Dissipative Particle Dynamics Parameters Research Articles

Dissipative Particle Dynamics Simulation for Reaction-Induced Phase Separation of Thermoset/Thermoplastic Blends.

Reaction-induced phase separation occurs during the curing reaction when a thermoplastic resin is dissolved in a thermoset resin, which enables toughening of the thermoset resin. As resin properties vary significantly depending on the morphology of the phase-separated structure, controlling the morphology formation is of critical importance. Reaction-induced phase separation is a phenomenon that ranges from the chemical reaction scale to the mesoscale dynamics of polymer molecules. In this study, we performed curing simulations using dissipative particle dynamics (DPD) coupled with a reaction model to reproduce reaction-induced phase separation. The curing reaction properties of the thermoset resin were determined by ab initio quantum chemical calculations, and the DPD parameters were determined by all-atom molecular dynamics simulations. This enabled mesoscopic simulations, including reactions that reflect the intrinsic material properties. The effects of the thermoplastic resin concentration, molecular weight, and curing conditions on the phase-separation morphology were evaluated, and the cure shrinkage and stiffness of each cured resin were confirmed to be consistent with the experimental trends. Furthermore, the local strain field under tensile deformation was visualized, and the inhomogeneous strain field caused by the phase-separated structures of two resins with different stiffnesses was revealed. These results can aid in understanding the toughening properties of thermoplastic additives at the molecular level.

An improved dissipative particle dynamics method for the liquid-particle two-phase flow in microchannels

Liquid-particle two-phase flow in microchannel widely exists in the fields of biomedical and environmental monitoring, such as the lab-chip device for disease diagnosis. The standard dissipative particle dynamics (DPD) method has been previously employed to study the liquid-particle two-phase flow in microchannel, but it cannot accurately simulate the real process because of the unsuitable DPD parameters. In the present study, an improved DPD method was developed by changing the system energy and fitting the characteristic curve between the random force coefficient and the Schmidt number. In addition, a new logarithmic relationship between the conservative force coefficient and the particle size was found. The result demonstrated that the improved DPD method enabled more accurate simulation on the liquid-particle two-phase flow in microchannels than the standard DPD method. For instance, in the simulation of particle sedimentation, the relative deviation between the value obtained by the improved DPD method and the theoretical value was less than 6% while the relative deviation was more than 20% for the standard DPD method. The simulated result of the particle migration in microchannel was in good agreement with the result obtained by Matas et al, and the relative deviation was less than 1.5%. Therefore, the improved DPD method would have great potentials in the study on the liquid-particle two-phase flow in microchannels.

Isolating the Effect of Crosslink Densities on Mechanical Properties of Isotactic Polypropylene Using Dissipative Particle Dynamics

AbstractGiven the importance of preserving the mechanical properties of recycled isotactic polypropylene (iPP) during its processing, this work provides an improved understanding of the contribution of introducing physical or chemical crosslinks using the dissipative particle dynamics (DPD) method, which makes it possible to model iPP structures with a realistic range of crosslink densities. First, the protocol to build a coarse‐grained model of iPP from an all‐atom expression by Bayesian optimization is described. A Bayesian optimization procedure employing two different cutoff distances successfully provides optimal DPD parameters reproducing iPP's properties compared to the all‐atom system. Then, the coarse‐grained iPP model with optimal DPD parameters is applied to study structures containing a realistic range of crosslink densities to evaluate their mechanical properties. These calculations demonstrate that the mechanical properties such as the Young's modulus and ultimate strength increase while the fracture strain decreases with an increase in the crosslink density, which is consistent with experimental observations. The results also show that there is a critical crosslink density above which these properties start to be improved due to the introduction of crosslinks. These findings can help us to obtain targeted properties of recycled iPP by introducing physical or chemical crosslinks.

Coarse Grained Modeling of Multiphase Flows with Surfactants.

