An enhanced entangled polymer model for dissipative particle dynamics

Evolution Kinetics of Stabilizing Pickering Emulsion by Brush-Modified Janus Particles: DPD Simulation and Experimental Insights

In the present study, we report the evolution of stabilizing Pickering emulsions using brush-modified Janus particles (JPs), utilizing the dissipative particle dynamics (DPD) simulation technique. Our results are subsequently corroborated with experimental findings. Each JP has one-half of the hydrophobic surface, with the other half embedded with hydrophilic polymer brushes grown via atom transfer radical polymerization (ATRP). Our generic simulation model analyzes the chemical kinetics of polymer brush growth on one-half of the initiator-embedded microparticle (MP) surface, resulting in the formation of JP. This involves evaluating monomer conversion and reaction rates. Our results exhibit a substantial influence of the number of JPs, grafted brush density, and brush length on oil-in-water emulsion stability. We studied the evolution kinetics and stability of emulsion formation by analyzing the growth of average domain size and corresponding scaling functions up to a late time limit. This study aims to clarify the connection between the size, quantity, and functionality of JPs and the stability of Pickering emulsions.

Resolving the dynamic properties of entangled linear polymers in non-equilibrium coarse grain simulation with a priori scaling factors

The molecular weight of polymers can influence the material properties, but the molecular weight at the experiment level sometimes can be a huge burden for property prediction with full-atomic simulations. The traditional bottom-up coarse grain (CG) simulation can reduce the computation cost. However, the dynamic properties predicted by the CG simulation can deviate from the full-atomic simulation result. Usually, in CG simulations, the diffusion is faster and the viscosity and modulus are much lower. The fast dynamics in CG are usually solved by a posteriori scaling on time, temperature, or potential modifications, which usually have poor transferability to other non-fitted physical properties because of a lack of fundamental physics. In this work, a priori scaling factors were calculated by the loss of degrees of freedom and implemented in the iterative Boltzmann inversion. According to the simulation results on 3 different CG levels at different temperatures and loading rates, such a priori scaling factors can help in reproducing some dynamic properties of polycaprolactone in CG simulation more accurately, such as heat capacity, Young's modulus, and viscosity, while maintaining the accuracy in the structural distribution prediction. The transferability of entropy-enthalpy compensation and a dissipative particle dynamics thermostat is also presented for comparison. The proposed method reveals the huge potential for developing customized CG thermostats and offers a simple way to rebuild multiphysics CG models for polymers with good transferability.

How fork-length asymmetry affects solvent connectivity and diffusion in grafted polymeric model membranes

The hydrophilic pore morphology and solvent diffusion within model (amphiphilic) polymer membranes are simulated by dissipative particle dynamics (DPD). The polymers are composed of a backbone of 18 covalently bonded A beads to which at regular intervals side chains are attached. The side chains are composed of linear Ap chains (i.e., -A1-A2…Ap) from which two branches, [AsC] and [ArC], split off (s ≤ r). C beads serve as functionalized hydrophilic pendent sites. The branch lengths (s + 1 and r + 1) are varied. Five repeat unit designs (with general formula A3[Ap[AsC][ArC]]) are considered: A2[A3C][A3C] (symmetric branching), A2[A2C][A4C], A2[AC][A5C], A2[C][A6C] (highly asymmetric branching), and A4[AC][A3C]. The distribution of water (W) and W diffusion through nanophase segregated hydrophilic pores is studied. For similar primary length p, an increase in side chain symmetry favors hydrophilic pore connectivity and long-range water transport. C beads located on the longer [ArC] branches reveal the highest C bead mobility and are more strongly associated with water than the C beads on the shorter [AsC] branches. The connectivity of hydrophilic (W and W + C) phases through mapped replica of selected snapshots obtained from Monte Carlo tracer diffusion simulations is in line with trends found from the W bead diffusivities during DPD simulations. The diffusive pathways for protons (H+) in proton exchange membranes and for hydronium (OH-) in anion exchange membranes are the same as for solvents. Therefore, control of the side chain architecture is an interesting design parameter for optimizing membrane conductivities.

