Conventional Dissipative Particle Dynamics Research Articles

Hydrodynamic and transport behavior of solid nanoparticles simulated with dissipative particle dynamics

Inertial migration of micro- and nanoparticles flowing through microchannels is commonly used for particle separation, sorting, and focusing on many lab-on-a-chip devices. Computer simulations of inertial migration of nanoparticles by mesoscale simulation methods, such as Dissipative Particle Dynamics (DPD) would be helpful to future experimental development of these lab-on-a-chip devices. However, the conventional DPD approach has a low Schmidt number and its ability to model inertial migration is questioned. In this work, we examine the ability of DPD simulations to investigate the inertial migration of rigid nanoparticles flowing through a slit channel. By varying the exponent and cutoff distance in the weight function of the random and dissipative forces, DPD models with Schmidt number varying between 1 and 370 were examined. We show that solvent penetration into nanoparticles and solvent-induced attraction between nanoparticles can be controlled by choosing appropriate interaction coefficients of the DPD conservative force and that these properties are not influenced by the Schmidt number of the DPD model. On the other hand, hydrodynamic properties and transport behaviour of rigid nanoparticles are influenced by the Schmidt number. With the conventional DPD model, nanoparticles tend to be evenly distributed across the channel and do not remain in steady-state positions during flow. At high Schmidt numbers, the particles migrate to long-lasting steady-state positions located between the channel center and walls, in agreement with known experimental observations. We conclude that to properly simulate inertial migration, modifications to the conventional DPD model that yield a high Schmidt number are required.

A dissipative particle dynamics model for studying dynamic phenomena in colloidal rod suspensions.

A dissipative particle dynamics (DPD) model is developed and demonstrated for studying dynamics in colloidal rod suspensions. The solvent is modeled as conventional DPD particles, while individual rods are represented by a rigid linear chain consisting of overlapping solid spheres, which interact with solvent particles through a hard repulsive potential. The boundary condition on the rod surface is controlled using a surface friction between the solid spheres and the solvent particles. In this work, this model is employed to study the diffusion of a single colloid in the DPD solvent and compared with theoretical predictions. Both the translational and rotational diffusion coefficients obtained at a proper surface friction show good agreement with calculations based on the rod size defined by the hard repulsive potential. In addition, the system-size dependence of the diffusion coefficients shows that the Navier-Stokes hydrodynamic interactions are correctly included in this DPD model. Comparing our results with experimental measurements of the diffusion coefficients of gold nanorods, we discuss the ability of the model to correctly describe dynamics in real nanorod suspensions. Our results provide a clear reference point from which the model could be extended to enable the study of colloid dynamics in more complex situations or for other types of particles.

Modeling Gas-Liquid Interfaces by Dissipative Particle Dynamics: Adsorption and Surface Tension of Cetyl Trimethyl Ammonium Bromide at the Air-Water Interface.

Adsorption of surfactants at gas-liquid interfaces that causes reduction in the surface tension is a classical problem in colloid and interface science with multiple practical applications in oil and gas recovery, separations, cosmetics, personal care, and biomedicine. Here, we develop an original coarse-grained model of the liquid-gas interface within the conventional dissipative particle dynamics (DPD) framework with the goal of quantitatively predicting the surface tension in the presence of surfactants. As a practical case-study example, we explore the adsorption of the cationic surfactant cetyl trimethyl ammonium bromide (CTAB) on the air-water interface. The gas phase is modeled as a DPD fluid composed of fictitious hard-core "gas" beads with exponentially decaying repulsive potentials to prevent penetration of the liquid phase components. A rigorous parametrization scheme is proposed based on matching the bulk and interfacial properties of water and octane taken as the reference compounds. Quantitative agreement between the simulated and experimental surface tension of CTAB solutions is found for a wide range of bulk surfactant concentrations (∼10-3 to ∼1 mmol/L) with the reduction of the surface tension from ∼72 mN/m (pure water) to the limiting value of ∼37.5 mN/m at the critical micelle concentration. The gas phase DPD model with the proposed parametrization scheme can be extended and applied to modeling various gas-liquid interfaces with surfactant and lipid monolayers, such as bubble suspensions, foams, froths, etc.

