Multiparticle Collision Dynamics Research Articles

Unveiling the transition of tumbling and tank-treading dynamics of star-shaped polyelectrolytes in shear flow by modulating the solution's dielectric properties.

The effects of the solution's dielectric properties on the conformation and dynamics of star-shaped polyelectrolytes in shear flow are investigated using a hybrid simulation method coupling multi-particle collision dynamics and molecular dynamics. The simulation results showed that by modulating the dielectric properties of the solution, star-shaped polyelectrolytes showed a three-step dynamic behavior transition from tumbling to tank-treading to tumbling dynamics under shear flow. The analysis indicated that this distinct transition in dynamics could be attributed to the uneven distribution of counterions induced by shear on the chain, resulting in a change in the polyelectrolyte conformation and degree of segmental alignment in arms. These findings contribute to a comprehensive understanding of the non-equilibrium dynamics of star-shaped polyelectrolytes in shear flow and offer a viable approach for controlling the dynamic behavior of star-shaped polyelectrolytes by adjusting the dielectric properties of the solution.

Multiparticle collision dynamics simulations of hydrodynamic interactions in colloidal suspensions: How well does the discrete particle approach do at short range?

The multiparticle collision dynamics (MPCD) simulation method is an attractive technique for studying the effects of hydrodynamic interactions in colloidal suspensions because of its flexibility, computational efficiency, and ease of implementation. Here, we analyze an extension of the basic MPCD method in which colloidal particles are discretized with a surface mesh of sensor nodes/particles that interact with solvent particles (MPCD + Discrete Particle or MPCD + DP). We use several situations that have been described analytically to probe the impact of colloidal particle mesh resolution on the ability of the MPCD + DP method to resolve short-ranged hydrodynamic interactions, which are important in crowded suspensions and especially in self-assembling systems that create high volume fraction phases. Specifically, we consider (A) hard-sphere diffusion near a wall, (B) two-particle diffusion, (C) hard-sphere diffusion in crowded suspensions, and (D) the dynamics of aggregation in an attractive colloidal suspension. We show that in each case, the density of sensor nodes plays a significant role in the accuracy of the simulation and that a surprisingly high number of surface nodes are needed to fully capture hydrodynamic interactions.

Magneto-Permeability Effect in Ferrofluid Flow Through Porous Media Studied via Multiparticle Collision Dynamics

AbstractAs more and more promising applications of magnetic nanoparticles in complicated environments are explored, their flow properties in porous media are of increasing interest. We here propose a hybrid approach based on the multiparticle collision dynamics method extended to porous media via friction forces and coupled with Brownian dynamics simulations of the rotational motion of magnetic nanoparticles’ magnetic moment. We simulate flow in planar channels homogeneously filled with a porous medium and verify our implementation by reproducing the analytical velocity profile of the Darcy–Brinkman model in the non-magnetic case. In the presence of an externally applied magnetic field, the non-equilibrium magnetization and friction forces lead to field-dependent velocity profiles that result in effective, field-dependent permeabilities. We provide a theoretical expression for this magneto-permeability effect in analogy with the magneto-viscous effect. Finally, we study the flow through planar channels, where only the walls are covered with a porous medium. We find a smooth crossover from the Poiseuille profile in the center of the channel to Brinkman–Darcy flow in the porous layers. We propose a simple estimate of the thickness of the porous layer based on the flow rate and maximum flow velocity.

Diffusive dynamics of a model protein chain in solution.

A Markov state model is a powerful tool that can be used to track the evolution of populations of configurations in an atomistic representation of a protein. For a coarse-grained linear chain model with discontinuous interactions, the transition rates among states that appear in the Markov model when the monomer dynamics is diffusive can be determined by computing the relative entropy of states and their mean first passage times, quantities that are unchanged by the specification of the energies of the relevant states. In this paper, we verify the folding dynamics described by a diffusive linear chain model of the crambin protein in three distinct solvent systems, each differing in complexity: a hard-sphere solvent, a solvent undergoing multi-particle collision dynamics, and an implicit solvent model. The predicted transition rates among configurations agree quantitatively with those observed in explicit molecular dynamics simulations for all three solvent models. These results suggest that the local monomer-monomer interactions provide sufficient friction for the monomer dynamics to be diffusive on timescales relevant to changes in conformation. Factors such as structural ordering and dynamic hydrodynamic effects appear to have minimal influence on transition rates within the studied solvent densities.

