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Letting free polymers diffuse from solution into a crosslinked polymer gel is often a crucial processing step in the synthesis of multiphase polymer-based gels, e.g., core-shell microgels. Here we use coarse-grained molecular dynamics simulations to obtain molecular insights into this process. We consider idealized situations where the gel is modeled as a regular polymer network with the topology of a diamond lattice, and all free polymers and strands have the same length and consist of the same type of monomer. After bringing the gel and the polymer solution into contact, two time regimes are observed: An initial compression of the gel caused by the osmotic pressure of the solution, followed by an expansion due to swelling. We characterize the time evolution of density profiles, the penetration of free polymers into the gel and the connection between the gel and solution phase. The interfacial structure locally equilibrates after roughly 100 chain relaxation times. At late times, the free chains inside the gel undergo a percolation transition if the polymer concentration in the gel exceeds a critical value, which is of the same order as the overlap concentration. The fluctuations of the interface can be described by a capillary wave model that accounts for the elasticity of the gel. Based on this, we extract the interfacial tension of the gel-solution interface. Interestingly, both the interfacial tension and the local interfacial width increase with increasing free polymer concentration - in contrast to liquid-liquid interfaces, where these two quantities are typically anticorrelated.

We present an extensive analysis of the relaxation dynamics of entangled linear polymer melts via long-time molecular dynamics simulations of a generic bead-spring model. We study the mean-squared displacements, the autocorrelation function of the end-to-end vector, $P(t)$, the single-chain dynamic structure factor, $S(q,t)$, and the linear viscoelastic properties, especially the shear stress relaxation modulus, $G(t)$. The simulation data are compared with the theoretically expected scaling laws for different time regimes of entangled melts, and with analytical expressions that account for different relaxation mechanisms in the tube model, namely, reptation, contour length fluctuation (CLF), and constraint release (CR). CLF involves a $t^{1/4}$ scaling regime in the time-dependence of $(1-P(t))$. With increasing chain length, a gradual development of this scaling regime is observed. In the absence of CR, the tube model further predicts that at long times, the chain dynamics is governed by one central quantity, the ``surviving tube fraction'' $\mu(t)$. As a result, one expects $S(q,t) \propto G(t) \propto P(t)$ in that time regime. We test this prediction by comparing $S(q,t)$ and $G(t)$ with $P(t)$. For both quantities, proportionality with $P(t)$ is not observed, indicating that CR has an important effect on the relaxation of these two quantities. Instead, to a very good approximation, we find $G(t)\propto P(t)^{2}$ at late times, which is consistent with the dynamic tube dilation or double reptation approximations for the CR process. In addition, we calculate non-local mobility functions, which can be used in dynamic density functional theories for entangled inhomogeneous polymer blends, and discuss the effect of entanglements on the shape of these functions.

Sphere-patterned ultrathin block copolymers films are potentially interesting for a variety of applications in nanotechnology. We use self-consistent field theory to investigate the elastic response of sphere monolayer films with respect to in-plane shear, in-plane extension and compression deformations, and with respect to bending. The relations between the in-plane elastic moduli is roughly compatible with the expectations for two-dimensional elastic systems with hexagonal symmetry, with one notable exception: The pure shear and the simple shear moduli differ from each other by roughly 20%. Even more importantly, the bending constants are found to be negative, indicating that free-standing block copolymer membranes made of only sphere mono-layer are inherently unstable above the glass transition. Our results are discussed in view of experimental findings.

We investigate the effect of polydispersity on the properties of curved linear brushes in good solvent and for molten brushes. To this end, we extend the strong stretching theory for polydisperse brushes to curved geometries and investigate the polymer chain end profiles, bending moduli and other properties for experimentally relevant polymer chain length distributions of the Schulz-Zimm type. We also investigate the properties of End Exclusion Zones (EEZ) that may appear in convex geometries under certain conditions, and show that their position in the brush can be engineered by careful selection of the polymer length distribution. Lastly, we propose a method to engineer chain end profiles by engineering the polymer length distribution.

