Nanospheres in phase-separating multicomponent fluids: A three-dimensional dissipative particle dynamics simulation

Pattern dynamics of density and velocity fields in segregation of fluid mixtures

We present comprehensive numerical results from a study of model H, which describes phase separation kinetics in binary fluid mixtures. We study the pattern dynamics of both density and velocity fields in d = 2, 3. The density length scales show three distinct regimes, in accordance with analytical arguments. The velocity length scale shows a diffusive behavior. We also study the scaling behavior of the morphologies for density and velocity fields and observe dynamical scaling in the relevant correlation functions and structure factors. Finally, we study the effect of quenched random field disorder on spinodal decomposition in model H.

An Efficient Random Number Generation Method for Molecular Simulation

We propose a new random number generation method, which is the fastest and the simplest of its kind, for use with molecular simulation. We also discuss the possibility of using this method with various other numerical calculations. To demonstrate the significant increases in calculation speeds that can be gained by using our method, we present a comparison with prior methods for dissipative particle dynamics (DPD) simulations. The DPD method uses random numbers to reproduce thermal fluctuations of molecules. As such, an efficient method to generate random numbers in parallel computing environments has been widely sought after. Several random number generation methods have been developed that use encryption. In this study, we establish for the first time that random numbers with desirable properties exist in the particle coordinates used in DPD calculations. We propose a method for generating random numbers without encryption that utilizes this source of randomness. This is an innovative method with minimal computational cost, since it is not dependent on a complicated random number generation algorithm or an encryption process. Furthermore, our method may lead to faster random number generation for many other physical and chemical simulations.

Dissipative particle dynamics simulations in colloid and Interface science: a review

Dissipative particle dynamics (DPD) is one of the most efficient mesoscale coarse-grained methodologies for modeling soft matter systems. Here, we comprehensively review the progress in theoretical formulations, parametrization strategies, and applications of DPD over the last two decades. DPD bridges the gap between the microscopic atomistic and macroscopic continuum length and time scales. Numerous efforts have been performed to improve the computational efficiency and to develop advanced versions and modifications of the original DPD framework. The progress in the parametrization techniques that can reproduce the engineering properties of experimental systems attracted a lot of interest from the industrial community longing to use DPD to characterize, help design and optimize the practical products. While there are still areas for improvements, DPD has been efficiently applied to numerous colloidal and interfacial phenomena involving phase separations, self-assembly, and transport in polymeric, surfactant, nanoparticle, and biomolecules systems.

The rapid and controllable fabrication of large-scale and highly ordered micro-honeycomb arrays induced by nonsolvent phase separation

Structures that are highly ordered in nature show unique light propagation abilities. Among them, micro-honeycomb arrays are attractive owing to their advantages relating to the collection of light or enlarging the viewing angle and, also, owing to their potential applications in precision optics. Inspired by the natural phenomenon of droplet condensation on a cold surface, breath figure self-assembly has been a common approach used to fabricate such ordered micro-honeycomb arrays. However, the harsh preparation conditions and specific polymer architecture required have limited the widespread application of this approach. In this work, by using a commercial linear homopolymer and introducing its nonsolvent, we successfully fabricated uniform micro-honeycomb arrays on a large scale in just seconds and at ambient humidity. The morphology of the structures can be easily tuned via controlling the preparation conditions. Furthermore, high fill-factor convex micro-lenses were prepared based on the as-prepared concave micro-honeycomb arrays as templates through a simple replication process. They demonstrate properties such as clear multiple image presentation and light diffraction. They can also assist the strong scattering of light, which enhances the fluorescent intensity by more than 10%. This method is envisaged as a potential candidate to replace breath figure self-assembly for micro-honeycomb arrays in a low-cost and high-efficiency manner under mild conditions.

