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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 average of their inscribed and circumscribed sphere diameters., Comment: 13 pages, 7 figures

We report molecular dynamics simulation results on the equilibrium properties of polymer thin films adsorbed onto flat and curved substrates. We first systematically determine the contact angle of polymer droplets on flat substrates as a function of the substrate-monomer adsorption strength and degree of polymerization. Focussing on the fully wetted regime, we then investigate the effect of the substrate's topography on the polymer film configuration by using substrates with varying mean curvature. We find that polymer chains close to the substrate are significantly stretched (compressed) in regions of high negative (positive) mean curvature. Further, we find partial dewetting near regions of high mean curvature for thin polymer films. For thicker films, the polymers fully cover the substrate and the shape of the liquid-vapor interface largely follows the shape of the substrate. As the film thickness is increased further, the liquid-vapor interface becomes completely flat. These simulation results are corroborated by analytic calculations using a simplified continuum model that treats the adsorbed polymers as an incompressible medium. Our findings show how the substrate topography influences the conformation of individual chains as well as the shape of the entire film., Comment: 26 pages, 9 figures

We investigate with numerical simulations the molecular origin of viscosity in melts of flexible and semiflexible oligomer rings in comparison to corresponding systems with linear chains. The strong increase of viscosity with ring stiffness is linked to the formation of entangled clusters, which dissolve under shear. This shear-induced breakup and alignment of rings in the flow direction lead to pronounced shear-thinning and non-Newtonian behavior. In melts of linear chains, the viscosity can be associated with the (average) number of entanglements between chains, which also dissolve under shear. While blends of flexible and semiflexible rings are mixed at rest, the two species separate under flow. This phenomenon has potential applications in microfluidic devices to segregate ring polymers of similar mass and chemical composition by their bending rigidity.

We investigate the self-assembly of amphiphilic nanocubes under rest and shear using molecular dynamics (MD) simulations and kinetic Monte Carlo (KMC) calculations. These particles combine both interaction and shape anisotropy, making them valuable models for studying folded proteins and DNA-functionalized nanoparticles. The nanocubes can self-assemble into various finite-sized aggregates ranging from rods to self-avoiding random walks, depending on the number and placement of the hydrophobic faces. Our study focuses on suspensions containing multi- and one-patch cubes, with their ratio systematically varied. When the binding energy is comparable to the thermal energy, the aggregates consist of only few cubes that spontaneously associate/dissociate. However, highly stable aggregates emerge when the binding energy exceeds the thermal energy. Generally, the mean aggregation number of the self-assembled clusters increases with the number of hydrophobic faces and decreases with the fraction of one-patch cubes. In sheared suspensions, the more frequent collisions between nanocube clusters lead to faster aggregation dynamics but also to smaller terminal steady-state mean cluster sizes. The MD and KMC simulations are in excellent agreement, and the analysis of the rate kernels enables the identification of the primary mechanisms responsible for the (shear-induced) cluster growth and breakup.

Living cells are characterized by the micrometric confinement of various macromolecules at high concentrations. Using droplets containing binary polymer blends as artificial cells, we previously showed that cell-sized confinement causes phase separation of the binary polymer solutions because of the length-dependent wetting of the polymers. Here we demonstrate that the wetting-induced heterogeneity of polymers also emerges in single-component polymer solutions. The resulting heterogeneity leads to a slower transport of small molecules at the center of cell-sized droplets than that in bulk solutions. This heterogeneous distribution is observed when longer polymers with lower wettability are localized at the droplet center. Molecular simulations support this wetting-induced heterogeneous distribution by polymer length. Our results suggest that cell-sized confinement functions as a structural regulator for polydisperse polymer solutions that specifically manipulate the diffusion of molecules, particularly those with sizes close to the correlation length of the polymer chains.

The formation of (bio)molecular condensates via liquid-liquid phase separation in cells has received increasing attention, as these coacervates play important functional and regulatory roles within biological systems. However, the majority of studies focused on the behavior of pure systems in bulk solutions, thus neglecting confinement effects and the interplay between the numerous molecules present in cells. To advance our knowledge, we perform simulations of binary polymer mixtures in droplets, considering both monodisperse and polydisperse molecular weight distributions for the longer polymer species. We find that confinement induces a spatial separation of the polymers by length, with the shorter ones moving to the droplet surface. This partitioning causes a distinct increase of the local polymer concentration in the droplet center, which is more pronounced in polydisperse systems. Consequently, the systems exhibit liquid-liquid phase separation at average polymer concentrations where bulk systems are still in the one-phase regime.