We study the equilibrium properties and the wetting behavior of a simple liquid on a polymer brush, with and without presence of lubricant by multibody Dissipative Particle Dynamics simulations. The lubricant is modelled as a polymeric liquid consisting of short chains that are chemically identical to the brush polymers. We investigate the behavior of the brush in terms of the grafting density and the amount of lubricant present. Regarding the wetting behavior, we study a sessile droplet on top of the brush. The droplet consists of non-bonded particles that form a dense phase. Our model and choice of parameters result in the formation of a wetting ridge and in the cloaking of the droplet by the lubricant, i.e. the lubricant chains creep up onto the droplet and eventually cover its surface completely. Cloaking is a phenomenon that is observed experimentally and is of integral importance to the dynamics of sliding droplets. We quantify the cloaking in terms of its thickness, which increases with the amount of lubricant present. The analysis reveals a well-defined transition point where the cloaking sets in. We propose a thermodynamic theory to explain this behavior. In addition we investigate the dependence of the contact angles on the size of the droplet and the possible effect of line tension. We quantify the variation of the contact angle with the curvature of the contact line on a lubricant free brush and find a negative value for the line tension. Finally we investigate the effect of cloaking/lubrication on the contact angles and the wetting ridge. We find that lubrication and cloaking reduce the contact angles by a couple of degrees. The effect on the wetting ridge is a reduction in the extension of the brush chains near the three phase contact line, an effect that was also observed in experiments of droplets on crosslinked gels.

Understanding the dynamics of drops on polymer-coated surfaces is crucial for optimizing applications such as self-cleaning materials or microfluidic devices. While the static and dynamic properties of deposited drops have been well characterised, a microscopic understanding of the underlying dynamics is missing. In particular, it is unclear how drop dynamics depends on the amount of uncrosslinked chains in the brush, because experimental techniques fail to quantify those. Here we use coarse-grained simulations to study droplets moving on a lubricated polymer brush substrate under the influence of an external body force. The simulation model is based on the many body dissipative particle dynamics (mDPD) method and designed to mimic a system of water droplets on polydimethylsiloxane (PDMS) brushes with chemically identical PDMS lubricant. In agreement with experiments, we find a sublinear power law dependence between the external force $F$ and the droplet velocity $v$, $F \propto v^\alpha$ with $\alpha <1$; however, the exponents differ ($\alpha \sim 0.6-0.7$ in simulations versus $\alpha \sim 0.25$ in experiments). With increasing velocity, the droplets elongate and the receding contact angle decreases, whereas the advancing contact angle remains roughly constant. Analyzing the flow profiles inside the droplet reveals that the droplets do not slide, but roll, with vanishing slip at the substrate surface. Surprisingly, adding lubricant has very little effect on the effective friction force between the droplet and the substrate, even though it has a pronounced effect on the size and structure of the wetting ridge, especially above the cloaking transition.

The non-invasive spatiotemporal control of cellular functions, organization of tissues, and even the behavior of small animals has become paramount for advanced therapies. As magnetic fields do not interact with biological matter, their application is not only suitable for in vitro experiments but also for in vivo applications, even in deep tissues. Particularly, the remote manipulation of paramagnetic entities through magnetic instruments has emerged as a promising approach across various biological contexts. Despite similarities in basic experimental concepts, variations in the properties and descriptions of those magnetic instruments among the authors and studies resulted in a lack of reproducibility and comparability. Therefore, this article addresses the question of how to standardize the characterization of magnetic instruments. Our emphasis lies on the ability of magnetic systems to control the movement of paramagnetic objects such as ferro- or superparamagnetic particles, within organisms. This movement is achieved by exerting a force on magnetic particles by exposing them to a locally varying magnetic field. While it is well-known that the exerted force depends on the spatial variation (i.e. the gradient) of the magnetic field, the magnitude of the field is equally important. However, this second factor is often neglected in the literature. Therefore, we conduct a comprehensive analysis and discussion of both factors. Furthermore, we propose a novel descriptor, termed "effective gradient", which combines both dependencies. To illustrate, we characterize different magnet systems by calculating and comparing the different quantities and relating them to two experiments with different superparamagnetic nanoparticles., Comment: submitted to Scientific Reports