The influence of random number generation in dissipative particle dynamics simulations using a cryptographic hash function

The tiny encryption algorithm (TEA) is widely used when performing dissipative particle dynamics (DPD) calculations in parallel, usually on distributed memory systems. In this research, we reduced the computational cost of the TEA hash function and investigated the influence of the quality of the random numbers generated on the results of DPD calculations. It has already been established that the randomness, or quality, of the random numbers depend on the number of processes from internal functions such as SHIFT, XOR and ADD, which are commonly referred to as “rounds”. Surprisingly, if we choose seed numbers from high entropy sources, with a minimum number of rounds, the quality of the random numbers generated is sufficient to successfully perform accurate DPD simulations. Although it is well known that using a minimal number of rounds is insufficient for generating high-quality random numbers, the combination of selecting good seed numbers and the robustness of DPD simulations means that we can reduce the random number generation cost without reducing the accuracy of the simulation results.

Colloidal Spherocylinders at an Interface: Flipper Dynamics and Bilayer Formation

We study the response of a film of colloidal spherocylinders to compression by combining pressure-area isotherm measurements, microscopy, and computer simulations. We find that the behavior of the film depends strongly on the geometry of the particles. For a small aspect ratio, a uniform monolayer forms and then buckles. For a higher aspect ratio, particles flip to orient perpendicular to the interface; we show that flipping occurs in locations where the nematic ordering is low. Our experiments and simulations further demonstrate that the longest particles rearrange to self-assemble a colloidal bilayer, which is stable due to the unique geometry of spherocylinders at an interface.

Multiscale simulation of ideal mixtures using smoothed dissipative particle dynamics

Smoothed dissipative particle dynamics (SDPD) [P. Español and M. Revenga, Phys. Rev. E 67, 026705 (2003)] is a thermodynamically consistent particle-based continuum hydrodynamics solver that features scale-dependent thermal fluctuations. We obtain a new formulation of this stochastic method for ideal two-component mixtures through a discretization of the advection-diffusion equation with thermal noise in the concentration field. The resulting multicomponent approach is consistent with the interpretation of the SDPD particles as moving volumes of fluid and reproduces the correct fluctuations and diffusion dynamics. Subsequently, we provide a general multiscale multicomponent SDPD framework for simulations of molecularly miscible systems spanning length scales from nanometers to the non-fluctuating continuum limit. This approach reproduces appropriate equilibrium properties and is validated with simulation of simple one-dimensional diffusion across multiple length scales.

Dissipative particle dynamics simulations of the viscosities of molten TNT and molten TNT suspensions containing nanoparticles

Based on dissipative particle dynamics (DPD) methods and experimental data, we used an empirical relationship between the DPD temperature and the real temperature to build a model that describes the viscosity of molten TNT fluids. The errors in the predicted viscosity based on this model were no more than 2.3 %. We also studied the steady-state shear rheological behavior of molten TNT fluids containing nanoparticles ("nanofluids"). The dependence of the nanofluid viscosity on the temperature was found to satisfy an Arrhenius-type equation, η = Ae (B/T) , where B, the flow activation energy, depends on particle content, size, and shape. We modified the Einstein-type viscosity model to account for the effects of nanoparticle solvation in TNT nanofluids. The resulting model was able to correctly predict the viscosities of suspensions containing nano- to microsized particles, and did not require any changes to the physical background of Einstein's viscosity theory. Graphical Abstract The revised Einstein viscosity model that correctly predict the viscosity of TNT suspensions containing nanoparticles.

Numerical Simulations of the Digital Microfluidic Manipulation of Single Microparticles

Single-cell analysis techniques have been developed as a valuable bioanalytical tool for elucidating cellular heterogeneity at genomic, proteomic, and cellular levels. Cell manipulation is an indispensable process for single-cell analysis. Digital microfluidics (DMF) is an important platform for conducting cell manipulation and single-cell analysis in a high-throughput fashion. However, the manipulation of single cells in DMF has not been quantitatively studied so far. In this article, we investigate the interaction of a single microparticle with a liquid droplet on a flat substrate using numerical simulations. The droplet is driven by capillary force generated from the wettability gradient of the substrate. Considering the Brownian motion of microparticles, we utilize many-body dissipative particle dynamics (MDPD), an off-lattice mesoscopic simulation technique, in this numerical study. The manipulation processes (including pickup, transport, and drop-off) of a single microparticle with a liquid droplet are simulated. Parametric studies are conducted to investigate the effects on the manipulation processes from the droplet size, wettability gradient, wetting properties of the microparticle, and particle-substrate friction coefficients. The numerical results show that the pickup, transport, and drop-off processes can be precisely controlled by these parameters. On the basis of the numerical results, a trap-free delivery of a hydrophobic microparticle to a destination on the substrate is demonstrated in the numerical simulations. The numerical results not only provide a fundamental understanding of interactions among the microparticle, the droplet, and the substrate but also demonstrate a new technique for the trap-free immobilization of single hydrophobic microparticles in the DMF design. Finally, our numerical method also provides a powerful design and optimization tool for the manipulation of microparticles in DMF systems.