Dissipative particle dynamics parameterization and simulations to predict negative volume excess and structure of PEG and water mixtures

We report the results of dissipative particle dynamics (DPD) parameterization and simulations of a mixture of hydrophilic polymer, PEG 400, and water which are known to exhibit negative volume excess property upon mixing. The addition of a Morse potential to the conventional DPD potential mimics the hydrogen bond attraction, where the parameterization takes the internal chemistry of the beads into account. The results indicate that the mixing of PEG and water are maintained by the influence of hydrogen bonds, and the mesoscopic structure is characterized by the trade-off of enthalpic and entropic effects.

Imposition of physical parameters in dissipative particle dynamics

In the mesoscale simulations by the dissipative particle dynamics (DPD), the motion of a fluid is modelled by a set of particles interacting in a pairwise manner, and it has been shown to be governed by the Navier–Stokes equation, with its physical properties, such as viscosity, Schmidt number, isothermal compressibility, relaxation and inertia time scales, in fact its whole rheology resulted from the choice of the DPD model parameters. In this work, we will explore the response of a DPD fluid with respect to its parameter space, where the model input parameters can be chosen in advance so that (i) the ratio between the relaxation and inertia time scales is fixed; (ii) the isothermal compressibility of water at room temperature is enforced; and (iii) the viscosity and Schmidt number can be specified as inputs. These impositions are possible with some extra degrees of freedom in the weighting functions for the conservative and dissipative forces. Numerical experiments show an improvement in the solution quality over conventional DPD parameters/weighting functions, particularly for the number density distribution and computed stresses.

Reducing the effects of compressibility in DPD-based blood flow simulations through severe stenotic microchannels

Viscous fluid flow simulations based on dissipative particle dynamics (DPD) may bear compressible flow effects when flowing through severe stenotic geometries. This is caused by the soft repulsive potential employed in the DPD force field, which limits the particle-based fluid system ability to sustain a large degree of compression. To mitigate this problem, a Morse potential was added to the DPD force field. We studied the fluid properties of the modified fluid model (DPD–Morse) and compared it with a previously published conventional DPD based fluid model. Our DPD–Morse model demonstrated reduced compressibility while preserving other fluid properties such as the fluid density and viscosity. We further investigated the fluid flow properties for a severe 3D stenotic microchannel with a 67% stenosis, using the two models. The DPD fluid model presented a significant density gradient along the flow direction, where the fluid density increased upstream towards the stenosis and decreased downstream from the stenosis before regaining its initial value. In contrast, the DPD–Morse model demonstrated a far better uniform fluid density distribution along the flow direction. We compared both solutions with CFD simulations. The DPD–Morse fluid resembled the behavior of the continuum fluid model whereas DPD fluid deviated from it. To estimate the effect that the difference between the two DPD formulations may have on the platelet activation potential, we have further embedded a platelet model within the flow field and investigated the shear stress accumulation along the platelet transport trajectory. In the stenotic section, the DPD fluid demonstrated a larger stress gradient than the DPD–Morse fluid. The platelet transport period was shorter for the DPD fluid as it generated a larger fluid density gradient that overestimated the acceleration of the platelet through the stenosis. With reduced fluid compressibility, our modified DPD–Morse fluid model was more accurate than the DPD fluid model when computing the platelet activation potential in a severe stenosis.

Transport dissipative particle dynamics model for mesoscopic advection-diffusion-reaction problems.

We present a transport dissipative particle dynamics (tDPD) model for simulating mesoscopic problems involving advection-diffusion-reaction (ADR) processes, along with a methodology for implementation of the correct Dirichlet and Neumann boundary conditions in tDPD simulations. tDPD is an extension of the classic dissipative particle dynamics (DPD) framework with extra variables for describing the evolution of concentration fields. The transport of concentration is modeled by a Fickian flux and a random flux between tDPD particles, and the advection is implicitly considered by the movements of these Lagrangian particles. An analytical formula is proposed to relate the tDPD parameters to the effective diffusion coefficient. To validate the present tDPD model and the boundary conditions, we perform three tDPD simulations of one-dimensional diffusion with different boundary conditions, and the results show excellent agreement with the theoretical solutions. We also performed two-dimensional simulations of ADR systems and the tDPD simulations agree well with the results obtained by the spectral element method. Finally, we present an application of the tDPD model to the dynamic process of blood coagulation involving 25 reacting species in order to demonstrate the potential of tDPD in simulating biological dynamics at the mesoscale. We find that the tDPD solution of this comprehensive 25-species coagulation model is only twice as computationally expensive as the conventional DPD simulation of the hydrodynamics only, which is a significant advantage over available continuum solvers.