Langevin equations or generalized Langevin equations (GLEs) are popular models for describing the motion of a particle in a fluid medium in an effective manner. Here we examine particles immersed in an inherently nonequilibrium fluid, i.e., an active bath, which are subject to an external force. Specifically, we consider two types of forces that are highly relevant for microrheological studies: A harmonic, trapping force and a constant, "drag" force. We study such systems by molecular simulations and use the simulation data to derive an effective GLE description. We find that, in an active bath, the external force in the GLE is not equal to the physical external force, but rather a renormalized external force, which can be significantly smaller. The effect cannot be attributed to the mere temperature renormalization, which is also observed.

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.

Polymer materials have the characteristic feature that they are multiscale systems by definition. Already the description of a single molecules involves a multitude of different scales, and cooperative processes in polymer assemblies are governed by the interplay of these scales. Polymers have been among the first materials for which systematic multiscale techniques were developed, yet they continue to present extraordinary challenges for modellers. In this perspective, we review popular models that are used to describe polymers on different scales and discuss scale bridging strategies such as static and dynamic coarse-graining methods and multiresolution approaches. We close with a list of hard problems which still need to be solved in order to gain a comprehensive quantitative understanding of polymer systems on all scales., Comment: to appear in ACS Polymers Au

Recently a novel class of responsive uncharged polymer brushes has been proposed [Klushin et al, J. Chem. Phys. 154, 074904 (2021)] where the brush-forming chains have an affinity to the substrate. For sufficiently strong surface interactions, a fraction of chains condenses into a near-surface layer, while the remaining ones form the outer brush with a reduced grafting density. The dense layer and the more tenuous outer brush can be seen as coexisting microphases. The effective grafting density of the outer brush is controlled by the adsorption strength and can be changed reversibly as a response to changes in environmental parameters. In this paper we use numerical self-consistent field calculations and theoretical considerations to study this phenomenon in polydisperse brushes. Our results reveal an unexpected effect: Although all chains are chemically identical, shorter chains are adsorbed preferentially. Hence, with the increase in the surface affinity parameter, a reduction in the surface grafting density of the residual brush is accompanied by a change in the shape of its molecular mass distribution. In particular, an originally bidisperse brush can be effectively transformed into a nearly monodisperse one containing only the longer chain fraction., Comment: 14 pages, 19 figures, submitted to J. Chem. Phys

Fluctuation-dissipation relations or "theorems" (FDTs) are fundamental for statistical physics and can be rigorously derived for equilibrium systems. Their applicability to non-equilibrium systems is, however, debated. Here, we simulate an active microrheology experiment, in which a spherical colloid is pulled with a constant external force through a fluid, creating near-equilibrium and far-from-equilibrium systems. We characterize the structural and dynamical properties of these systems, and reconstruct an effective generalized Langevin equation (GLE) for the colloid dynamics. Specifically, we test the validity of two FDTs: The first FDT relates the non-equilibrium response of a system to equilibrium correlation functions, and the second FDT relates the memory friction kernel in the GLE to the stochastic force. We find that the validity of the first FDT depends strongly on the strength of the external driving: it is fulfilled close to equilibrium and breaks down far from it. In contrast, we observe that the second FDT is always fulfilled. We provide a mathematical argument why this generally holds for memory kernels reconstructed from a deterministic Volterra equation for correlation functions, even for non-stationary non-equilibrium systems. Motivated by the Mori-Zwanzig formalism, we therefore suggest to impose an orthogonality constraint on the stochastic force, which is in fact equivalent to the validity of this Volterra equation. Such GLEs automatically satisfy the second FDT and are unique, which is desirable when using GLEs for coarse-grained modeling., Comment: Typos corrected in the Appendix