Hydrodynamics in bridging and aggregation of two colloidal particles in a near-critical binary mixture

We investigate bridging and aggregation of two colloidal particles in a near-critical binary mixture when the fluid far from the particles is outside the coexistence (CX) curve and is rich in the component disfavored by the colloid surfaces. In such situations, the adsorption-induced interaction is enhanced, leading to bridging and aggregation of the particles. We realize bridging firstly by changing the temperature with a fixed interparticle separation and secondly by letting the two particles aggregate. The interparticle attractive force dramatically increases upon bridging. The dynamics is governed by hydrodynamic flow around the colloid surfaces. In aggregation, the adsorption layers move with the particles and squeezing occurs at narrow separation. These results suggest relevance of bridging in the reversible colloid aggregation observed so far. We use the local functional theory [J. Chem. Phys., 2012, 136, 114704] to take into account the renormalization effect and the simulation method [Phys. Rev. Lett., 2000, 85, 1338] to calculate the hydrodynamic flow around the colloidal particles.

Combined effect of cortical cytoskeleton and transmembrane proteins on domain formation in biomembranes

We investigate the combined effects of transmembrane proteins and the subjacent cytoskeleton on the dynamics of phase separation in multicomponent lipid bilayers using computer simulations of a particle-based implicit solvent model for lipid membranes with soft-core interactions. We find that microphase separation can be achieved by the protein confinement by the cytoskeleton. Our results have relevance to the finite size of lipid rafts in the plasma membrane of mammalian cells.

Dual effects of mesoscopic fillers on the polyethersulfone modified cyanate ester: enhanced viscoelastic effect and mechanical properties

Enlarging the filler content and decreasing the filler size contribute to enhancing both viscoelastic effect and mechanical property of polyethersulfone modified cyanate system.

Bottom-up construction of interaction models of non-Markovian dissipative particle dynamics

We derive the equation of motion for non-Markovian dissipative particle dynamics (NMDPD) by introducing the history effects on the time evolution of the system. Our formulation is based on the generalized Langevin equation, which describes the motions of the centers of mass of clusters comprising microscopic particles. The mean, friction, and fluctuating forces in the NMDPD model are directly constructed from an underlying molecular dynamics (MD) system without any scaling procedure. For the validation of our formulation, we construct NMDPD models from high-density Lennard-Jones systems, in which the typical time scales of the coarse-grained particle motions and the fluctuating forces are not fully separable. The NMDPD models reproduce the temperatures, diffusion coefficients, and viscosities of the corresponding MD systems more accurately than the dissipative particle dynamics models based on a Markovian approximation. Our results suggest that the NMDPD method is a promising alternative for simulating mesoscale flows where a Markovian approximation is not valid.

VISUALIZING SOFT MATTER: MESOSCOPIC SIMULATIONS OF MEMBRANES, VESICLES AND NANOPARTICLES

Biological membranes have properties and behavior that emerge from the propagation of the molecular characteristics of their components across many scales. Artificial smart materials, such as drug delivery vehicles and nanoparticles, often rely on modifying naturally-occurring soft matter, such as polymers and lipid vesicles, so that they possess useful behavior. Mesoscopic simulations allow in silico experiments to be easily and cheaply performed on complex, soft materials requiring as input only the molecular structure of the constituents at a coarse-grained level. They can therefore act as a guide to experimenters prior to performing costly assays. Additionally, mesoscopic simulations provide the only currently feasible window on the length and time scales relevant to important biophysical processes such as vesicle fusion. We describe here recent work using Dissipative Particle Dynamics simulations to explore the structure and behavior of amphiphilic membranes, the fusion of vesicles, and the interactions between rigid nanoparticles and soft surfaces.

