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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 construct a coarse-grained (CG) model for dipalmitoylphosphatidylcholine (DPPC)/cholesterol bilayers and apply it to large-scale simulation studies of lipid membranes. Our CG model is a two-dimensional representation of the membrane,…

Soft Condensed Matter · Physics 2009-11-10 Teemu Murtola , Emma Falck , Michael Patra , Mikko Karttunen , Ilpo Vattulainen

Many-body dissipative particle dynamics (MDPD) offers a significant speed-up in the simulation of various systems, including soft matter, in comparison with molecular dynamics (MD) simulations based on Lennard-Jones nteractions, which is…

Soft Condensed Matter · Physics 2025-06-09 Natalia Kramarz , Luís H. Carnevale , Panagiotis E. Theodorakis

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

We implemented a coarse-graining procedure to construct mesoscopic models of complex molecules. The final aim is to obtain better results on properties depending on slow modes of the molecules. Therefore the number of particles considered…

Soft Condensed Matter · Physics 2009-10-31 Hendrik Meyer , Oliver Biermann , Roland Faller , Dirk Reith , Florian Mueller-Plathe

MARTINI is a popular coarse-grained force-field that is mainly used in molecular dynamics (MD) simulations. It is based on the ``Lego'' approach where intermolecular interactions between coarse-grained beads representing chemical units of…

Computational Physics · Physics 2024-06-25 Luis H. Carnevale , Panagiotis E. Theodorakis

Molecular dynamics (MD) simulation is essential for various scientific domains but computationally expensive. Learning-based force fields have made significant progress in accelerating ab-initio MD simulation but are not fast enough for…

Machine Learning · Computer Science 2023-08-29 Xiang Fu , Tian Xie , Nathan J. Rebello , Bradley D. Olsen , Tommi Jaakkola

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

Simulations of condensed matter systems often focus on the dynamics of a few distinguished components but require integrating the dynamics of the full system. A prime example is a molecular dynamics simulation of a (macro)molecule in…

Computational Physics · Physics 2024-03-12 Mauricio J. del Razo , Daan Crommelin , Peter G. Bolhuis

Data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the context of multiscale problems. The present paper offers a…

Computational Physics · Physics 2020-08-26 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis

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 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 coarse-graining method applicable to dry scalar active matter with motility regulation. Our approach, based on a multiscale perturbative expansion of the backward Kolmogorov equation, does not rely on any specific microscopic…

Statistical Mechanics · Physics 2026-04-13 Alberto Dinelli , Pietro Luigi Muzzeddu

Given the ubiquity of depletion effects in biological and other soft matter systems, it is desirable to have coarse-grained Molecular Dynamics simulation approaches appropriate for the study of complex systems. This paper examines the use…

Soft Condensed Matter · Physics 2015-06-22 Tyler N. Shendruk , Martin Bertrand , James L. Harden , Gary W. Slater , Hendrick W. de Haan

The Dynamic Monte Carlo (DMC) method is an established molecular simulation technique for the analysis of the dynamics in colloidal suspensions. An excellent alternative to Brownian Dynamics or Molecular Dynamics simulation, DMC is…

Soft Condensed Matter · Physics 2020-07-15 Fabián A. García Daza , Alejandro Cuetos , Alessandro Patti

We present a coarse-graining strategy for reducing the number of particle species in mixtures to achieve a simpler system with higher diffusion while preserving the total particle number and characteristic dynamic features. As a system of…

Soft Condensed Matter · Physics 2020-09-16 Thomas Heinemann , YounJoon Jung

We develop a coarse grained (CG) approach for efficiently simulating calcium dynamics in the endoplasmic reticulum membrane based on a fine stochastic lattice gas model. By grouping neighboring microscopic sites together into CG cells and…

Chemical Physics · Physics 2015-06-15 Chuansheng Shen , Hanshuang Chen

In recent years, molecular dynamics (MD) simulations have emerged as a pivotal tool for understanding the structure, dynamics, and phase behavior in charged soft matter systems. To explore phenomena across greater length and time scales in…

Computational Physics · Physics 2024-07-18 Benjamin Bobin Ye , Shensheng Chen , Zhen-Gang Wang

Coarse-grained (CG) molecular dynamics (MD) simulations can simulate large molecular complexes over extended timescales by reducing degrees of freedom. A critical step in CG modeling is the selection of the CG mapping algorithm, which…

Soft Condensed Matter · Physics 2025-07-23 Soumya Mondal , Subhanu Halder , Debarchan Basu , Sandeep Kumar , Tarak Karmakar

We demonstrate that an inverse Monte Carlo approach allows to reconstruct effective interaction potentials from real-space images. The method is exemplified on monomolecular ethanol-water films imaged with scanning force microscopy (SFM),…

Statistical Mechanics · Physics 2016-04-13 Jonas Gienger , Nikolai Severin , Jürgen P. Rabe , Igor M. Sokolov
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