Electrostatics in dissipative particle dynamics using Ewald sums with point charges

Topological phase transition in a quasi-two-dimensional Coulomb gas

A system with an equal number of positive and negative charges confined in a box with a small but finite thickness is modeled as a function of temperature using mesoscale numerical simulations for various values of the charges. The Coulomb interaction is used in its three-dimensional form, U(r)∼1/r. A topological phase transition is found in this quasi-two-dimensional (2D) system. The translational order parameter, spatial correlation function, specific heat, and electric current show qualitatively different trends below and above a critical temperature. We find that a 2D logarithmic Coulomb interaction is not essential for the appearance of this transition. This work suggests new experimental tests of our predictions, as well as novel theoretical approaches to probe quasi-2D topological phase transitions.

DPD Modelling of the Self- and Co-Assembly of Polymers and Polyelectrolytes in Aqueous Media: Impact on Polymer Science

This review article is addressed to a broad community of polymer scientists. We outline and analyse the fundamentals of the dissipative particle dynamics (DPD) simulation method from the point of view of polymer physics and review the articles on polymer systems published in approximately the last two decades, focusing on their impact on macromolecular science. Special attention is devoted to polymer and polyelectrolyte self- and co-assembly and self-organisation and to the problems connected with the implementation of explicit electrostatics in DPD numerical machinery. Critical analysis of the results of a number of successful DPD studies of complex polymer systems published recently documents the importance and suitability of this coarse-grained method for studying polymer systems.

Coarse-grained simulation of the translational and rotational diffusion of globular proteins by dissipative particle dynamics

With simplified interactions and degrees of freedom, coarse-grained (CG) simulations have been successfully applied to study the translational and rotational diffusion of proteins in solution. However, in order to reach larger lengths and longer timescales, many CG simulations employ an oversimplified model for proteins or an implicit-solvent model in which the hydrodynamic interactions are ignored, and thus, the real kinetics are more or less unfaithful. In this work, we develop a CG model based on the dissipative particle dynamics (DPD) that can be universally applied to different types of proteins. The proteins are modeled as a group of rigid DPD beads without conformational changes. The fluids (including solvent and ions) are also modeled as DPD beads. The electrostatic interactions between charged species are explicitly considered by including charge distributions on DPD particles. Moreover, a surface friction between the protein and fluid beads is applied to control the slip boundary condition. With this model, we investigate the self-diffusion of a single globular protein in bulk solution. The translational and rotational diffusion coefficients of the protein can be tuned by the surface frictional constant to fit the predictions of the Stokes-Einstein (SE) relation. We find that both translational and rotational diffusion coefficients that meet with the prediction of the SE relation based on experimental results of the hydrodynamic radius are reached at almost the same frictional constant for different types of proteins. Such scaling behavior indicates that the model can be applied to simulate the translational and rotational diffusion together for various types of proteins.

The ENUF method-Ewald summation based on nonuniform fast Fourier transform: Implementation, parallelization, and application

Computer simulations of model systems are widely used to explore striking phenomena in promising applications spanning from physics, chemistry, biology, to materials science and engineering. The long range electrostatic interactions between charged particles constitute a prominent factor in determining structures and states of model systems. How to efficiently calculate electrostatic interactions in simulation systems subjected to partial or full periodic boundary conditions has been a grand challenging task. In the past decades, a large variety of computational schemes has been proposed, among which the Ewald summation method is the most reliable route to accurately deal with electrostatic interactions between charged particles in simulation systems. In addition, extensive efforts have been done to improve computational efficiencies of the Ewald summation based methods. Representative examples are approaches based on cutoffs, reaction fields, multi-poles, multi-grids, and particle-mesh schemes. We sketched an ENUF method, an abbreviation for the Ewald summation method based on the nonuniform fast Fourier transform technique, and have implemented this method in particle-based simulation packages to calculate electrostatic energies and forces at micro- and mesoscopic levels. Extensive computational studies of conformational properties of polyelectrolytes, dendrimer-membrane complexes, and ionic fluids demonstrated that the ENUF method and its derivatives conserve both energy and momentum to floating point accuracy, and exhibit a computational complexity of O N log N with optimal physical parameters. These ENUF based methods are attractive alternatives in molecular simulations where high accuracy and efficiency of simulation methods are needed to accelerate calculations of electrostatic interactions at extended spatiotemporal scales.

Self-Assembly of Phosphocholine Derivatives Using the ELBA Coarse-Grained Model: Micelles, Bicelles, and Reverse Micelles

The ELBA coarse-grained force field was originally developed for lipids, and its water model is described as a single-site Lennard-Jones particle with electrostatics modeled by an embedded point-dipole, while other molecules in this force field have a three (or four)-to-one mapping scheme. Here, ELBA was applied to investigate the self-assembly processes of dodecyl-phosphocholine (DPC) micelle, 1,2-dipalmitoyl-sn-glycero-3-phosphocholine/1,2-dihexaoyl-sn-glycero-3-phosphocholine (DPPC/DHPC) bicelles, and DPPC/cyclohexane/water reverse micelles through coarse-grained molecular dynamics (MD) simulations. New parameters were obtained using a simplex algorithm-based calibration procedure to determine the Lennard-Jones parameters for cyclohexane, dodecane, and cyclohexane-dodecane cross-interactions. Density, self-diffusion coefficient, surface tension, and mixture excess volume were found to be in fair agreement with experimental data. These new parameters were used in the simulations, and the obtained structures were analyzed for shape, size, volume, and surface area. Except for the shape of DPC micelles, all other properties match well with available experimental data and all-atom simulations. Remarkably, in agreement with experiments the rodlike shape of the DPPC reverse micelle is well described by ELBA, while all-atom data in the literature predicts a disclike shape. To further check the consistency of the force field in reproducing the correct shapes of reverse micelles, additional simulations were performed doubling the system size. Two distinct reverse micelles were obtained both presenting the rodlike shape and correct aggregation number.

Structure and Dynamics of Stimuli-Responsive Nanoparticle Monolayers at Fluid Interfaces

Stimuli-responsive nanoparticles at fluid interfaces offer great potential for realizing on-demand and controllable self-assembly that can benefit various applications. Here, we conducted electrostatic dissipative particle dynamics simulations to provide a fundamental understanding of the microstructure and interfacial dynamics of responsive nanoparticle monolayers at a water-oil interface. The model nanoparticle is functionalized with polyelectrolytes to render the pH sensitivity, which permits further manipulation of the monolayer properties. The monolayer structure was analyzed in great detail through the density and electric field distributions, structure factor, and Voronoi tessellation. Even at a low surface coverage, a continuous disorder-to-order phase transition was observed when the particle's degree of ionization increases in response to pH changes. The six-neighbor particle fraction and bond orientation order parameter quantitatively characterize the structural transition induced by long-range electrostatic interactions. Adding salt can screen the electrostatic interactions and offer additional control on the monolayer structure. The detailed dynamics of the monolayer in different states was revealed by analyzing mean-squared displacements, in which different diffusion regimes were identified. The self-diffusion of individual particles and the collective dynamics of the whole monolayer were probed and correlated with the structural transition. Our results provide deeper insight into the dynamic behavior of responsive nanoparticle surfactants and lay the groundwork for bottom-up synthesis of novel nanomaterials, responsive emulsions, and microdroplet reactors.