Aggregation of nanoparticles in a block copolymer bilayer

In this paper, we examine, by dissipative particle dynamics (DPD) simulation, the interactions between nanoparticles and block copolymer bilayer membranes. The bilayer has a hydrophobic core and hydrophilic head groups on both sides of the core. Nanoparticles without or with a grafted homopolymer are considered. For the conditions investigated, the single nanoparticles and small aggregates are located at the interfaces of the membrane, namely the interfaces between the hydrophilic domains of the membrane and the solvent as well as at the interface between the hydrophobic and hydrophilic domains of the membrane. The large aggregates are located in the hydrophilic domains. By increasing the length of the homopolymer grafted on the nanoparticles, the size of the aggregates in the membrane decreases. At relatively short DPD step times, the particles aggregate in the solvent. As the time increases, the single particles and aggregates penetrate into the membrane.

A comparison of implicit- and explicit-solvent simulations of self-assembly in block copolymer and solute systems

We have developed explicit- and implicit-solvent models for the flash nanoprecipitation process, which involves rapid coprecipitation of block copolymers and solutes by changing solvent quality. The explicit-solvent model uses the dissipative particle dynamics (DPD) method and the implicit-solvent model uses the Brownian dynamics (BD) method. Each of the two models was parameterized to match key properties of the diblock copolymer (specifically, critical micelle concentration, diffusion coefficient, polystyrene melt density, and polyethylene glycol radius of gyration) and the hydrophobic solute (aqueous solubility, diffusion coefficient, and solid density). The models were simulated in the limit of instantaneous mixing of solvent with antisolvent. Despite the significant differences in the potentials employed in the implicit- and explicit-solvent models, the polymer-stabilized nanoparticles formed in both sets of simulations are similar in size and structure; however, the dynamic evolution of the two simulations is quite different. Nanoparticles in the BD simulations have diffusion coefficients that follow Rouse behavior (D ∝ M(-1)), whereas those in the DPD simulations have diffusion coefficients that are close to the values predicted by the Stokes-Einstein relation (D ∝ R(-1)). As the nanoparticles become larger, the discrepancy between diffusion coefficients grows. As a consequence, BD simulations produce increasingly slower aggregation dynamics with respect to real time and result in an unphysical evolution of the nanoparticle size distribution. Surface area per polymer of the stable explicit-solvent nanoparticles agrees well with experimental values, whereas the implicit-solvent nanoparticles are stable when the surface area per particle is roughly two to four times larger. We conclude that implicit-solvent models may produce questionable results when simulating nonequilibrium processes in which hydrodynamics play a critical role.

Fluid-bicontinuous gels stabilized by interfacial colloids: low and high molecular weight fluids

Carefully tuned composite materials can have properties wholly unlike those of their separate constituents. We review the development of one example: colloid-stabilized emulsions with bicontinuous liquid domains. These non-equilibrium structures resemble the sponge mesophase of surfactants; however, in the colloid-stabilized case the interface separating the liquid domains is itself semi-solid. The arrangement of domains is created by arresting liquid-liquid phase separation via spinodal decomposition. Dispersed colloids exhibiting partial wettability become trapped on the newly created interface and jam together as the domains coarsen. Similar structures have been created in polymer blends stabilized using either interfacial nanoparticles or clay platelets. Here it has been possible to create the domain arrangement either by phase separation or by direct mixing of the melt. The low molecular weight liquid and polymer based structures have been developed independently and much can be learnt by comparing the two.