Growth kinetics and morphology characterization of binary polymeric fluid under random photo-illumination

We present a comprehensive study using dissipative particle dynamics simulations to investigate phase separation kinetics (PSK) in three-dimensional (3d) polymeric fluids under random photo-illumination. We consider two scenarios: polymer blends with active radicals at one end of each immiscible chain and block copolymer (BCP) melts with photosensitive bonds linking incompatible blocks. The phase separation (PS) is induced by temperature quench of the initial homogeneously mixed system. Simultaneously, the system experiences random photo-illumination, simulated by two concurrent random events: (a) the recombination of active radicals in polymer blends and (b) the breaking of photosensitive bonds in BCP chains. Variations in the bond-breaking probability, Pb, mimic the change in light intensity. The length scale follows power law growth, R(t) ∼ tϕ, where ϕ represents the growth exponent. Increasing Pb results in a gradual transition in growth kinetics from micro-PS to macro-PS, accompanied by corresponding transition probabilities for both systems. Micro-PSK dominates the evolution process at low Pb values. The scaling functions exhibit data overlap for most scaled distances, indicating the statistical self-similarity of evolving patterns. Our study enhances the understanding of PSK in polymeric fluids, revealing the impact of photosensitive bonds and active radicals. Furthermore, it suggests the potential for designing novel polymeric materials with desired properties.

Effect of amphiphilic polymers on phase separating binary mixtures: A DPD simulation study

We present the phase separation dynamics of a binary (AB), simple fluid (SF), and amphiphilic polymer (AP) mixture using dissipative particle dynamics simulation at d = 3. We study the effect of different AP topologies, including block copolymers, ring block copolymers (RCP), and miktoarm star polymers, on the evolution morphologies, dynamic scaling functions, and length scale of the AB mixture. Our results demonstrate that the presence of APs leads to significantly different evolution morphologies in SF. However, the deviation from dynamical scaling is prominent, mainly for RCP. Typically, the characteristic length scale for SF follows the power law R(t) ∼ tϕ, where ϕ is the growth exponent. In the presence of high AP, we observe diffusive growth (ϕ → 1/3) at early times, followed by saturation in length scale (ϕ → 0) at late times. The extent of saturation varies with constraints imposed on the APs, such as topology, composition ratio, chain length, and stiffness. At lower composition ratios, the system exhibits inertial hydrodynamic growth (ϕ → 2/3) at asymptotic times without clearly exhibiting the viscous hydrodynamic regime (ϕ → 1) at earlier times in our simulations. Our results firmly establish the existence of hydrodynamic growth regimes in low surfactant-influenced phase separation kinetics of binary fluids and settle the related ambiguity in d = 3 systems.

Segregation of fluids with polymer additives at domain interfaces: a dissipative particle dynamics study

This paper investigates the phase separation kinetics of ternary fluid mixtures composed of a polymeric component (C) and two simple fluids (A and B) using dissipative particle dynamics simulations with a system dimensionality of d = 3. We model the affinities between the components to enable the settling of the polymeric component at the interface of fluids A and B. Thus, the system evolves to form polymer coated morphologies, enabling alteration of the fluids' interfacial properties. This manipulation can be utilized across various disciplines, such as the stabilization of emulsions and foams, rheological control, biomimetic design, and surface modification. We probe the effects of various parameters, such as the polymeric concentration, chain stiffness, and length, on the phase separation kinetics of the system. The simulation results show that changes in the concentration of flexible polymers exhibit perfect dynamic scaling for coated morphologies. The growth rate decreases as the polymeric composition is increased due to reduced surface tension and restricted connectivity between A- and B-rich clusters. Variations in the polymer chain rigidity at fixed composition ratios and degrees of polymerization slow the evolution kinetics of AB fluids marginally, although the effect is more pronounced for perfectly rigid chains. Whereas flexible polymer chain lengths at fixed composition ratios slow down the segregation kinetics of AB fluids slightly, varying the chain lengths of perfectly rigid polymers leads to a significant deviation in the length scale and dynamic scaling for the evolved coated morphologies. The characteristic length scale follows a power-law growth with a growth exponent ϕ that shows a crossover from the viscous to the inertial hydrodynamic regime, where the values of ϕ depend on the constraints imposed on the system.

Microstructural Dynamics of Polymer Melts during Stretching: Radial Size Distribution

The transient elongational viscosity ηe(t) of the polymer melt is known to exhibit strain hardening, which depends on the strain rate ε˙. This phenomenon was elucidated by the difference of chain stretching in the entanglement network between extension and shear. However, to date, the microscopic evolution of polymer melt has not been fully statistically analyzed. In this work, the radial size distributions P(Rg,t) of linear polymers are explored by dissipative particle dynamics during the stretching processes. In uniaxial extensional flow, it is observed that the mean radius of gyration R¯g(t) and standard deviation σ(t) remain unchanged until the onset of strain hardening, corresponding to linear viscoelasticity. Both R¯g and σ rise rapidly in the non-linear regime, and bimodal size distribution can emerge. Moreover, the onset of strain hardening is found to be insensitive to the Hencky strain (ε˙Ht) and chain length (N).

