Dynamics of solutes with hydrodynamic interactions: comparison between Brownian dynamics and stochastic rotation dynamics simulations

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.

On analytical theories for conductivity and self-diffusion in concentrated electrolytes

Describing analytically the transport properties of electrolytes, such as their conductivity or the self-diffusion of the ions, has been a central challenge of chemical physics for almost a century. In recent years, this question has regained some interest in light of Stochastic Density Field Theory (SDFT) - an analytical framework that allows the approximate determination of density correlations in fluctuating systems. In spite of the success of this theory to describe dilute electrolytes, its extension to concentrated solutions raises a number of technical difficulties, and requires simplified descriptions of the short-range repulsion between the ions. In this article, we discuss recent approximations that were proposed to compute the conductivity of electrolytes, in particular truncations of Coulomb interactions at short distances. We extend them to another observable (the self-diffusion coefficient of the ions) and compare them to earlier analytical approaches, such as the mean spherical approximation and mode-coupling theory. We show how the treatment of hydrodynamic effects in SDFT can be improved, that the choice of the modified Coulomb interactions significantly affects the determination of the properties of the electrolytes, and that comparison with other theories provides a guide to extend SDFT approaches in this context.

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.

Nanoparticle Assembly and Oriented Attachment: Correlating Controlling Factors to the Resulting Structures

Nanoparticle assembly and attachment are common pathways of crystal growth by which particles organize into larger scale materials with hierarchical structure and long-range order. In particular, oriented attachment (OA), which is a special type of particle assembly, has attracted great attention in recent years because of the wide range of material structures that result from this process, such as one-dimensional (1D) nanowires, two-dimensional (2D) sheets, three-dimensional (3D) branched structures, twinned crystals, defects, etc. Utilizing in situ transmission electron microscopy techniques, researchers observed orientation-specific forces that act over short distances (∼1 nm) from the particle surfaces and drive the OA process. Integrating recently developed 3D fast force mapping via atomic force microscopy with theories and simulations, researchers have resolved the near-surface solution structure, the molecular details of charge states at particle/fluid interfaces, inhomogeneity of surface charges, and dielectric/magnetic properties of particles that influence short- and long-range forces, such as electrostatic, van der Waals, hydration, and dipole-dipole forces. In this review, we discuss the fundamental principles for understanding particle assembly and attachment processes, and the controlling factors and resulting structures. We review recent progress in the field via examples of both experiments and modeling, and discuss current developments and the future outlook.

Predictive Design and Analysis of Drug Transport by Multiscale Computational Models Under Uncertainty

Computational modeling of drug delivery is becoming an indispensable tool for advancing drug development pipeline, particularly in nanomedicine where a rational design strategy is ultimately sought. While numerous in silico models have been developed that can accurately describe nanoparticle interactions with the bioenvironment within prescribed length and time scales, predictive design of these drug carriers, dosages and treatment schemes will require advanced models that can simulate transport processes across multiple length and time scales from genomic to population levels. In order to address this problem, multiscale modeling efforts that integrate existing discrete and continuum modeling strategies have recently emerged. These multiscale approaches provide a promising direction for bottom-up in silico pipelines of drug design for delivery. However, there are remaining challenges in terms of model parametrization and validation in the presence of variability, introduced by multiple levels of heterogeneities in disease state. Parametrization based on physiologically relevant in vitro data from microphysiological systems as well as widespread adoption of uncertainty quantification and sensitivity analysis will help address these challenges.

Diffusion and sedimentation in colloidal suspensions using multiparticle collision dynamics with a discrete particle model

We study self-diffusion and sedimentation in colloidal suspensions of nearly hard spheres using the multiparticle collision dynamics simulation method for the solvent with a discrete mesh model for the colloidal particles (MD+MPCD). We cover colloid volume fractions from 0.01 to 0.40 and compare the MD+MPCD simulations to experimental data and Brownian dynamics simulations with free-draining hydrodynamics (BD) as well as pairwise far-field hydrodynamics described using the Rotne-Prager-Yamakawa mobility tensor (BD+RPY). The dynamics in MD+MPCD suggest that the colloidal particles are only partially coupled to the solvent at short times. However, the long-time self-diffusion coefficient in MD+MPCD is comparable to that in experiments, and the sedimentation coefficient in MD+MPCD is in good agreement with that in experiments and BD+RPY, suggesting that MD+MPCD gives a reasonable description of hydrodynamic interactions in colloidal suspensions. The discrete-particle MD+MPCD approach is convenient and readily extended to more complex shapes, and we determine the long-time self-diffusion coefficient in suspensions of nearly hard cubes to demonstrate its generality.