Microphase separation induced by interfacial segregation of isotropic, spherical nanoparticles

In a recent experiment by Chung et al. [Nano Lett. 5, 1878 (2005)] and simulation by Stratford et al. [Science 309, 2198 (2005)] on immiscible blends containing nanoscale particles, it was shown that the phase separation of the two polymers can be prevented as a result of the aggregation of the nanoparticles at the interfaces between the two polymers. Motivated by these studies, we performed large scale systematic simulations, based on the dissipative particle dynamics approach, on immiscible binary (A-B) fluids containing moderate volume fractions of isotropic nanoscale spherical particles N. The nanoparticles preferentially segregate at the interfaces between the two fluids if the pairwise interactions between the three components are such that chi(AB)>/chi(AN)-chi(BN)/. We find that at later times, the average domain size saturates to a value, L approximately R(N)/phi(N), where R(N) and phi(N) are the radius and volume fraction of the nanoparticles, respectively. For small nanoparticles, however, full phase separation is observed.

Control of Aggregation of Nanoparticles by Double-Hydrophilic Block Copolymers: A Dissipative Particle Dynamics Study

Double-hydrophilic block copolymer (DHBC)-directed mineralization is investigated by dissipative particle dynamics (DPD) simulation. By mineralization, we refer to the formation of inorganic crystals from the solution. In the current study, the DHBCs are modeled as chains of A and B blocks with repulsion between unlike blocks, while the mineralization is approximated by aggregation of hydrophobic nanoparticles from the solution. Depending on the relative concentrations of nanoparticles and DHBC, dispersed spherical aggregates, hexagonally packed cylinders, and ordered lamellae structures are obtained. The structures formed are seen to be controlled by competing forces between aggregation of nanoparticles, the interaction of DHBC with nanoparticles, and the self-assembly of DHBC in the solution. The time evolutions of hexagonally packed cylinders and ordered lamellae are studied. For the development of cylinders, nanoparticles first aggregate into orientationally disordered small cylinders, then these cylinders slowly grow into hexagonally packed long cylinders. For the development of ordered lamellae, nanoparticles first form a disordered structure, then grow into disordered lamellae, and at last evolve into ordered lamellae. The simulation demonstrates that addition of DHBC can effectively control the aggregation of inorganic particles and lead to formation of a variety of nanostructures.

Hydrodynamic interaction in polymer solutions simulated with dissipative particle dynamics

The authors analyzed extensively the dynamics of polymer chains in solutions simulated with dissipative particle dynamics (DPD), with a special focus on the potential influence of a low Schmidt number of a typical DPD fluid on the simulated polymer dynamics. It has been argued that a low Schmidt number in a DPD fluid can lead to underdevelopment of the hydrodynamic interaction in polymer solutions. The authors' analyses reveal that equilibrium polymer dynamics in dilute solution, under typical DPD simulation conditions, obey the Zimm [J. Chem. Phys. 24, 269 (1956)] model very well. With a further reduction in the Schmidt number, a deviation from the Zimm model to the Rouse model is observed. This implies that the hydrodynamic interaction between monomers is reasonably developed under typical conditions of a DPD simulation. Only when the Schmidt number is further reduced, the hydrodynamic interaction within the chains becomes underdeveloped. The screening of the hydrodynamic interaction and the excluded volume interaction as the polymer volume fraction is increased are well reproduced by the DPD simulations. The use of soft interaction between polymer beads and a low Schmidt number do not produce noticeable problems for the simulated dynamics at high concentrations, except for the entanglement effect which is not captured in the simulations.

Wetting-induced depletion interaction between particles in a phase-separating liquid mixture

Inclusion of solid particles drastically affects the pattern evolution of phase separation of a binary fluid mixture, via preferential wetting of one of the phases to the particles. Here we study this problem by numerical simulation, which incorporates interparticle hydrodynamic interactions properly. When particles favor one of the components of a mixture, wetting layers are quickly formed on the particle surfaces and all particles are eventually included into the more wettable phase. For immobile particles, domains of the more wettable phase are pinned to the particles and the domain growth is thus suppressed. For this case, the domain size at a certain phase-separation time decreases monotonically with increasing the particle concentration. For mobile particles, on the other hand, the reentrant morphological transformation is observed as a function of the particle concentration: With an increase in the particle concentration, the domain morphology of the more wettable phase sequentially changes from network, droplet to network. We found that the final morphological transition is induced by wetting-induced depletion interaction: strong attractive interactions act among particles when the total volume of the more wettable phase is not enough to cover all the particles by wetting layers.