Mesoscale Modeling of Phase Separation Controlled by Hydrosilylation in Polyhydromethylsiloxane (PHMS)-Containing Blends

Controlling morphology of polysiloxane blends crosslinked by the hydrosilylation reaction followed by pyrolysis constitutes a robust strategy to fabricate polymer-derived ceramics (PDCs) for a number of applications, from water purification to hydrogen storage. Herein, we introduce a dissipative particle dynamics (DPD) approach that captures the phase separation in binary and ternary polymer blends undergoing hydrosilylation. Linear polyhydromethylsiloxane (PHMS) chains are chosen as preceramic precursors and linear vinyl-terminated polydimethylsiloxane (v-PDMS) chains constitute the reactive sacrificial component. Hydrosilylation of carbon-carbon unsaturated double bonds results in the formation of carbon-silicon bonds and is widely utilized in the synthesis of organosilicons. We characterize the dynamics of binary PHMS/v-PDMS blends undergoing hydrosilylation and ternary blends in which a fraction of the reactive sacrificial component (v-PDMS) is replaced with the non-reactive sacrificial component (methyl-terminated PDMS (m-PDMS), polyacrylonitrile (PAN), or poly(methyl methacrylate) (PMMA)). Our results clearly demonstrate that the morphology of the sacrificial domains in the nanostructured polymer network formed can be tailored by tunning the composition, chemical nature, and the degree of polymerization of the sacrificial component. We also show that the addition of a non-reactive sacrificial component introduces facile means to control the self-assembly and morphology of these nanostructured materials by varying the fraction, degree of polymerization, or the chemical nature of this component.

Mesoscale Modeling of Agglomeration of Molecular Bottlebrushes: Focus on Conformations and Clustering Criteria

Using dissipative particle dynamics, we characterize dynamics of aggregation of molecular bottlebrushes in solvents of various qualities by tracking the number of clusters, the size of the largest cluster, and an average aggregation number. We focus on a low volume fraction of bottlebrushes in a range of solvents and probe three different cutoff criteria to identify bottlebrushes belonging to the same cluster. We demonstrate that the cutoff criteria which depend on both the coordination number and the length of the side chain allows one to correlate the agglomeration status with the structural characteristics of bottlebrushes in solvents of various qualities. We characterize conformational changes of the bottlebrush within the agglomerates with respect to those of an isolated bottlebrush in the same solvents. The characterization of bottlebrush conformations within the agglomerates is an important step in understanding the relationship between the bottlebrush architecture and material properties. An analysis of three distinct cutoff criteria to identify bottlebrushes belonging to the same cluster introduces a framework to identify both short-lived transient and long-lived agglomerates; the same approach could be further extended to characterize agglomerates of various macromolecules with complex architectures beyond the specific bottlebrush architecture considered herein.

Slip-Spring Hybrid Particle-Field Molecular Dynamics for Coarse-Graining Branched Polymer Melts: Polystyrene Melts as an Example

The topology of chains significantly modifies the dynamical properties of polymer melts. Here, we extend a recently developed efficient simulation method, namely the slip-spring hybrid particle-field (SS-hPF) model, to study the structural and dynamical properties of branched polymer melts over large spatial-temporal scales. In the coarse-grained SS-hPF simulation of polymers, the bonded potentials are derived by iterative Boltzmann inversion from the underlying fine-grained model. The nonbonded potentials are computed from a density functional field instead of pairwise interactions used in standard molecular dynamics simulations, which increases the computational efficiency by a factor of 10-20. The entangled dynamics is lost due to the soft-core nature of density functional field interactions. It is recovered by a multichain slip-spring model that is rigorously parametrized from existing experimental or simulation data. To quantitatively predict the relaxation and diffusion of branched polymers, which are dominated by arm retraction rather than chain reptation, the slip-spring algorithm is augmented to improve the polymer dynamics near the branch point. Multiple dynamical observables, e.g., diffusion coefficients, arm relaxations, and tube survival probabilities, are characterized in an example coarse-grained model of symmetric and asymmetric star-shaped polystyrene melts. Consistent dynamical behaviors are identified and compared with theoretical predictions. With a single rescaling factor, the prediction of diffusion coefficients agrees well with the available experimental measurements. In this work, an efficient approach is provided to build chemistry-specific coarse-grained models for predicting the dynamics of branched polymers.