Wetting and drying phenomena are studied for flexible and semiflexible polymer solutions via coarse-grained molecular dynamics simulations and density functional theory calculations. The study is based on the use of Young's equation for the contact angle, determining all relevant surface tensions from the anisotropy of the pressure tensor. The solvent quality (or effective temperature, equivalently) is varied systematically, while all other interactions remain unaltered. For flexible polymers, the wetting transition temperature $T_{\rm w}$ increases monotonically with chain length $N$, while the contact angle at temperatures far below $T_{\rm w}$ is independent of $N$. For semiflexible polymer solutions, $T_{\rm w}$ varies non-monotonically with the persistence length: Initially, $T_{\rm w}$ increases with increasing chain stiffness and reaches a maximum, but then a sudden drop of $T_{\rm w}$ is observed, which is associated with the isotropic-nematic transition of the system.

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 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 BD and BD+RPY, and the sedimentation coefficient in MD+MPCD is in good agreement with that in BD+RPY, suggesting that MD+MPCD gives a reasonable description of the 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., Comment: 13 pages, 8 figures

Binary mixtures of semiflexible polymers with the same chain length but different persistence lengths separate into two coexisting different nematic phases when the osmotic pressure of the lyotropic solution is varied. Molecular Dynamics simulations and Density Functional Theory predict phase diagrams either with a triple point, where the isotropic phase coexists with two nematic phases, or a critical point of unmixing within the nematic mixture. The difference in locally preferred bond angles between the constituents drives this unmixing without any attractive interactions between monomers.

We study the evaporation-induced stratification of a mixture of short and long polymer chains in a drying droplet using molecular simulations. We systematically investigate the effects of hydrodynamic interactions (HI) on this process by comparing hybrid simulations accounting for HI between polymers through the multiparticle collision dynamics technique with free-draining Langevin dynamics simulations neglecting the same. We find that the dried supraparticle morphologies are homogeneous when HI are included but are stratified in core--shell structures (with the short polymers forming the shell) when HI are neglected. The simulation methodology unambiguously attributes this difference to the treatment of the solvent in the two models. We rationalize the presence (or absence) of stratification by measuring phenomenological multicomponent diffusion coefficients for the polymer mixtures. The diffusion coefficients show the importance of not only solvent backflow but also HI between polymers in controlling the dried supraparticle morphology., Comment: 13 pages, 9 figures

Neural networks (NNs) are employed to predict equations of state from a given isotropic pair potential using the virial expansion of the pressure. The NNs are trained with data from molecular dynamics simulations of monoatomic gases and liquids, sampled in the $NVT$ ensemble at various densities. We find that the NNs provide much more accurate results compared to the analytic low-density limit estimate of the second virial coefficient. Further, we design and train NNs for computing (effective) pair potentials from radial pair distribution functions, $g(r)$, a task which is often performed for inverse design and coarse-graining. Providing the NNs with additional information on the forces greatly improves the accuracy of the predictions, since more correlations are taken into account; the predicted potentials become smoother, are significantly closer to the target potentials, and are more transferable as a result.

The interplay of nematic order and phase separation in solutions of semiflexible polymers in solvents of variable quality is investigated by density functional theory (DFT) and molecular dynamics (MD) simulations. We studied coarse-grained models, with a bond-angle potential to control chain stiffness, for chain lengths comparable to the persistence length of the chains. We varied both the density of the monomeric units and the effective temperature that controls the quality of the implicit solvent. For very stiff chains only a single transition from an isotropic fluid to a nematic is found, with a phase diagram of "swan-neck" topology. For less stiff chains, however, also unmixing between isotropic fluids of different concentration, ending in a critical point, occurs for temperatures above a triple point. The associated critical behavior is examined in the MD simulations and found compatible with Ising universality. Apart from this critical behavior, DFT calculations agree qualitatively with the MD simulations.

In Part I of this two-part series, the reverse perturbation method for shearing simple liquids [Phys. Rev. E 59, 4894 (1999)] was extended to systems of interacting particles with time-discrete stochastic dynamics. For verification, in this paper (Part II) the reverse perturbation method is first applied to a simple momentum-conserving liquid, modeled through the Multi-Particle Collision Dynamics (MPCD) technique [J. Chem. Phys. 110, 8605 (1999)]. For MPCD, excellent agreement between the measured shear viscosity and its theoretical prediction is found. Furthermore, this paper contains applications of the reverse perturbation method to agent-based simulations of the Vicsek-model [Phys. Rev. Lett. 75, 1226 (1995)] and its metric-free version. The extracted transport coefficients, the kinematic viscosity $\nu$ and the momentum amplification coefficient $\lambda$, were compared to theoretical predictions. To verify the transport coefficients, Green-Kubo relations were evaluated and transverse current correlations were measured in independent simulations. Not too far to the transition to collective motion, we find excellent agreement between the different measurements of the transport coefficients. However, the measured values of $\nu$ and $1-\lambda$ are always slightly higher than the mean-field predictions, even at large mean free paths and at state points quite far from the threshold to collective motion, that is, far in the disordered phase. These findings seem to indicate that the mean-field assumption of molecular chaos is much less reliable in systems with velocity-alignment rules such as the Vicsek model, compared to models obeying detailed balance such as MPCD., Comment: This manuscript has been merged into arXiv:1905.04082