Coarse-grained modeling methods allow simulations at larger scales than molecular dynamics, making it feasible to simulate multifluid systems. It is, however, critical to use model parameters that represent the fluid properties with fidelity under both equilibrium and dynamic conditions. In this work, dissipative particle dynamics (DPD) methods were used to simulate the flow of oil and water in a narrow slit under Poiseuille and Couette flow conditions. Large surfactant molecules were also included in the computations. A systematic methodology is presented to determine the DPD parameters necessary for ensuring that the boundary conditions were obeyed, that the oil and water viscosities were represented correctly, and that the velocity profile for the multifluid system agreed with the theoretical expectations. Surfactant molecules were introduced at the oil–water interface (sodium dodecylsulfate and octaethylene glycol monododecyl ether) to determine the effects of surface-active molecules on the two-phase flow. A critical shear rate was found for Poiseuille flow, beyond which the surfactants desorbed to form the interface forming micelles and destabilize the interface, and the surfactant-covered interface remained stable under Couette flow even at high shear rates.

Simulation of high Schmidt number fluids with dissipative particle dynamics: Parameter identification and robust viscosity evaluation

Dissipative particle dynamics (DPD) is a widely used coarse-grained technique for the simulation of complex fluids. Although the method is capable of describing the hydrodynamics of any fluid, the common choice of DPD parameters, such as friction coefficient γ, dissipative cutoff radius rcD, coarse-graining factor Nm and weighting function exponent s, unrealistically leads to the simulation of liquid water with a low Schmidt number Sc at standard pressure and temperature. In this work we explored the influence of these parameters, finding the set of parameters needed to properly simulate liquid water. Particular attention was devoted to the numerical techniques to calculate the transport properties from equilibrium simulations, especially in the calculation of the viscosity, comparing the most commonly adopted techniques and formulating a recipe that can be used for further investigations.

Asphaltenes at the water-oil interface using DPD/COSMO-SAC

Asphaltenes are the heaviest fraction of crude oil. Its deposition causes large problems during oil exploitation. Sometimes it is difficult to separate the asphaltenes from the oil because of the very stable water in oil emulsions that they form. The Dissipative Particle Dynamics (DPD) has been used to study the interfacial properties of asphaltene molecules at the water-oil interface. The COSMO-SAC method was used to systematically obtaining the conservative force DPD parameters. The methodology to obtain the DPD-parameters has been tested in hydrocarbon-water systems yielding good results for the interfacial tension compared to experimental data. Asphaltene-toluene mixtures were also analyzed using this methodology in terms of diffusion coefficients and structural information showing consistent results. Ultimately, the water-asphaltene-oil systems were investigated, and the critical micelle concentration is in agreement with experimental values. Density profiles and angular analysis of asphaltene molecules at the water-oil interface have also been carried out, showing that those molecules are preferentially parallel to the interface at low asphaltene concentration, whereas at higher concentrations, entropic effects become dominant, and the molecules assume a tilted configuration. The size and number of aggregates at the water-oil interface show that asphaltenes form small aggregates at low concentrations and large structures at high concentrations.

Translation of Chemical Structure into Dissipative Particle Dynamics Parameters for Simulation of Surfactant Self-Assembly.

Dissipative particle dynamics (DPD) can be used to simulate the self-assembly properties of surfactants in aqueous solutions, but in order to simulate a new compound, a large number of new parameters are required. New methods for the calculation of reliable DPD parameters directly from chemical structure are described, allowing the DPD approach to be applied to a much wider range of organic compounds. The parameters required to describe the bonded interactions between DPD beads were calculated from molecular mechanics structures. The parameters required to describe the nonbonded interactions were calculated from surface site interaction point (SSIP) descriptions of molecular fragments that represent individual beads. The SSIPs were obtained from molecular electrostatic potential surfaces calculated using density functional theory and used in the SSIMPLE algorithm to calculate transfer free energies between different bead liquids. This approach was used to calculate DPD parameters for a range of different types of surfactants, which include ester, amide, and sugar moieties. The parameters were used to simulate the self-assembly properties in aqueous solutions, and comparison of the results for 27 surfactants with the available experimental data shows that these DPD simulations accurately predict critical micelle concentrations, aggregation numbers, and the shapes of the supramolecular assemblies formed. The methods described here provide a general approach to determining DPD parameters for neutral organic compounds of arbitrary structure.