We propose a dynamic coarse-graining (CG) scheme for mapping heterogeneous polymer fluids onto extremely CG models in a dynamically consistent manner. The idea is to use as target function for the mapping a wave-vector dependent mobility function derived from the single-chain dynamic structure factor, which is calculated in the microscopic reference system. In previous work, we have shown that dynamic density functional calculations based on this mobility function can accurately reproduce the order/disorder kinetics in polymer melts, thus it is a suitable starting point for dynamic mapping. To enable the mapping over a range of relevant wave vectors, we propose to modify the CG dynamics by introducing internal friction parameters that slow down the CG monomer dynamics on local scales, without affecting the static equilibrium structure of the system. We illustrate and discuss the method using the example of infinitely long linear Rouse polymers mapped onto ultrashort CG chains. We show that our method can be used to construct dynamically consistent CG models for homopolymers with CG chain length N=4, whereas for copolymers, longer CG chain lengths are necessary, Comment: to appear in the J. Phys.: Cond. Matter - update of references and small changes in Sec. 2.1

We propose a novel class of responsive polymer brushes, where the effective grafting density can be controlled by external stimuli. This is achieved by using end-grafted polymer chains that have an affinity to the substrate. For sufficiently strong surface interactions, a fraction of chains condenses into a near-surface layer, while the remaining ones form the outer brush. The dense layer and the more tenuous outer brush can be seen as coexisting microphases. The effective grafting density of the outer brush is controlled by the adsorption strength and can be changed reversibly and in a controlled way as a response to changes in environmental parameters. The effect is demonstrated by numerical SCF calculations and analyzed by scaling arguments. Since the thickness of the denser layer is about a few monomer sizes, its capacity to form a microphase is limited by the product of the brush chain length and the grafting density. We explore the range of chain lengths and grafting densities where the effect is most pronounced. In this range, the SCF studies suggest that individual chains inside the brush show large rapid fluctuations between two states that are separated by only a small free energy barrier. The behavior of the brush as a whole, however, does not reflect these large fluctuations, and the effective grafting density varies smoothly as a function of the control parameters., Comment: To appear in J. Chem. Phys

We investigate the molecular origin of shear-thinning in melts of flexible, semiflexible and rigid oligomers with coarse-grained simulations of a sheared melt. Alignment, stretching and tumbling modes or suppression of the latter all contribute to understanding how macroscopic flow properties emerge from the molecular level. By performing simulations of single chains in a shear flow, we identify which of these phenomena are of collective nature and arise through interchain interactions and which are already present in dilute systems. Building upon these microscopic simulations we identify by means of the Irving-Kirkwood formula the corresponding macroscopic stress tensor for a non-Newtonian polymer fluid. Shear-thinning effects in oligomer melts are also demonstrated by macroscopic simulations of a channel flow. The latter have been obtained by the discontinuous Galerkin method approximating macroscopic polymer flows. Our study confirms the influence of microscopic details in the molecular structure of short polymers such as chain flexibility on macroscopic polymer flows.

The generalized Langevin equation is a model for the motion of coarse-grained particles where dissipative forces are represented by a memory term. The numerical realization of such a model requires the implementation of a stochastic delay-differential equation and the estimation of a corresponding memory kernel. Here we develop a new approach for computing a data-driven Markov model for the motion of the particles, given equidistant samples of their velocity autocorrelation function. Our method bypasses the determination of the underlying memory kernel by representing it via up to about twenty auxiliary variables. The algorithm is based on a sophisticated variant of the Prony method for exponential interpolation and employs the Positive Real Lemma from model reduction theory to extract the associated Markov model. We demonstrate the potential of this approach for the test case of anomalous diffusion, where data are given analytically, and then apply our method to velocity autocorrelation data of molecular dynamics simulations of a colloid in a Lennard-Jones fluid. In both cases, the VACF and the memory kernel can be reproduced very accurately. Moreover, we show that the algorithm can also handle input data with large statistical noise. We anticipate that it will be a very useful tool in future studies that involve dynamic coarse-graining of complex soft matter systems.

