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There exist methods for determining effective conservative interactions in coarse grained particle based mesoscopic simulations. The resulting models can be used to capture thermal equilibrium behavior, but in the model system we study do…

Soft Condensed Matter · Physics 2016-03-28 Anders Eriksson , Martin Nilsson Jacobi , Johan Nyström , Kolbjørn Tunstrøm

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

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 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) 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

We present a novel approach of mapping dissipative particle dynamics (DPD) into classical molecular dynamics. By introducing the invariant volume element representing the swarm of atoms we show that the interactions between the emerging…

Soft Condensed Matter · Physics 2019-02-19 Vlad P Sokhan , Ilian T Todorov

A proper treatment of electrostatic interactions is crucial for the accurate calculation of forces in computer simulations. Electrostatic interactions are typically modeled using Ewald based methods, which have become one of the…

Soft Condensed Matter · Physics 2016-09-21 K. A. Terrón-Mejía , R. López-Rendón , A. Gama Goicochea

Dissipative Particle Dynamics (DPD) is a popular simulation model for investigating hydrodynamic behavior of systems with non-negligible equilibrium thermal fluctuations. DPD employs soft core repulsive interactions between the system…

Statistical Mechanics · Physics 2016-03-23 Oded Farago , Niels Grønbech-Jensen

In this article we show in details the derivation of an integration scheme for the dissipative particle dynamic model (DPD) using the stochastic Trotter formula [De Fabritiis et al., Physica A, 361, 429 (2006)]. We explain some subtleties…

Soft Condensed Matter · Physics 2016-08-16 M. Serrano , G. De Fabritiis , P. Español , P. V. Coveney

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

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

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

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

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

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

Dissipative particle dynamics (DPD) is now a well-established method for simulating soft matter systems. However, its applicability was recently questioned because some investigations showed an upper coarse-graining limit that would prevent…

Soft Condensed Matter · Physics 2011-11-09 Rudolf M. Füchslin , Harold Fellermann , Anders Eriksson , Hans-Joachim Ziock

We investigate the behavior of dissipative particle dynamics (DPD) with time-correlated random noise. A new stochastic force for DPD is proposed which consists of a random force whose noise has an algebraic correlation proportional to 1/t…

Statistical Mechanics · Physics 2019-01-10 Morgane Borreguero , Marco Ellero , Nikolaus A. Adams

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

A brief overview of mesoscopic modelling via dissipative particle dynamics is presented, with emphasis on the appropriate parametrisation and how to calculate the relevant parameters for given realistic systems. The dependence on…

Chemical Physics · Physics 2016-02-19 E. Mayoral , E. Nahmad-Achar

Accurate interaction potentials between microscopic components such as colloidal particles or cells are crucial to understanding a range of processes, including colloidal crystallization, bacterial colony formation, and cancer metastasis.…

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