Smoothed dissipative particle dynamics with angular momentum conservation

Smoothed dissipative particle dynamics (SDPD) combines two popular mesoscopic techniques, the smoothed particle hydrodynamics and dissipative particle dynamics (DPD) methods, and can be considered as an improved dissipative particle dynamics approach. Despite several advantages of the SDPD method over the conventional DPD model, the original formulation of SDPD by Español and Revenga (2003) [9], lacks angular momentum conservation, leading to unphysical results for problems where the conservation of angular momentum is essential. To overcome this limitation, we extend the SDPD method by introducing a particle spin variable such that local and global angular momentum conservation is restored. The new SDPD formulation (SDPD+a) is directly derived from the Navier–Stokes equation for fluids with spin, while thermal fluctuations are incorporated similarly to the DPD method. We test the new SDPD method and demonstrate that it properly reproduces fluid transport coefficients. Also, SDPD with angular momentum conservation is validated using two problems: (i) the Taylor–Couette flow with two immiscible fluids and (ii) a tank-treading vesicle in shear flow with a viscosity contrast between inner and outer fluids. For both problems, the new SDPD method leads to simulation predictions in agreement with the corresponding analytical theories, while the original SDPD method fails to capture properly physical characteristics of the systems due to violation of angular momentum conservation. In conclusion, the extended SDPD method with angular momentum conservation provides a new approach to tackle fluid problems such as multiphase flows and vesicle/cell suspensions, where the conservation of angular momentum is essential.

Pore network design: DPD-Monte Carlo study of solvent diffusion dependence on side chain location

Phase separation within water containing polymer membranes is studied by dissipative particle dynamics (DPD). The polymers are composed of hydrophobic backbone A beads to which ([A-C] or [A-A-C-C]) side chains are attached with a hydrophilic (C) end moiety. Water diffusion through the water containing pores is modeled by Monte Carlo (MC) tracer diffusion. Several polymeric architectures are considered which differ in the way side chains are attached along the polymer backbones. In total 120 pore morphologies are stored on file and probed by MC tracer diffusion calculations. For membranes of the same ion exchange capacity diffusion is highest for architectures for which two side chains are branching off from the backbone sites as compared to architectures for which only one side chain is branching off. This conclusion is also obtained from diffusion constants derived from mean squared displacements of water during the DPD simulations. The intrinsic high polymer mobility in conventional DPD results in water diffusivities that are much higher than those obtained from the MC calculations. Assigning higher masses to the polymer beads results in significant decrease in water bead motion.

Dissipative particle dynamics simulation of macromolecular solutions under Poiseuille flow in microchannels

macromolecular solutions under Poiseuille flow in microchannels are investigated using the dissipative particle dynamics (DPD) approach. The results show that the macromolecular solutions are non-Newtonian fluids which can be described by power-law fluids, and the power-law index decreases with the increase of the macromolecular concentration. The DPD simulations show that the hydrodynamic interaction between the macromolecular chains and the wall, and the gradient of Brownian diffusivity of the chains govern the cross-stream migration of the macromolecules. However, the chain-wall hydrodynamic interaction may not be fully developed and are partly screened in conventional DPD approach. Hence, the chains migrate toward the wall during flow. Simulation results also indicate that the migration toward the wall increases with the increase of the driving force. The competition between the unscreened chain-wall hydrodynamic interaction and Brownian diffusivity leads to two symmetric off-center peaks and a local minimum in the channel centerline in the chain center-of-mass distribution. Under strong confinement, the chain-wall hydrodynamic interaction may be fully screened and the Brownian motion is weak, thus the chains weakly move toward the wall for channel of small width.