We propose and compare different strategies to construct dynamic density functional theories (DDFTs) for inhomogeneous polymer systems close to equilibrium from microscopic simulation trajectories. We focus on the systematic construction of the mobility coefficient, $\Lambda(r,r')$, which relates the thermodynamic driving force on monomers at position $r'$ to the motion of monomers at position $r$. A first approach based on the Green-Kubo formalism turns out to be impractical because of a severe plateau problem. Instead, we propose to extract the mobility coefficient from an effective characteristic relaxation time of the single chain dynamic structure factor. To test our approach, we study the kinetics of ordering and disordering in diblock copolymer melts. The DDFT results are in very good agreement with the data from corresponding fine-grained simulations., Comment: Some typos corrected compared to published version (Eqs. (32) and (38))

The self-consistent field theory is a popular and highly successful theoretical framework for studying equilibrium (co)polymer systems at the mesoscopic level. Dynamic density functionals allow one to use this framework for studying dynamical processes in the diffusive, non-inertial regime. The central quantity in these approaches is the mobility function, which describes the effect of chain connectivity on the nonlocal response of monomers to thermodynamic driving fields. In a recent study [Mantha et al, Macromolecules 53, 3409 (2020)], we have developed a method to systematically construct mobility functions from reference fine-grained simulations. Here we focus on melts of linear chains in the Rouse regime and show how the mobility functions can be calculated semi-analytically for multiblock copolymers with arbitrary sequences without resorting to simulations. In this context, an accurate approximate expression for the single-chain dynamic structure factor is derived. Several limiting regimes are discussed. Then we apply the resulting density functional theory to study ordering processes in a two-length scale block copolymer system after instantaneous quenches into the ordered phase. Different dynamical regimes in the ordering process are identified: At early times, the ordering on short scales dominates; at late times, the ordering on larger scales takes over. For large quench depths, the system does not necessarily relax into the true equilibrium state. Our density functional approach could be used for the computer-assisted design of quenching protocols in order to create novel nonequilibrium materials., Comment: Some typos have been corrected

We develop a dynamic mean-field theory for polar active particles that interact through a self-generated field, in particular one generated through emitting a chemical signal. While being a form of chemotactic response, it is different from conventional chemotaxis in that particles discontinuously change their motility when the local concentration surpasses a threshold. The resulting coupled equations for density and polarization are linear and can be solved analytically for simple geometries, yielding inhomogeneous density profiles. Specifically, here we consider a planar and circular interface. Our theory thus explains the observed coexistence of dense aggregates with an active gas. There are, however, differences to the more conventional picture of liquid-gas coexistence based on a free energy, most notably the absence of a critical point. We corroborate our analytical predictions by numerical simulations of active particles under confinement and interacting through volume exclusion. Excellent quantitative agreement is reached through an effective translational diffusion coefficient. We finally show that an additional response to the chemical gradient direction is sufficient to induce vortex clusters. Our results pave the way to engineer motility responses in order to achieve aggregation and collective behavior even at unfavorable conditions.