Coarse-Grained Modeling of Ion-Containing Polymers

Ion-containing polymers have continued to be an important research focus for several decades due to their use as an electrolyte in energy storage and conversion devices. Elucidation of connections between the mesoscopic structure and multiscale dynamics of the ions and solvent remains incompletely understood. Coarse-grained modeling provides an efficient approach for exploring the structural and dynamical properties of these soft materials. The unique physicochemical properties of such polymers are of broad interest. In this review, we summarize the current development and understanding of the structure-property relationship of ion-containing polymers and provide insights into the design of such materials determined from coarse-grained modeling and simulations accompanying significant advances in experimental strategies. We specifically concentrate on three types of ion-containing polymers: proton exchange membranes (PEMs), anion exchange membranes (AEMs), and polymerized ionic liquids (polyILs). We posit that insight into the similarities and differences in these materials will lead to guidance in the rational design of high-performance novel materials with improved properties for various power source technologies.

Adsorption of amphiphilic grafted polymers as polymer corrosion inhibitors: insights from mesoscopic simulations

The homogeneous covering of amphiphillic polymer molecules onto metallic surfaces is of great importance for corrosion inhibitor applications. Lyophillic side chains grafted onto a lyophobic backbone act as anchors that allow the molecule to absorb at the metallic surface preventing the exposure with the solvent. Coarse-grained simulations are used to study the sorption and conformation behaviour of amphiphillic grafted polymers for corrosion inhibition. The backbone insolubility is found to play a key role in the sorption and conformation behaviour in the dilute limit. For finite concentrations, moderate backbone solubility and moderate molecule concentrations achieve optimal surface coverage, while highly a lyophobic backbone leads to bulk-like structures as a consequence of aggregation.

Interfacial Assembly of Anisotropic Core-Shell and Hollow Microgels

Microgels, cross-linked polymers with submicrometer size, are ideal soft model systems. While spherical microgels have been studied extensively, anisotropic microgels have hardly been investigated. In this study, we compare the interfacial deformation and assembly of anisotropic core-shell and hollow microgels. The core-shell microgel consists of an elliptical core of hematite covered with a thin silica layer and a thin shell made of poly(N-isopropylacrylamide). The hollow microgels were obtained after a two-step etching procedure of the inorganic core. The behavior of these microgels at the oil-water interface was investigated in a Langmuir-Blodgett trough combined with ex situ atomic force microscopy. First, the influence of the architecture of anisotropic microgels on their spreading at the interface was investigated experimentally and by dissipative particle dynamic simulations. Hereby, the importance of the local shell thickness on the lateral and longitudinal interfacial deformation was highlighted as well as the differences between the core-shell and hollow architectures. The shape of the compression isotherms as well as the dimensions, ordering, and orientation of the microgels at the different compressions were analyzed. Due to their anisotropic shape and stiffness, both anisotropic microgels were found to exhibit significant capillary interactions with a preferential side-to-side assembly leading to stable microgel clusters at low interfacial coverage. Such capillary interactions were found to decrease in the case of the more deformable hollow anisotropic microgels. Consequently, anisotropic hollow microgels were found to distribute more evenly at high surface pressure compared to stiffer core-shell microgels. Our findings emphasize the complex interplay between the colloid design, anisotropy, and softness on the interfacial assembly and the opportunities it therefore offers to create more complex ordered interfaces.

Resolving the missing link between single platelet force and clot contractile force

Blood clot contraction plays an important role in wound healing and hemostasis. Although clot contraction is known to be driven by platelets, how single platelet forces relate to the forces generated by macroscopic clots remains largely unknown. Using our microfabricated high-throughput platelet contraction cytometer, we find that single platelets have an average force of 34 nN ( n = 10 healthy individuals). However, multiple bulk clot experiments predict a mean single platelet force lower than 0.5 nN. To resolve this discrepancy, we use a mesoscale computational model to probe the mechanism by which individual platelets induce forces in macroscopic clots. Our experimentally informed model shows that the number of platelets in the clot cross-section defines the net clot force. We provide a relationship between single platelet force and the clot force that is useful for better understanding of blood disorders associated with bleeding and thrombosis, and facilitates the development of platelet-based and platelet-mimetic biomaterials.

DPD Modelling of the Self- and Co-Assembly of Polymers and Polyelectrolytes in Aqueous Media: Impact on Polymer Science

This review article is addressed to a broad community of polymer scientists. We outline and analyse the fundamentals of the dissipative particle dynamics (DPD) simulation method from the point of view of polymer physics and review the articles on polymer systems published in approximately the last two decades, focusing on their impact on macromolecular science. Special attention is devoted to polymer and polyelectrolyte self- and co-assembly and self-organisation and to the problems connected with the implementation of explicit electrostatics in DPD numerical machinery. Critical analysis of the results of a number of successful DPD studies of complex polymer systems published recently documents the importance and suitability of this coarse-grained method for studying polymer systems.