A new model for dissipative particle dynamics boundary condition of walls with different wettabilities

The implementation of solid-fluid boundary condition has been a major challenge for dissipative particle dynamics (DPD) method. Current implementations of boundary conditions usually try to approach a uniform density distribution and a velocity profile close to analytical solution. The density oscillations and slip velocity are intentionally eliminated, and different wall properties disappear in the same analytical solution. This paper develops a new wall model that combines image and frozen particles and a new strategy to emphasize different wall properties especially wettabilities. The strategy first studies the realistic wall-fluid system by molecular dynamics (MD) simulation depending on physical parameters. Then, a DPD simulation is used to match the density and velocity profiles with the new wall model. The obtained DPD parameters can simulate the systems with the same wall and fluid materials. With this method, a simulation of the Poiseuille flow of liquid argon with copper walls is presented. Other walls with super-hydrophilic, hydrophilic, and hydrophobic wettabilities are also simulated. The limitations of the analytical solution and the effect of the wall-fluid interaction are discussed. The results show that the method suggested in this paper can simulate the mesoscale behavior of the microchannel flow related to realistic systems.

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved.The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

Native-Based Dissipative Particle Dynamics Approach for α-Helical Folding.

We developed a dissipative particle dynamics (DPD) approach that captures polyalanine folding into a stable helical conformation. Within the proposed native-based approach, the DPD parameters are derived based on the contact map constructed from the molecular dynamics (MD) simulations. We show that the proposed approach reproduces the folding of polypeptides of various lengths, including bundle formation for sufficiently long polypeptides. The proposed approach also allows one to capture the folding of the helical segments of the lysozyme. With further development of computationally efficient native-based DPD approaches for folding, modeling of a range of biomaterials incorporating α-helical segments could be extended to time and length scales far beyond those accessible in molecular dynamics simulations.

High-fidelity scaling relationships for determining dissipative particle dynamics parameters from atomistic molecular dynamics simulations of polymeric liquids

An optimized Dissipative Particle Dynamics (DPD) model with simple scaling rules was developed for simulating entangled linear polyethylene melts. The scaling method, which can be used for mapping dimensionless (reduced units) DPD simulation data to physical units, was based on scaling factors for three fundamental physical units; namely, length, time, and viscosity. The scaling factors were obtained as ratios of equilibrium Molecular Dynamics (MD) simulation data in physical units and equivalent DPD simulation data for relevant quantities. Specifically, the time scaling factor was determined as the ratio of longest relaxation times, the length scaling factor was obtained as the ratio of the equilibrium end-to-end distances, and the viscosity scaling factor was calculated as the ratio of zero-shear viscosities, each as obtained from the MD (in physical units) and DPD (reduced units) simulations. The scaling method was verified for three MD/DPD model liquid pairs under several different nonequilibrium conditions, including transient and steady-state simple shear and planar elongational flows. Comparison of the MD simulation results with those of the scaled DPD simulations revealed that the optimized DPD model, expressed in terms of the proposed scaling method, successfully reproduced the computationally expensive MD results using relatively cheaper DPD simulations.

Dissipative particle dynamics for modeling micro-objects in microfluidics: application to dielectrophoresis.

The dissipative particle dynamics (DPD) technique is employed to model the trajectories of micro-objects in a practical microfluidic device. The simulation approach is first developed using an in-house Fortran code to model Stokes flow at Reynolds number of 0.01. The extremely low Reynolds number is achieved by adjusting the DPD parameters, such as force coefficients, thermal energies of the particles, and time steps. After matching the numerical flow profile with the analytical results, the technique is developed further to simulate the deflection of micro-objects under the effect of a deflecting external force in a rectangular microchannel. A mapping algorithm is introduced to establish the scaling relationship for the deflecting force between the physical device and the DPD domain. Dielectrophoresis is studied as a case study for the deflecting force, and the trajectory of a single red blood cell under the influence of the dielectrophoretic force is simulated. The device is fabricated using standard microfabrication techniques, and the experiments involving a dilute sample of red blood cells are performed at two different cases of the actuation voltage. Good agreement between the numerical and experimental results is achieved.