Shear-induced structural and viscosity changes of amphiphilic patchy nanocubes in suspension

Our study demonstrates the relationship between the design of patchy nanocubes, their self-assembled structures including shear-induced structural changes and the rheological properties of suspensions through coarse-grained molecular simulations.

Particle-based and continuum models for confined nematics in two dimensions.

We use the particle-based stochastic multi-particle collision dynamics (N-MPCD) algorithm to simulate confined nematic liquid crystals in regular two-dimensional polygons such as squares, pentagons and hexagons. We consider a range of values of the nematicities, U, and simulation domain sizes, R, that canvass nano-sized polygons to micron-sized polygons. We use closure arguments to define mappings between the N-MPCD parameters and the parameters in the continuum deterministic Landau-de Gennes framework. The averaged N-MPCD configurations agree with those predicted by Landau-de Gennes theory, at least for large polygons. We study relaxation dynamics or the non-equilibrium dynamics of confined nematics in polygons, in the N-MPCD framework, and the kinetic traps bear strong resemblance to the unstable saddle points in the Landau-de Gennes framework. Finally, we study nematic defect dynamics inside the polygons in the N-MPCD framework and the finite-size effects slow down the defects and attract them to polygon vertices. Our work is a comprehensive comparison between particle-based stochastic N-MPCD methods and deterministic/continuum Landau-de Gennes methods, and this comparison is essential for new-age multiscale theories.

Mesoscale simulations of diffusion and sedimentation in shape-anisotropic nanoparticle suspensions.

We determine the long-time self-diffusion coefficient and sedimentation coefficient for suspensions of nanoparticles with anisotropic shapes (octahedra, cubes, tetrahedra, and spherocylinders) as a function of nanoparticle concentration using mesoscale simulations. We use a discrete particle model for the nanoparticles, and we account for solvent-mediated hydrodynamic interactions between nanoparticles using the multiparticle collision dynamics method. Our simulations are compared to theoretical predictions and experimental data from existing literature, demonstrating good agreement in the majority of cases. Further, we find that the self-diffusion coefficient of the regular polyhedral shapes can be estimated from that of a sphere whose diameter is the average of their inscribed and circumscribed sphere diameters.

Confined Dynamics in Spherical Polymer Brushes.

We investigate the dynamics of polymers grafted to spherical nanoparticles in solution using hybrid molecular dynamics simulations with a coarse-grained solvent modeled via the multiparticle collision dynamics algorithm. The mean-square displacements of monomers near the surface of the nanoparticle exhibit a plateau on intermediate time scales, indicating confined dynamics reminiscent of those reported in neutron spin-echo experiments. The confined dynamics vanish beyond a specific radial distance from the nanoparticle surface that depends on the polymer grafting density. We show that this dynamical confinement transition follows theoretical predictions for the critical distance associated with the structural transition from confined to semidilute brush regimes. These findings suggest the existence of a hitherto unreported dynamic length scale connected with theoretically predicted static fluctuations in spherical polymer brushes and provide new insights into recent experimental observations.

The role of flow in the self-assembly of dragline spider silk proteins

Hydrodynamic flow in the spider duct induces conformational changes in dragline spider silk proteins (spidroins) and drives their assembly, but the underlying physical mechanisms are still elusive. Here we address this challenging multiscale problem with a complementary strategy of atomistic and coarse-grained molecular dynamics simulations with uniform flow. The conformational changes at the molecular level were analyzed for single-tethered spider silk peptides. Uniform flow leads to coiled-to-stretch transitions and pushes alanine residues into β sheet and poly-proline II conformations. Coarse-grained simulations of the assembly process of multiple semi-flexible block copolymers using multi-particle collision dynamics reveal that the spidroins aggregate faster but into low-order assemblies when they are less extended. At medium-to-large peptide extensions (50%–80%), assembly slows down and becomes reversible with frequent association and dissociation events, whereas spidroin alignment increases and alanine repeats form ordered regions. Our work highlights the role of flow in guiding silk self-assembly into tough fibers by enhancing alignment and kinetic reversibility, a mechanism likely relevant also for other proteins whose function depends on hydrodynamic flow.