Controlling Degradation and Erosion of Polymer Networks: Insights from Mesoscale Modeling

Understanding and controlling degradation of polymer networks on the mesoscale is critical for a range of applications. We utilize dissipative particle dynamics to capture photocontrolled degradation and erosion processes in hydrogels formed by end-linking of four-arm polyethylene glycol precursors. We demonstrate that the polydispersity and the fraction of broken-off fragments scale with the relative extent of reaction. The reverse gel point measured is close to the value predicted by the bond percolation theory on a diamond lattice. We characterize the erosion process via tracking the mass loss that accounts for the fragments remaining in contact with the percolated network. We quantify the dependence of the mass loss on the extent of reaction and on the properties of the film prior to degradation. These results elucidate the main features of degradation and erosion on the mesoscale and could provide guidelines for future design of degrading materials with dynamically controlled properties.

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.

Nonequilibrium Processes in Polymer Membrane Formation: Theory and Experiment

Porous polymer and copolymer membranes are useful for ultrafiltration of functional macromolecules, colloids, and water purification. In particular, block copolymer membranes offer a bottom-up approach to form isoporous membranes. To optimize permeability, selectivity, longevity, and cost, and to rationally design fabrication processes, direct insights into the spatiotemporal structure evolution are necessary. Because of a multitude of nonequilibrium processes in polymer membrane formation, theoretical predictions via continuum models and particle simulations remain a challenge. We compiled experimental observations and theoretical approaches for homo- and block copolymer membranes prepared by nonsolvent-induced phase separation and highlight the interplay of multiple nonequilibrium processes─evaporation, solvent-nonsolvent exchange, diffusion, hydrodynamic flow, viscoelasticity, macro- and microphase separation, and dynamic arrest─that dictates the complex structure of the membrane on different scales.

Structural properties of cationic surfactant-fatty alcohol bilayers: insights from dissipative particle dynamics

Bilayers, self-assembled by cationic surfactants and fatty alcohols in water, are the basic units of lamellar gel networks - creamy formulations extensively used in cosmetics and pharmaceutics. Mesoscopic modelling and study of the bilayers formed by single- or double-tail cationic surfactants (CTAC or DHDAC), and fatty alcohols (FAs) in the lamellar fluid and gel phases were employed. Fatty alcohols with alkyl tail equal to or greater than the surfactant alkyl tail, i.e., C₁₆FA or C₁₈FA and C₂₂FA, were considered. A model formulation was explored with the FA concentration greater than that of the surfactant and the structure of the fluid and gel bilayers in tensionless state characterised via the density profiles across the bilayers, orientational order parameters of the surfactant and FA chains, intrinsic analysis of the bilayer interfaces, and bending rigidity. The intrinsic analysis allows identification and quantification of the coexistence of the interdigitated and non-interdigitated phases present within the gel bilayers. The FA chains were found to conform the primary scaffolding of the bilayers while the surfactant chains tessellate bilayer monolayers from their water-hydrophobic interface. Further, the overlap of the FA chains from the apposed monolayers of the fluid bilayers rises with increasing FA length. Finally, the prevalence of the non-interdigitated phase over the interdigitated phase within the gel bilayers becomes enhanced upon the FA length increase with a preference of the surfactant chains to reside in the non-interdigitated phase rather than the interdigitated phase.

Discrete mechanical model of lamellipodial actin network implements molecular clutch mechanism and generates arcs and microspikes

Mechanical forces, actin filament turnover, and adhesion to the extracellular environment regulate lamellipodial protrusions. Computational and mathematical models at the continuum level have been used to investigate the molecular clutch mechanism, calculating the stress profile through the lamellipodium and around focal adhesions. However, the forces and deformations of individual actin filaments have not been considered while interactions between actin networks and actin bundles is not easily accounted with such methods. We develop a filament-level model of a lamellipodial actin network undergoing retrograde flow using 3D Brownian dynamics. Retrograde flow is promoted in simulations by pushing forces from the leading edge (due to actin polymerization), pulling forces (due to molecular motors), and opposed by viscous drag in cytoplasm and focal adhesions. Simulated networks have densities similar to measurements in prior electron micrographs. Connectivity between individual actin segments is maintained by permanent and dynamic crosslinkers. Remodeling of the network occurs via the addition of single actin filaments near the leading edge and via filament bond severing. We investigated how several parameters affect the stress distribution, network deformation and retrograde flow speed. The model captures the decrease in retrograde flow upon increase of focal adhesion strength. The stress profile changes from compression to extension across the leading edge, with regions of filament bending around focal adhesions. The model reproduces the observed reduction in retrograde flow speed upon exposure to cytochalasin D, which halts actin polymerization. Changes in crosslinker concentration and dynamics, as well as in the orientation pattern of newly added filaments demonstrate the model's ability to generate bundles of filaments perpendicular (actin arcs) or parallel (microspikes) to the protruding direction.