Constructing the phase diagram of sodium laurylethoxysulfate using dissipative particle dynamics

HypothesisSodium Laurylethoxysulfate (SLES) is a fundamental ingredient in a wide range of surfactant products and the mapping of its various mesophases is pivotal in predicting the liquid viscosity. Here we want to show that the use of properly parameterised coarse-grained molecular models can provide structural information of the surfactant solutions not easily achievable through experimental characterization. ExperimentsWe use a novel set of Dissipative Particle Dynamics parameters specifically developed for surfactant molecules to construct the first phase diagram of pure SLES in sodium chloride/water solutions. FindingsWe found that our DPD model is able to reproduce the range of morphologies expected for these types of ionic surfactants and in agreement with recent rheological data and theoretical predictions based on the packing parameter. We calculated the structure factor for various salt concentrations and show that the change from spherical to worm-like micelles can be inferred also looking at the intensity of the peak at intermediate q-values which decreases in intensity as salt concentrations increase. Varying the ethoxyl groups we observe that the additional ethoxyl group increased the micellar radius and affected the micelles’ shape polydispersity in the system. Finally, based on the contour length of worm-like micelles observed at intermediate salt concentrations, a closed mathematical formula is proposed capable of predicting the average micellar contour length given the salt and surfactant concentrations.

Dissipative particle dynamics: dissipative forces from atomistic simulation

ABSTRACT 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 Brownian quasiparticles arise naturally from its geometric definition and include both conservative repulsion and dissipative drag forces. The quasiparticles, which are composed of atomistic host solvent rather than being simply immersed in it, provide a link between the atomistic and DPD levels and a practical route to extract the DPD parameters as direct statistical averages over the atomistic host system. The method thus provides the molecular foundations for the mesoscopic DPD. It is illustrated on the example of simple monatomic supercritical fluid demonstrating good agreement in thermodynamic and transport properties calculated for the atomistic system and DPD using the obtained parameters.

DPD Parameters Estimation for Simultaneously Simulating Water-Oil Interfaces and Aqueous Nonionic Surfactants.

The outcome of a coarse-grained simulation within the dissipative particle dynamics framework strongly depends on the choice of the repulsive parameter between different species. Different methodologies have been used in the literature to determine these parameters toward reproducing selected experimental system properties. In this work, a systematic investigation on possible procedures for estimating the simulation parameters is conducted. We compare methods based on the Hildebrand and the Hansen solubility parameter theories, mapped into the Flory-Huggins model. We find that using the Hansen solubility parameters it is possible to achieve a high degree of coarse graining, with parameters that yield realistic values for the interfacial tension. The procedure was first applied to the water/benzene system and then validated for water/ n-octane, water/1,1-dichloroethane, water/methyl cyclohexane, and water/isobutyl acetate. In all these cases, the experimental interfacial tension could be reproduced by adjusting a single correction factor. In the case of the water-benzene system, the dissipative particle dynamics parameters derived using our approach were able to simultaneously describe both the interfacial tension and micellar properties of aqueous nonionic surfactants representative of the octyl poly(ethylene oxide) C8H17O(C2H4O)mH family. We show how the parameters can be used, within the dissipative particle dynamics framework, to simulate the water/oil interface in the presence of surfactants at varying concentrations. The results show, as expected, that as the surfactant concentration increases, the interfacial tension decreases, and micelles form in bulk water.

Inertial migration of a rigid sphere in plane Poiseuille flow as a test of dissipative particle dynamics simulations.

After reviewing and organizing the literature on the problem of inertial cross-stream migration of rigid spheres in various geometries including tubes and channels, we use Dissipative Particle Dynamics (DPD) simulations to study the simplest case of migration of a single neutrally or non-neutrally buoyant sphere with diameter 20% of the gap in plane Poiseuille flow and assess the potential and limitations of DPD simulations for this and similar problems. We find that the neutrally buoyant sphere lags by up to 6% behind the surrounding fluid and is focused at a position around 50% of the distance between the channel center and the wall. With Re increasing from around 100 to 500, the sphere migrates closer to the channel center. With flow driven by gravity, a much denser non-neutrally buoyant sphere leads the surrounding fluid and is focused at a position closer to the wall, around 60% the distance from the channel center to the wall, in qualitative agreement with previous work. The lower values of the Schmidt number Sc in DPD simulations relative to real fluids, due to the relatively large diffusivity of DPD beads, are shown to not significantly affect the consistency of our DPD results with literature results although they make results noisy at low Re (i.e., 50). However, the increase in Ma and Wi with increasing Re leads to compressible flow effects and in some cases viscoelastic effects at high Re depending on the DPD parameters chosen. Even for optimally chosen parameters, we require to avoid strong compressibility effects. Thus, the relative simplicity of the DPD method for complex fluid flows is offset by the need to control the effects of unphysically high values of other parameters, such as Ma and Wi, which seriously limits the range of conditions under which DPD simulations give valid results in fluid transport problems.