Multi-particle collision dynamics for a coarse-grained model of soft colloids applied to ring polymers.

The simulation of polymer solutions often requires the development of methods that accurately include hydrodynamic interactions. Resolution on the atomistic scale is too computationally expensive to cover mesoscopic time and length scales on which the interesting polymer phenomena are observed. Therefore, coarse-graining methods have to be applied. In this work, the solvent is simulated using the well-established multi-particle collision dynamics scheme, and for the polymer, different coarse-graining methods are employed and compared against the monomer resolved Kremer-Grest model by their resulting diffusion coefficients. This research builds on previous work [Ruiz-Franco et al., J. Chem. Phys. 151, 074902 (2019)], in which star polymers and linear chains in a solvent were simulated and two different coarse-graining methods were developed, in order to increase computational efficiency. The present work extends this approach to ring polymers and seeks to refine one of the authors' proposed model: the penetrable soft colloid model. It was found that both proposed models are not well suited to ring polymers; however, the introduction of a factor to the PSC model delivers satisfying results for the diffusion behavior by regulating the interaction intensity with the solvent.

Control of the aggregate structure of magnetic cubic particles in a quasi-2D suspension via both the strength and direction of an applied magnetic field (multi-particle collision dynamics simulations)

We have first investigated a feasibility of a malt-particle collision dynamics (MPCD) method by addressing whether or not the translational and rotational Brownian motion is activated at a physically reasonable level. From the results with respect to the root mean square velocities, we conclude that the MPCD method is a quite feasible simulation technique for a suspension composed of magnetic cubic particles. Then we have applied the MPCD simulation method to a quasi-2D system of magnetic cubic particles in order to control a regime change in the internal structure of particle aggregates by means of the strength and direction of a uniform applied magnetic field. In the case of a magnetic field applied in a certain direction from the 2D plane, a regime change in the internal structure of large densely-packed clusters into a regular configuration is more effectively attained than a magnetic field applied along the 2D plane.

Using heterogeneous GPU nodes with a Cabana-based implementation of MPCD

The Kokkos based library Cabana, which has been developed in the Co-design Center for Particle Applications (CoPA), is used for the implementation of Multi-Particle Collision Dynamics (MPCD), a particle-based description of hydrodynamic interactions. Cabana allows for a function portable implementation, which has been used to study the interplay between CPU and GPU usage on a multi-node system as well as analysis of said interplay with performance analysis tools. As a result, we see most advantages in a homogeneous GPU usage, but we also discuss the extent to which heterogeneous applications might be more performant, using both CPU and GPU concurrently.

Particle-based mesoscopic model for phase separation in a binary fluid mixture.

A mesoscopic simulation model to study the phase separation in a binary fluid mixture in three dimensions (3D) is presented here by augmenting the existing particle-based multiparticle collision dynamics (MPCD) algorithm. The approach describes the nonideal equationof the fluid state by incorporating the excluded-volume interaction between the two components within the framework of stochastic collision, which depends on the local fluid composition and velocity. Calculating the nonideal contribution to the pressure both from simulation and analytics shows the model to be thermodynamically consistent. A phase diagram to explore the range of parameters that give rise to phase separation in the model is investigated. The interfacial width and phase growth obtained from the model agree with the literature for a wide range of temperatures and parameters.