It is well-known that magnetic forces can induce a formation of densely packed strings of magnetic particles or even sheafs of several strings (spindles). Here we show that in a sufficiently strong magnetic field, more complex aggregates of particles, translating with a much faster speed than would be for a single particle or even a spindle, can be assembled at the water-air interface. Such a superfast flotilla is composed of many distant strings or spindles, playing a role of its vessels, and moves, practically, as a whole. We provide theoretical results to interpret the effect of a collective motion of such magnetic vessels. Our theory shows that, in contrast to an isolated chain or spindle, which velocity grows logarithmically with the number of magnetic particles, the speed of the interface flotilla becomes much higher, being proportional to the square root of their number. These results may guide the design of magnetic systems for extremely fast controlled delivery., Comment: 6 pages, 5 figures

We investigate the effect of polymer length dispersity on the properties of self-assembled micelles in solution by self-consistent field calculations. Polydispersity stabilizes micelles by raising the free energy barriers of micelle formation and dissolution. Most importantly, it significantly reduces the size fluctuations of micelles: Block copolymers of moderate polydispersity form more uniform particles than their monodisperse counterparts. We attribute this to the fact that the packing of the solvophobic monomers in the core can be optimized if the constituent polymers have different length., Comment: 4 main figures and 4 supplementary figures. Manuscript accepted for publication in Physical Review Materials

Nanoparticles coated with hydrophilic polymers often show a reduction in unspecific interactions with the biological environment, which improves their biocompatibility. The molecular determinants of this reduction are not very well understood yet, and their knowledge may help improving nanoparticle design. Here we address, using molecular dynamics simulations, the interactions of human serum albumin, the most abundant serum protein, with two promising hydrophilic polymers used for the coating of therapeutic nanoparticles, poly(ethylene-glycol) and poly-sarcosine. By simulating the protein immersed in a polymer-water mixture, we show that the two polymers have a very similar affinity for the protein surface, both in terms of the amount of polymer adsorbed and also in terms of the type of amino acids mainly involved in the interactions. We further analyze the kinetics of adsorption and how it affects the polymer conformations. Minor differences between the polymers are observed in the thickness of the adsorption layer, that are related to the different degree of flexibility of the two molecules. In comparison poly-alanine, an isomer of poly-sarcosine known to self-aggregate and induce protein aggregation, shows a significantly larger affinity for the protein surface than PEG and PSar, which we show to be related not to a different patterns of interactions with the protein surface, but to the different way the polymer interacts with water.

We propose a generalized Langevin dynamics (GLD) technique to construct non-Markovian particle-based coarse-grained models from fine-grained reference simulations and to efficiently integrate them. The proposed GLD model has the form of a discretized generalized Langevin equation with distance-dependent two-particle contributions to the self- and pair-memory kernels. The memory kernels are iteratively reconstructed from the dynamical correlation functions of an underlying fine-grained system. We develop a simulation algorithm for this class of non-Markovian models that scales linearly with the number of coarse-grained particles. Our GLD method is suitable for coarse-grained studies of systems with incomplete time scale separation, as is often encountered, e.g., in soft matter systems. We apply the method to a suspension of nanocolloids with frequency-dependent hydrodynamic interactions. We show that the results from GLD simulations perfectly reproduce the dynamics of the underlying fine-grained system. The effective speedup of these simulations amounts to a factor of about $10^4$. Additionally, the transferability of the coarse-grained model with respect to changes of the nanocolloid density is investigated. The results indicate that the model is transferable to systems with nanocolloid densities that differ by up to one order of magnitude from the density of the reference system., Comment: 16 pages, 6 figures, accepted by Soft Matter (https://pubs.rsc.org/en/content/articlelanding/2018/sm/c8sm01817k#!divAbstract)