Platelet heterogeneity enhances blood clot volumetric contraction: An example of asynchrono-mechanical amplification

Physiological processes such as blood clotting and wound healing as well as pathologies such as fibroses and musculoskeletal contractures, all involve biological materials composed of a contracting cellular population within a fibrous matrix, yet how the microscale interactions among the cells and the matrix lead to the resultant emergent behavior at the macroscale tissue level remains poorly understood. Platelets, the anucleate cell fragments that do not divide nor synthesize extracellular matrix, represent an ideal model to study such systems. During blood clot contraction, microscopic platelets actively pull fibers to shrink the macroscale clot to less than 10% of its initial volume. We discovered that platelets utilize a new emergent behavior, asynchrono-mechanical amplification, to enhanced volumetric material contraction and to magnify contractile forces. This behavior is triggered by the heterogeneity in the timing of a population of actuators. This result indicates that cell heterogeneity, often attributed to stochastic cell-to-cell variability, can carry an essential biophysical function, thereby highlighting the importance of considering 4 dimensions (space + time) in cell-matrix biomaterials. This concept of amplification via heterogeneity can be harnessed to increase mechanical efficiency in diverse systems including implantable biomaterials, swarm robotics, and active polymer composites.

Assessing the derivation of time parameters from branched polymer coarse-grain model

The parameterization of rheological models for polymers is often obtained from experiments via the top-down approach. This procedure allows us to determine good fitting parameters for homogeneous materials but is less effective for polymer mixtures. From a molecular simulation point of view, the timescales needed to derive those parameters are often accessed through the use of coarse-grain potentials. However, these potentials are often derived from linear model systems and the transferability to a more complex structure is not straightforward. Here, we verify the transferability of a potential computed from linear polymer simulations to more complex molecular shapes and present a type of analysis, which was recently formulated in the framework of a tube theory, to a coarse-grain molecular approach in order to derive the input parameters for a rheological model. We describe the different behaviors arising from the local topological structure of molecular sub-units. Coarse-grain models and mean-field based tube theory for polymers form a powerful combination with potentially important applications.

Effectiveness of coarse graining degree and speedup on the dynamic properties of homopolymer

Evaluation of effective coarse graining (CG) degree and reasonable speedup relative to all-atomistic (AA) model was conducted to provide a basis for building appropriate larger-scale model. The reproducibility of atomistic conformation and temperature transferability both act as the analysis criteria to resolve the maximum acceptable CG degree. Taking short- and long time spans into account simultaneously in the estimation of computational speedup, a dynamic scaling factor is accessible in fitting mean squared displacement ratio of CG to AA as an exponential function. Computing loss in parallel running is an indispensable component in acceleration, which was also added in the evaluation. Subsequently, a quantified prediction of CG speedup arises as a multiplication of dynamic scaling factor, computing loss, time step, and the square of reduction in the number of degrees of freedom. Polyethylene oxide was adopted as a reference system to execute the direct Boltzmann inversion and iterative Boltzmann inversion. Bonded and non-bonded potentials were calculated in CG models with 1~4 monomers per bead. The effective CG degree was determined as two at the most with a speedup of four orders magnitude over AA in this study. Determination of effectiveness CG degree and the corresponding speedup prediction provide available tools in larger spatiotemporal-scale calculations.

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.

Behavior and mechanics of dense microgel suspensions

Suspensions of soft and highly deformable microgels can be concentrated far more than suspensions of hard colloids, leading to their unusual mechanical properties. Microgels can accommodate compression in suspensions in a variety of ways such as interpenetration, deformation, and shrinking. Previous experiments have offered insightful, but somewhat conflicting, accounts of the behavior of individual microgels in compressed suspensions. We develop a mesoscale computational model to probe the behavior of compressed suspensions consisting of microgels with different architectures at a variety of packing fractions and solvent conditions. We find that microgels predominantly change shape and mildly shrink above random close packing. Interpenetration is only appreciable above space filling, remaining small relative to the mean distance between cross-links. At even higher packing fractions, microgels solely shrink. Remarkably, irrespective of the single-microgel properties, and whether the suspension concentration is changed via changing the particle number density or the swelling state of the particles, which can even result in colloidal gelation, the mechanics of the suspension can be quantified in terms of the single-microgel bulk modulus, which thus emerges as the correct mechanical measure for these type of soft-colloidal suspensions. Our results rationalize the many and varied experimental results, providing insights into the relative importance of effects defining the mechanics of suspensions comprising soft particles.