Confined Electrolytes Show Bulk Dynamics Modulated by Hydrodynamic Couplings with the Walls

We use numerical simulations at the mesoscopic scale, namely, multiparticle collision dynamics (MPCD), to investigate the properties of electrolyte solutions in a charged slit pore. The solution is described within the primitive model of electrolytes, where ions are charged hard spheres embedded in a dielectric medium. Hydrodynamic couplings between ions and with the charged walls are precisely accounted for by the MPCD algorithm. We show that the dynamic properties of ions in this situation strongly differ from the behavior at infinite dilution (ideal case), contrary to what is usually assumed in the usual Poisson-Nernst-Planck description of this kind of systems. As a consequence of confinement, the diffusion coefficients of ions unexpectedly increase with the average ionic density in the systems. This is due to a decrease of the proportion of ions that are slowed down by the wall. Moreover, nonequilibrium simulations are used to estimate the electrical conductivity of these confined electrolytes. We show that the simulation results can be accounted for quantitatively by combining bulk descriptions of the electrical conductivity of electrolytes with a simple description of the hydrodynamics of ions in a slit pore.

Behaviors of a Polymer Chain in Channels: From Zimm to Rouse Dynamics

The effects of confinement and hydrodynamic interactions on single-chain diffusion behaviors are studied by using a combination of molecular dynamics and multiparticle collision dynamics simulations. For polymers in free space, the simulation results showed that the diffusion coefficient D∞ for long chains scales with the chain length N as D∞ ∼ N–ν (ν = 0.588), consistent with the Zimm dynamics, but it deviates from the Zimm dynamics for short chains. For polymers confined in channels with width H, the diffusion coefficient is found to follow two different scaling relations. The observed behaviors could be understood by introducing a microscopic hydrodynamic length ξh, below which the overall effect of hydrodynamic interactions becomes less important. For a confined chain, the diffusion behavior exhibits a crossover from Zimm (nondraining) to Rouse (free draining) dynamics as the channel size H decreases. When H is larger than ξh, the confinement experienced by the polymer chain is weak and the diffusion coefficient scales as D ∼ H0.7, in accordance with the prediction of blob theory; when H is smaller than ξh, D becomes independent of H, implying a free draining condition. A general analytical expression of D is derived by extending the partially permeable sphere model to the blob scale, which gives a quantitative description of the transition from Zimm to Rouse dynamics as H decreases.

What quantity of charge on the nanoparticle can result in a hybrid morphology of the nanofluid and a higher thermal conductivity?

One of the most important mechanisms for promotion of the thermal conductivity(TC) of nanofluid is aggregation of nanoparticles. In present work, a hybrid method of multi-particle collision dynamics and molecular dynamics (MPCD-MD) is employed to evaluate the aggregation morphology and TC of Cu-H2O nanofluid. Numerical simulations for various quantity of charges (QoC) on nanoparticles are conducted, and three kinds of morphology of nanoparticles distribution, whole aggregation morphology at lower QoC, hybrid morphology at moderate QoC and fully dispersed morphology at greater QoC, are obtained for the first time in microscopic simulations. For hybrid morphologies, the fractal dimension first drops and then rises with increasing QoC, since aggregates can break up into several clusters at relatively low QoC and can be fully dispersed at relatively high QoC. Instead, the TC first increases and then decreases, and the TC can reach a peak at a certain QoC. The underneath mechanism should be a balance between the effects of nanolayers and Kapitza resistance. This can provide helpful guidance to prepare nanofluids with higher TC.

Dynamics of semi‐flexible and breakable fibers under Poiseuille flow

AbstractIn the processing of fiber‐reinforced polymer composites, especially in injection molding, the fiber's orientation, length, and distribution vary depending on the location of the channel flow and its properties, which affects the performance of final products. To investigate the intricate behavior of fiber suspensions under Poiseuille flow, we used the hybrid simulation approach, multiparticle collision dynamics–molecular dynamics (MPC‐MD), which takes hydrodynamic interactions and fiber properties (strength, flexibility) into account. For non‐breakable and rodlike fibers, fibers align well along the flow direction while showing more alignment near the wall. As fiber becomes breakable and/or flexible, the length and orientation of fibers strongly depend on their properties. The interesting phenomenon is specifically seen for breakable and semiflexible fibers, where the orientation of the fiber exhibits non‐monotonic behavior depending on the flow rate. This complex behavior highlights the importance of comprehending the dynamics of many types of fibers and necessitates research into the best conditions for injection molding.