Dissipative particle dynamics study of velocity autocorrelation function and self-diffusion coefficient in terms of interaction potential strength

ABSTRACTThis research focuses on numerically investigating the self-diffusion coefficient and velocity autocorrelation function (VACF) of a dissipative particle dynamics (DPD) fluid as a function of the conservative interaction strength. Analytic solutions to VACF and self-diffusion coefficients in DPD were obtained by many researchers in some restricted cases including ideal gases, without the account of conservative force. As departure from the ideal gas conditions are accentuated with increasing the relative proportion of conservative force, it is anticipated that the VACF should gradually deviate from its normally expected exponentially decay. This trend is confirmed through numerical simulations and an expression in terms of the conservative force parameter, density and temperature is proposed for the self-diffusion coefficient. As it concerned the VACF, the equivalent Langevin equation describing Brownian motion of particles with a harmonic potential is adapted to the problem and reveals an exponentially decaying oscillatory pattern influenced by the conservative force parameter, dissipative parameter and temperature. Although the proposed model for obtaining the self-diffusion coefficient with consideration of the conservative force could not be verified due to computational complexities, nonetheless the Arrhenius dependency of the self-diffusion coefficient to temperature and pressure permits to certify our model over a definite range of DPD parameters.

Modeling Self-Assembly of the Surfactants into Biological Bilayer Membranes with Special Chemical Structure Using Dissipative Particle Dynamics Method

The aim of this study is to simulate the self-assembly of the surfactant molecules with special chemical structure and bending stiffness into bilayer membranes using a mesoscopic Dissipative Particle Dynamics (DPD) method. Thesurfactants are modeled with special chemical structure and bending stiffness. To confirm that the novel model is physical, we determine the interaction parameters based on matching the compressibility and solubility of the DPD system with real physics of the fluid. To match the mutual solubility for binary fluids, we use the relation between DPD parameters and -parameters in Flory-Huggins-type models. Unsaturated bonds can change the stiffness of a lipid membrane which is modeled by introducing a bond bending potential. To verify our model we investigate the effect of surfactant structure like chain length and stiffness of those molecules on the properties of the modeled membrane as area per surfactant. To validate our results, we also compare them with the theoretical calculations as well as with the experimental and other existing simulations results. We show that there is a good coincidence between all of the results.

Interaction parameters between carbon nanotubes and water in Dissipative Particle Dynamics

Flow of water past an array of single-walled carbon nanotubes (SWNTs) is simulated in this work to determine the interaction parameters of carbon nanotubes (CNTs) and water using Dissipative Particle Dynamics (DPD). For this flow configuration, results from molecular dynamics simulations by Walther et al. are available and can be used for validation (Phys. Rev. E, 2004, 062201). The hydrodynamic properties for SWNT (32, 0) with diameter of 2.5 nm were determined in different Reynolds number flows. A set of appropriate DPD parameters was found so that the drag coefficients of the CNT agreed well with the Stokes–Oseen analytical solution and the fluid slip length on the CNT wall was comparable with the Walther et al. results. It was also found that it is feasible to apply these parameters in longer length and time scales by increasing the number of water molecules grouped into each DPD bead and still maintain the hydrodynamic properties of CNTs as well as their hydrophobic surface character.

Dissipative Particle Dynamics: Effects of Parameterization and Thermostating Schemes on Rheology

We report a sensitivity analysis for dissipative particle dynamics (DPD) method, showing that it is highly sensitive to parameterization, integration method, and thermostating schemes. Practical guidelines are presented to maintain Newtonian characteristics of DPD fluid at a possible range of shear rates over wide-ranging DPD parameters. The effects of cutoff radii and the weight functions exponent in DPD triple forces are studied on viscosity, and optimized ranges are recommended for effective temperature control. Moreover, the advantages and shortcomings of DPD method is manifested using alternative thermostats (Peters, Lowe-Andersen, and Nosé-Hoover-Lowe-Andersen) in simultaneously meeting proper temperature control and Newtonian behavior in moderate to high shear rate regimes. It was shown that improper temperature control may lead to nonphysical shear-thickening. Diverse ranges of simulation settings are identified that are capable of delivering Newtonian viscosities from 0.83 to 46.3 in DPD units. This study also aims to reduce the risk of numerical artefacts giving seemingly accurate results in single-species, suspensions, or other complex systems.