Highly Oil-Repellent Thermoplastic Boundaries via Surface Delivery of CF3 Groups by Molecular Bottlebrush Additives

We fabricated thermoplastic surfaces possessing extremely limited water and oil wettability without employment of long-chain perfluoroalkyl (LCPFA) substances. Namely, by taking advantage of the structure and behavior of original oleophobic perfluoropolyether (PFPE) methacrylate (PFM) molecular bottlebrush (MBB) additive we obtained polymeric surfaces with oil contact angles well above 80° and surface energy on the level of 10 mN/m. Those angles and surface energies are the highest and the lowest respective values reported to date for any bulk solid flat organic surface not containing LCPFA. We show experimentally and computationally that this remarkable oil repellency is attributed to migration of small quantities of the oleophobic MBB additives to the surface of the thermoplastics. Severe mismatch in the affinity between the densely grafted long side chains of MBB and a host matrix promotes stretching and densification of mobile side chains delivering the lowest surface energy functionalities (CF₃) to the materials' boundary. Our studies demonstrate that PFM can be utilized as an effective low surface energy additive to conventional thermoplastic polymers, such as poly(methyl methacrylate) and Nylon-6. We show that films containing PFM achieve the level of oil repellency significantly higher than that of polytetrafluoroethylene (PTFE), a fully perfluorinated thermoplastic. The surface energy of the films is also significantly lower than that of PTFE, even at low concentrations of PFM additives.

Nanoparticle assembly modulated by polymer chain conformation in composite materials

Mixing nanoparticles into a strategically selected polymer matrix yields nanocomposites with well-controlled microstructures and unique properties and functions. The modulation of nanoparticle assembly by polymer chain conformation can play a dominant role in determining nanocomposite structures, yet such a physical mechanism remains largely unexplored. We hypothesize that highly ordered microdomains of rigid linear polymers provide a template for nanoparticle assembly into open fractal structures. We conducted mesoscopic computer simulations and physical experiments to elucidate how polymer chain conformation regulates the dynamic evolution of nanoparticle structures during the drying processing of polymer nanocomposite films. The evaporation of polymer-nanoparticle mixtures with varying chain stiffnesses was simulated using dissipative particle dynamics. The formation of distinguished nanoparticle assemblies as a result of matrix selection was further corroborated by probing nanoparticle aggregation in different polymer nanocomposite coatings. The results show that polymer conformation not only influences the dispersion states of individual particles (dispersed vs. aggregated), but also modulates the morphologies of large-scale assembly (globular vs. fractal). The emergence of nematically ordered polymer clusters when the chain rigidity is increased creates local solvent-rich "voids" that promote anisotropic particle aggregates, which then percolate into open fractal structures upon solvent evaporation. The nanoparticle dynamics also exhibits an intriguing non-monotonic behavior attributed to the transitions between the coupling and decoupling with polymer dynamics. The nanoparticle assembly morphologies obtained in simulations match well with the electron microscopy images taken in physical experiments.

Computational Design of Nanostructured Soft Interfaces: Focus on Shape Changes and Spreading of Cubic Nanogels

Understanding the dynamics of gels at soft interfaces is vital for a range of applications, from biocatalysis and drug delivery to enhanced oil recovery applications. Herein, we use dissipative particle dynamics simulations to focus on the shape changes of a cubic nanogel as it adsorbs from the aqueous phase onto the oil-water interface, effectively acting as a compatibilizer. Upon adsorption at the interface, the hydrogel spreads over the interface, adopting various shapes depending on its size and cross-link density. We characterize these shapes by the shape anisotropy and an effective extent of spreading. We highlight the differences between these characteristics for cubic and spherical nanogels and show that the choice of the cubic shape over the spherical one results in a wider range of topographies that could be dynamically prescribed onto the soft interface due to the gels' adsorption. We first validate our model parameters with respect to the known experimental values for polyacrylamide (PAAm) gels and focus on spreading and shape changes of PAAm nanogels onto the oil-water interfaces. We then probe the behavior of active gels by changing an affinity of the polymer matrix for the solvent, which can be caused by the application of an external stimulus (light, temperature, or change in the chemical composition of solvent). Furthermore, we focus on the interactions between multiple gels placed at the liquid-liquid interface. We show that controlling the shapes and the clustering of the gels at the interfaces via variations in solvent quality result in tailoring the dynamics and topography of soft nanostructured interfaces. Hence, our findings provide insights into the design of soft active nanostructured interfaces with topographies controlled externally via solvent quality.

