical Physics · Physics 2016-10-18 R. Qiao , P. He

Dissipative particle dynamics (DPD) is an effective mesoscopic particle model with a lower computational cost than molecular dynamics because of the soft potentials that it employs. However, the soft potential is not strong enough to…

Computational Physics · Physics 2018-07-27 Zhijie Xu , Paul Meakin

We develop a computational method based on Dissipative Particle Dynamics (DPD) that introduces solvent hydrodynamic interactions to coarse-grained models of solutes, such as ions, molecules, or polymers. DPD-solvent (DPDS) is a fully…

Soft Condensed Matter · Physics 2024-05-24 Tine Curk

Dissipative particle dynamics (DPD) is a relatively new technique which has proved successful in the simulation of complex fluids. We caution that for the equilibrium achieved by the DPD simulation of a simple fluid the temperature depends…

Statistical Mechanics · Physics 2009-10-30 C. A. Marsh , J. M. Yeomans

We study numerical methods for dissipative particle dynamics (DPD), which is a system of stochastic differential equations and a popular stochastic momentum-conserving thermostat for simulating complex hydrodynamic behavior at mesoscales.…

Numerical Analysis · Mathematics 2021-06-08 Xiaocheng Shang

Understanding the complex viscoelastic properties of polymeric liquids remains a challenge in materials science and soft matter physics. Here, we present a simple and computationally efficient criterion for the topological constraints in…

Soft Condensed Matter · Physics 2007-05-23 P. Nikunen , I. Vattulainen , M. Karttunen

We introduce a framework for model reduction of chain models for dissipative particle dynamics (DPD) simulations, where the characteristic size of the chain, pressure, density, and temperature are preserved. The proposed methodology reduces…

Soft Condensed Matter · Physics 2016-05-04 Nicolas Moreno , Suzana P. Nunes , Victor M. Calo

Smoothed Dissipative Particle Dynamics (SDPD) is a mesoscopic particle method which allows to select the level of resolution at which a fluid is simulated. The numerical integration of its equations of motion still suffers from the lack of…

Statistical Mechanics · Physics 2017-10-25 Gérôme Faure , Gabriel Stoltz

Particle methods are less computationally efficient than grid based numerical solution of the Navier Stokes equation. However, they have important advantages including rigorous mass conservation, momentum conservation and isotropy. In…

Fluid Dynamics · Physics 2024-06-26 Paul Meakin , Zhijie Xu

Smoothed dissipative particle dynamics (SDPD) is a widely used particle-based method for modelling soft matter systems at mesoscopic and macroscopic scales, offering thermodynamic consistency and direct control over the fluid's transport…

Fluid Dynamics · Physics 2025-10-22 Marina Echeverria Ferrero , Nicolas Moreno , Marco Ellero

We derive a mesoscopic modeling and simulation technique that is very close to the technique known as dissipative particle dynamics. The model is derived from molecular dynamics by means of a systematic coarse-graining procedure. Thus the…

Soft Condensed Matter · Physics 2009-10-31 Eirik G. Flekkoy , Peter V. Coveney , Gianni De Fabritiis

Smoothed Dissipative Particle Dynamics (SDPD) is a mesoscopic method which allows to select the level of resolution at which a fluid is simulated. In this work, we study the consistency of the resulting thermodynamic properties as a…

Statistical Mechanics · Physics 2016-10-19 G. Faure , J. Roussel , J. -B. Maillet , G. Stoltz

Modelling micro- and meso-scopic scale thermodynamic and transport properties of soft condensed matter hinges upon its representation. This is especially relevant for polar solvents such as water, since these require effective…

Soft Condensed Matter · Physics 2026-04-17 Michael A. Seaton , Benjamin T. Speake , Ilian T. Todorov

Smoothed Dissipative Particle Dynamics (SDPD) is a mesoscopic method which allows to select the level of resolution at which a fluid is simulated. The aim of this work is to extend SDPD to chemically reactive systems.To this end, an…

Fluid Dynamics · Physics 2017-09-13 Gérôme Faure , Jean-Bernard Maillet

We present a theoretical approach to scale the artificially fast dynamics of simulated coarse-grained polymer liquids down to its realistic value. As coarse-graining affects entropy and dissipation, two factors enter the rescaling:…

Soft Condensed Matter · Physics 2015-05-27 I. Y. Lyubimov , J. McCarty , A. Clark , M. G. Guenza

Dissipative particle dynamics is a widely used mesoscale technique for the simulation of hydrodynamics (as well as immersed particles) utilizing coarse-grained molecular dynamics. While the method is capable of describing any fluid, the…

Computational Physics · Physics 2019-10-22 Ryan C. Krafnick , Angel E. Garcia

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li
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