Multiparticle collision dynamics (MPCD) is a flexible and robust mesoscale computational technique for simulating solvent-mediated hydrodynamic interactions in soft materials. Here, we provide a critical overview of the MPCD method and summarize its current strengths and limitations. The capabilities of the method are highlighted by reviewing its recent applications to simulate diverse phenomena, ranging from the flow of complex fluids and thermo-osmotic transport to bacterial swimming and active particle self-assembly. We also discuss outstanding challenges and emerging methodological developments that are expected to greatly expand the applicability of MPCD to other systems of technological importance., Comment: 3 figures

Semiflexible polymers in concentrated lyotropic solution are studied within a bead-spring model by molecular dynamics simulations, focusing on the emergence of a smectic A phase and its properties. We systematically vary the density of the monomeric units for several contour lengths that are taken smaller than the chain persistence length. The difficulties concerning the equilibration of such systems and the choice of appropriate ensemble (constant volume versus constant pressure, where all three linear dimensions of the simulation box can fluctuate independently) are carefully discussed. Using HOOMD-blue on graphics processing units, systems containing more than a million monomeric units are accessible, making it possible to distinguish the order of the phase transitions that occur. While in this model the nematic-smectic transition is continuous, the transition from the smectic phase to a related crystalline structure with true three-dimensional long-range order is clearly of first order. Further, both orientational and positional correlations of monomeric units are studied as well as the order parameters characterizing the nematic, smectic A, and crystalline phases. The analogy between smectic order and one-dimensional harmonic crystals with respect to the behavior of the structure factor is also explored. Finally, the results are put in perspective with pertinent theoretical predictions and possible experiments.

The migration of a Brownian fluid droplet in a parallel-plate microchannel was investigated using dissipative particle dynamics computer simulations. In a Newtonian solvent, the droplet migrated toward the channel walls due to inertial effects at the studied flow conditions, in agreement with theoretical predictions and recent simulations. However, the droplet focused onto the channel centerline when polymer chains were added to the solvent. Focusing was typically enhanced for longer polymers and higher polymer concentrations with a nontrivial flow-rate dependence due to droplet and polymer deformability. Brownian motion caused the droplet position to fluctuate with a distribution that primarily depended on the balance between inertial lift forces pushing the droplet outward and elastic forces from the polymers driving it inward. The droplet shape was controlled by the local shear rate, and so its average shape depended on the droplet distribution., Comment: 10 pages, 9 figures

We present an efficient open-source implementation of the multiparticle collision dynamics (MPCD) algorithm that scales to run on hundreds of graphics processing units (GPUs). We especially focus on optimizations for modern GPU architectures and communication patterns between multiple GPUs. We show that a mixed-precision computing model can improve performance compared to a fully double-precision model while still providing good numerical accuracy. We report weak and strong scaling benchmarks of a reference MPCD solvent and a benchmark of a polymer solution with research-relevant interactions and system size. Our MPCD software enables simulations of mesoscale hydrodynamics at length and time scales that would be otherwise challenging or impossible to access.

We investigate the dynamics of nanoparticles in semidilute polymer solutions when the nanoparticles are comparably sized to the polymer coils using explicit- and implicit-solvent simulation methods. The nanoparticle dynamics are subdiffusive on short time scales before transitioning to diffusive motion on long time scales. The long-time diffusivities scale according to theoretical predictions based on full dynamic coupling to the polymer segmental relaxations. In agreement with our recent experiments, however, we observe that the nanoparticle subdiffusive exponents are significantly larger than predicted by the coupling theory over a broad range of polymer concentrations. We attribute this discrepancy in the subdiffusive regime to the presence of an additional coupling mechanism between the nanoparticle dynamics and the polymer center-of-mass motion, which differs from the polymer relaxations that control the long-time diffusion. This coupling is retained even in the absence of many-body hydrodynamic interactions when the long-time dynamics of the colloids and polymers are matched.

We systematically studied the validity and transferability of effective, coarse-grained, pair potentials in ultrasoft colloidal systems. We focused on amphiphilic dendrimers, macromolecules which can aggregate into clusters of overlapping particles to minimize the contact area with the surrounding (implicit) solvent. Simulations were performed for both the monomeric and coarse-grained model in the liquid phase at densities ranging from infinite dilution up to values close to the freezing point. For every state point, each macromolecule was mapped onto a single interaction site and the effective pair potential was computed using a coarse-graining technique based on force-matching. We found excellent agreement between the spatial dendrimer distributions obtained from the coarse-grained and microscopically detailed simulations at low densities, where the macromolecules were distributed homogeneously in the system. However, the agreement deteriorated significantly when the density was increased further and the cluster occupation became more polydisperse. Under these conditions, the effective pair potential of the coarse-grained model can no longer be computed by averaging over the whole system, but the local density needs to be taken into account instead.