Preference Parameters for the Calculation of Thermal Conductivity by Multiparticle Collision Dynamics

Calculation of the thermal conductivity of nanofluids by molecular dynamics (MD) is very common. Regrettably, general MD can only be employed to simulate small systems due to the huge computation workload. Instead, the computation workload can be considerably reduced due to the coarse-grained fluid when multiparticle collision dynamics (MPCD) is employed. Hence, such a method can be utilized to simulate a larger system. However, the selection of relevant parameters of MPCD noticeably influences the calculation results. To this end, parameterization investigations for various bin sizes, number densities, time-steps, rotation angles and temperatures are carried out, and the influence of these parameters on the calculation of thermal conductivity are analyzed. Finally, the calculations of thermal conductivity for liquid argon, water and Cu-water nanofluid are performed, and the errors compared to the theoretical values are 3.4%, 1.5% and 1.2%, respectively. This proves that the method proposed in the present work for calculating the thermal conductivity of nanofluids is applicable.

Microscopic flow around a diffusing particle

We report here on the computation of the microscopic flow induced by the motion of a small tagged particle in a fluid from molecular dynamic simulations. It is found that the hydrodynamical Stokes solution with slip boundary conditions is recovered at only a few diameters away from the tagged particle. However, fluctuations of the diffusing particle itself induce a renormalization of the bath viscosity and, more strikingly, an apparent violation of the non-penetrability of the particles in the laboratory frame. The expected zero normal velocity at contact is satisfied only in the particle frame, or for heavy particles. Further evidence of this generalized boundary condition is given by the evaluation of the flow in a granular gas using data from particle tracking experiments.

Comparison of different coupling schemes between counterions and charged nanoparticles in multiparticle collision dynamics

We applied the multiparticle collision dynamics (MPC) simulation technique to highly asymmetric electrolytes in solution, i.e., charged nanoparticles and their counterions in a solvent. These systems belong to a domain of solute size which ranges between the electrolyte and the colloidal domains, where most analytical theories are expected to fail, and efficient simulation techniques are still missing. MPC is a mesoscopic simulation method which mimics hydrodynamics properties of a fluid, includes thermal fluctuations, and can be coupled to a molecular dynamics of solutes. We took advantage of the size asymmetry between nanoparticles and counterions to treat the coupling between solutes and the solvent bath within the MPC method. Counterions were coupled to the solvent bath during the collision step and nanoparticles either through a direct interaction force or with stochastic rotation rules which mimic stick boundary conditions. Moreover, we adapted the simulation procedure to address the issue of the strong electrostatic interactions between solutes of opposite charges. We show that the short-ranged repulsion between counterions and nanoparticles can be modeled by stochastic reflection rules. This simulation scheme is very efficient from a computational point of view. We have also computed the transport coefficients for various densities. The diffusion of counterions was found in one case to increase slightly with the volume fraction of nanoparticles. The deviation of the electric conductivity from the ideal behavior (solutes at infinite dilution without any direct interactions) is found to be strong.

Effect of Hydrodynamic Interactions on Self-Diffusion of Quasi-Two-Dimensional Colloidal Hard Spheres

We compare experimental results from a quasi-two-dimensional colloidal hard sphere fluid to a Monte Carlo simulation of hard disks with small particle displacements. The experimental short-time self-diffusion coefficient D(S) scaled by the diffusion coefficient at infinite dilution, D(0), strongly depends on the area fraction, pointing to significant hydrodynamic interactions at short times in the experiment, which are absent in the simulation. In contrast, the area fraction dependence of the experimental long-time self-diffusion coefficient D(L)/D(0) is in quantitative agreement with D(L)/D(0) obtained from the simulation. This indicates that the reduction in the particle mobility at short times due to hydrodynamic interactions does not lead to a proportional reduction in the long-time self-diffusion coefficient. Furthermore, the quantitative agreement between experiment and simulation at long times indicates that hydrodynamic interactions effectively do not affect the dependence of D(L)/D(0) on the area fraction. In light of this, we discuss the link between structure and long-time self-diffusion in terms of a configurational excess entropy and do not find a simple exponential relation between these quantities for all fluid area fractions.

Effects of hydrodynamic interactions on the crystallization of passive and active colloidal systems

Effects of hydrodynamic interactions (HI) on the crystallization of a two-dimensional suspension of colloidal particles have been investigated, by applying a multiscale simulation method combining multiparticle collision dynamics for solvent particles with standard molecular dynamics for the colloids. For a passive system, we find that HI slightly shifts the freezing point to a smaller density, while the equilibrium structure remains nearly unchanged for a given global order parameter. For an active system, however, HI can significantly shift the freezing density to a higher value and the freezing transition becomes more continuous compared to its passive counterpart. This HI-induced shift becomes more remarkable with increasing propelling force. In addition, HI may also enhance the structural heterogeneities in an active system. For both passive and active systems, it is shown that HI can accelerate the relaxation process to their final steady state.

Computation of shear viscosity of colloidal suspensions by SRD-MD

The behaviour of sheared colloidal suspensions with full hydrodynamic interactions (HIs) is numerically studied. To this end, we use the hybrid stochastic rotation dynamics-molecular dynamics (SRD-MD) method. The shear viscosity of colloidal suspensions is computed for different volume fractions, both for dilute and concentrated cases. We verify that HIs help in the collisions and the streaming of colloidal particles, thereby increasing the overall shear viscosity of the suspension. Our results show a good agreement with known experimental, theoretical, and numerical studies. This work demonstrates the ability of SRD-MD to successfully simulate transport coefficients that require correct modelling of HIs.