Organization of associating or crosslinked actin filaments in confinement

A key factor of actin cytoskeleton organization in cells is the interplay between the dynamical properties of actin filaments and cell geometry, which restricts, confines and directs their orientation. Crosslinking interactions among actin filaments, together with geometrical cues and regulatory proteins can give rise to contractile rings in dividing cells and actin rings in neurons. Motivated by recent in vitro experiments, in this work we performed computer simulations to study basic aspects of the interplay between confinement and attractive interactions between actin filaments. We used a spring-bead model and Brownian dynamics to simulate semiflexible actin filaments that polymerize in a confining sphere with a rate proportional to the monomer concentration. We model crosslinking, or attraction through the depletion interaction, implicitly as an attractive short-range potential between filament beads. In confining geometries smaller than the persistence length of actin filaments, we show rings can form by curving of filaments of length comparable to, or longer than the confinement diameter. Rings form for optimal ranges of attractive interactions that exist in between open bundles, irregular loops, aggregated, and unbundled morphologies. The probability of ring formation is promoted by attraction to the confining sphere boundary and decreases for large radii and initial monomer concentrations, in agreement with prior experimental data. The model reproduces ring formation along the flat plane of oblate ellipsoids.

A coarse-grain model for entangled polyethylene melts and polyethylene crystallization

The Shinoda-DeVane-Klein (SDK) model is herein demonstrated to be a viable coarse-grain model for performing molecular simulations of polyethylene (PE), affording new opportunities to advance molecular-level, scientific understanding of PE materials and processes. Both structural and dynamical properties of entangled PE melts are captured by the SDK model, which also recovers important aspects of PE crystallization phenomenology. Importantly, the SDK model can be used to represent a variety of materials beyond PE and has a simple functional form, making it unique among coarse-grain PE models. This study expands the suite of tools for studying PE in silico and paves the way for future work probing PE and PE-based composites at the molecular level.

Modeling of Entangled Polymer Diffusion in Melts and Nanocomposites: A Review

This review concerns modeling studies of the fundamental problem of entangled (reptational) homopolymer diffusion in melts and nanocomposite materials in comparison to experiments. In polymer melts, the developed united atom and multibead spring models predict an exponent of the molecular weight dependence to the polymer diffusion very similar to experiments and the tube reptation model. There are rather unexplored parameters that can influence polymer diffusion such as polymer semiflexibility or polydispersity, leading to a different exponent. Models with soft potentials or slip-springs can estimate accurately the tube model predictions in polymer melts enabling us to reach larger length scales and simulate well entangled polymers. However, in polymer nanocomposites, reptational polymer diffusion is more complicated due to nanoparticle fillers size, loading, geometry and polymer-nanoparticle interactions.

Scaling and Interactions of Linear and Ring Polymer Brushes via DPD Simulations

Single and double layers of polymer coated surfaces are investigated by means of Dissipative Particle Dynamics (DPD), focusing on the difference between grafted ring and linear chains. Several different surface coverages σ , as well as chain lengths N and brush separations D, are analyzed for athermal, i.e., good solvent, conditions. The size in the form of the radius of gyration R g , the shape as asphericity δ ∗ , and orientation β ∗ , as well as density profiles as functions of distance from grafting plane ρ ( z ) , are studied. The effect of an added bond repulsion potential to suppress bond crossing in DPD is analyzed. Scaling laws of R g and its components R g ⊥ and R g ∥ are investigated. We find R g ∝ N ν , ν = 0.588 for surface coverages below the overlap surface concentration σ ∗ . For σ > σ ∗ we find R g ⊥ ∝ N ν ⊥ , ν ⊥ ≅ 1 and R g ∥ ∝ N ν ∥ , ν ∥ = 1 / 2 of ring brushes with the standard DPD model and ν ∥ ≅ 2 / 5 with added bond repulsion. The σ dependence of the radius of gyration was found to be R g ∝ σ μ with μ = 1 / 3 for surface coverages grater than σ ∗ . The perpendicular component R g ⊥ scales independent of the bond repulsion potential as R g ⊥ ∝ σ μ ⊥ , μ ⊥ = 1 / 3 , whereas the scaling of the parallel component exhibits a topological repulsion dependence R g ∥ ∝ σ μ ∥ , μ ∥ = - 1 / 12 for standard DPD and μ ∥ = - 1 / 6 for bond repulsion.