J053031 Lennard-Jones流体の粗視化に基づく散逸粒子動力学相互作用モデルの構築 : 気液界面を含む系に関する検討

The application of molecular dynamics (MD) simulation to mesoscale (10-100 nm) flow analysis is computationally expensive at present. Dissipative particle dynamics (DPD) simulation is the powerful candidate for the alternative method. Larger scale and longer time simulation is possible by using DPD since a single dissipative particle represents multi-particles. In DPD interaction models, the force contains three parts, each of which is pairwise additive: conservative, dissipative and random forces, respectively. In the conventional DPD framework, the parameters of these three forces are determined so that macroscopic properties such as diffusivity or compressibility are recovered. In our study, we investigate the method of bottom-up construction of DPD models by means of MD simulations. We focus on the center of mass of the cluster containing Lennard-Jones (LJ) particles and extract the effective forces exerted on the clusters. In our simulations, the DPD model can roughly reproduce the surface tension of the MD system while the temperature and diffusivity are underestimated due to the overestimation of friction coefficients. The diffusivity of the DPD system can be improved by scaling the friction coefficients so that the temperature of the DPD system matches that of the MD system.

Forced Convection Heat Transfer Simulation Using Dissipative Particle Dynamics

Dissipative particle dynamics (DPD) with energy conservation was applied to simulate forced convection in parallel-plate channels with boundary conditions of constant wall temperature (CWT) and constant wall heat flux (CHF). DPD is a coarse-grained version of molecular dynamics. An additional equation for energy conservation was solved along with conventional DPD equations, where inter-particle heat flux accounts for changes in mechanical and internal energies when particles interact with surrounding particles. The solution domain was considered to be two–dimensional with periodic boundary condition in the flow direction and additional layers of particles on the top and bottom of the channel to apply no-slip and wall temperature boundary conditions. The governing equation for energy conservation was modified based on periodic fully developed velocity and temperature conditions. The results were shown via velocity and temperature profiles across the channel cross-section. The Nusselt numbers for CWT and CHF were calculated from the temperature gradient at the wall using a second order accurate forward difference approximation. The results agreed well with the exact solutions to within 2.3%.

Dissipative particle dynamics simulation of pore‐scale multiphase fluid flow

Multiphase fluid flow through porous media involves complex fluid dynamics, and it is difficult to model such complex behavior, on the pore scale, using grid‐based continuum models. In this paper, the application of dissipative particle dynamics (DPD), a relatively new mesoscale method, to the simulation of pore‐scale multiphase fluid flows under a variety of flow conditions is described. We demonstrate that the conventional DPD method using purely repulsive conservative (nondissipative) particle‐particle interactions is capable of modeling single‐phase flow fields in saturated porous media. In order to simulate unsaturated multiphase flow through porous media, we applied a modified model for the conservative particle‐particle interactions that combines short‐range repulsive and long‐range attractive interactions. This form for the conservative particle‐particle interactions allows the behavior of multiphase systems consisting of gases, liquids, and solids to be simulated. We also demonstrated that the flow of both wetting and nonwetting fluids through porous media can be simulated by controlling the ratios between the fluid‐fluid and fluid‐solid (fluid‐wall) interparticle interaction strengths.

Dissipative particle dynamics simulation of fluid motion through an unsaturated fracture and fracture junction

Multiphase fluid motion in unsaturated fractures and fracture networks involves complicated fluid dynamics, which is difficult to model using grid-based continuum methods. In this paper, the application of dissipative particle dynamics (DPD), a relatively new mesoscale method to simulate fluid motion in unsaturated fractures is described. Unlike the conventional DPD method that employs a purely repulsive conservative (non-dissipative) particle–particle interaction to simulate the behavior of gases, we used conservative particle–particle interactions that combine short-range repulsive and long-range attractive interactions. This new conservative particle–particle interaction allows the behavior of multiphase systems consisting of gases, liquids and solids to be simulated. Our simulation results demonstrate that, for a fracture with flat parallel walls, the DPD method with the new interaction potential function is able to reproduce the hydrodynamic behavior of fully saturated flow, and various unsaturated flow modes including thin film flow, wetting and non-wetting flow. During simulations of flow through a fracture junction, the fracture junction can be fully or partially saturated depending on the wetting property of the fluid, the injection rate and the geometry of the fracture junction. Flow mode switching from a fully saturated flow to a thin film flow can also be observed in the fracture junction.