Structure and dynamics of chemically active ring polymers: swelling to collapse.

The ring structures are common in many synthetic or natural systems and experience both local and long-range forces by chemical sensing. This work is an effort to investigate the structural and dynamical properties of a chemically active ring in an explicit solvent bath utilizing hybrid molecular dynamics (MD) and multiparticle collision dynamics (MPCD) simulation techniques. We show that by tuning the chemical properties of the ring, it can be converted from a chemo-attractant to a chemo-repellent, thereby changing the steady state to be either collapsed or swelled as compared to its passive limit. We quantify these observations by comparing the scaling laws, local structures and the dynamics of active and passive rings. Furthermore, we show the impact of varying numbers of active sites by calculating the contact probability of the collapse state that highlights diverse structures. We also analyze the dynamics of the ring by finding the relaxation time and the mean square displacement of the centre of mass. A faster relaxation with enhanced diffusion is observed for the active rings.

Negative differential thermal resistance in a two-dimensional gas model

The negative differential thermal resistance (NDTR) effect refers to a phenomenon that may take place in a heat transport system where the heat current counterintuitively decreases as the temperature difference between heat baths increases. Understanding and controlling the NDTR properties of out-of-equilibrium systems and using them to design new functional thermal devices are the major challenges of modern science and technology, which has important theoretical significance and application prospects. Up to now, the various lattice models representing solid materials have been taken to study the NDTR properties, but the fluid models have not received enough attention. It has recently been shown that in one-dimensional hard-point gas models representing fluids, there is a mechanism for NDTR induced by heat baths. The mechanism for NDTR in such a system depends on the simple fact that decreasing the temperature of the cold bath can weaken the motion of particles and decrease the collision rate between particles and the hot bath, thus impeding thermal exchange between the cold and hot baths. In this paper, we study how this mechanism works in more general two-dimensional gas models described by multi-particle collision dynamics. The gas models we consider are in a finite rectangular region of two-dimensional space with each end in contact with a heat bath. Based on the analytical results and numerical simulations, we show that the mechanism underlying NDTR induced by heat baths is also in effect for two-dimensional gas models and is applicable for describing systems with small sizes and weak interactions. Our result, together with that previously obtained in one-dimensional gas models, provides strong evidence that gas systems can exhibit NDTR by decreasing the temperature of the heat bath, which sheds new light on the exploring direction for developing various fluidic thermal control devices.

Active nematic liquid crystals simulated by particle-based mesoscopic methods.

Two Multi-particle collision dynamics algorithms that simulate nematic liquid crystals are generalised to reproduce active behaviour. One of the algorithms is due to Shendruk and Yeomans and is based on particles that carry an orientation vector ordered by a mean-field energy [T. N. Shendruk and J. M. Yeomans, Soft Matter, 2015, 11, 5101]. In the other algorithm, due to Mandal and Mazza, particles possess an order parameter tensor which evolves according to the Qian-Sheng model of nematohydrodynamics [S. Mandal and M. G. Mazza, Phys. Rev. E, 2019, 99, 063319]. For both methods activity is incorporated through a force proportional to the divergence of the local average order parameter tensor. Both implementations produce disclination curves in the nematic fluid that undergo nucleation and self-annihilation dynamics. Topological defects are found to be consistent with those observed in recent experiments of three-dimensional active nematics. Results permit to compare the length-scales over which the different nematic Multi-particle collision dynamics methods operate. The structure and dynamics of the orientation and flow fields agree with those obtained recently in numerical studies of continuum three-dimensional active nematics. Overall, our results open the opportunity to use mesoscopic particle-based approaches to study active liquid crystals in situations such as nonequilibrium states driven by flow or colloidal particles in active anisotropic solvents.