We present a hybrid simulation method which allows one to study the dynamical evolution of self-assembling (co)polymer solutions in the presence of hydrodynamic interactions. The method combines an established dynamic density functional theory for polymers that accounts for the nonlocal character of chain dynamics at the level of the Rouse model, the external potential dynamics (EPD) model, with an established Navier-Stokes solver, the Lattice Boltzmann (LB) method. We apply the method to study the self-assembly of nanoparticles and vesicles in two-dimensional copolymer solutions in a typical microchannel Poiseuille flow profile. The simulations start from fully mixed systems which are suddenly quenched below the spinodal line. In order to isolate effects caused by walls, we use a reverse Poiseuille flow geometry with periodic boundary conditions. We identify three stages of self assembly, i.e., initial spinodal decomposition, particle nucleation, and particle growth (ripening). We find that (i) In the presence of shear, the nucleation of droplets is delayed by an amount roughly proportional to the shear rate, (ii) Shear flow greatly increases the rates of particle fusions, (iii) in later stages of self-assembly, stronger shear flows may induce irreversible shape transformation {\em via} finger formation, in particular in vesicle systems. The combination of these effects lead to an accumulation of particles close to the center of the Poiseuille flow profile, and the polymeric matter has a double peak distribution centered around the flow maximum.

The co-solvency method is a method for the size controlled preparation of nanoparticles like polymersomes, where a poor co-solvent is mixed into a homogeneous copolymer solution to trigger precipitation of the polymer. The size of the resulting particles is determined by the rate of co-solvent addition. We use the Cahn-Hilliard equation with a Flory-Huggins free energy model to describe the precipitation of a polymer under changing solvent quality by applying a time dependent Flory-Huggins interaction parameter. The analysis focuses on the characteristic size R of polymer aggregates that form during the initial spinodal decomposition stage, and especially on how R depends on the rate s of solvent quality change. Both numerical results and a perturbation analysis predict a power law dependence $R \sim s^{-1/6}$, which is in agreement with power laws for the final particle sizes that have been reported from experiments and molecular dynamics simulations. Hence, our model results suggest that the nanoparticle size in size-controlled precipitation is essentially determined during the spinodal decomposition stage.

The self-assembly of copolymeric vesicles and micelles in micromixers is studied by External Potential Dynamics (EPD) simulations -- a dynamic density functional approach that explicitly accounts for the polymer architecture both at the level of thermodynamics and dynamics. Specifically, we focus on the co-solvent method, where nanoparticle precipitation is triggered by mixing a poor co-solvent into a homogeneous copolymer solution in a micromixer. Experimentally, it has been reported that the flow rate in the micromixers influences the size of the resulting particles as well as their morphology: At small flow rates, vesicles dominate; with increasing flow rate, more and more micelles form, and the size of the particles decreases. Our simulation model is based on the assumption that the flow rate mainly sets the rate of mixing of solvent and co-solvent. The simulations reproduce the experimental observations at an almost quantitative level and provide insight into the underlying physical mechanisms: First, they confirm an earlier conjecture according to which the size control takes place in the earliest stage of the particle self-assembly, during the spinodal decomposition of polymers and solvent. Second, they reveal a crossover between different morphological regimes as a function of mixing rate. Hence they demonstrate that varying the mixing rate in a co-solvent setup is an effective way to control two key properties of drug delivery systems, their mean size and their morphology.

Using Brownian Dynamics, we study the dynamical behavior of a polymer grafted onto an adhesive surface close to the mechanically induced adsorption-stretching transition. Even though the transition is first order, (in the infinite chain length limit, the stretching degree of the chain jumps discontinuously), the characteristic relaxation time is found to grow according to a power law as the transition point is approached. We present a dynamic effective interface model which reproduces these observations and provides an excellent quantitaive description of the simulations data. The generic nature of the theoretical model suggests that the unconventional mixing of features that are characteristic for first-order transitions (a jump in an order parameter) and features that are characteristic of critical points (anomalous slowdown) may be a common phenomenon in force-driven phase transitions of macromolecules., Comment: 5 figures

Experimental data on thin films of cylinder-forming block copolymers (BC) -- free-standing BC membranes as well as supported BC films -- strongly suggest that the local orientation of the BC patterns is coupled to the geometry in which the patterns are embedded. We analyze this phenomenon using general symmetry considerations and numerical self-consistent field studies of curved BC films in cylindrical geometry. The stability of the films against curvature-induced dewetting is also analyzed. In good agreement with experiments, we find that the BC cylinders tend to align along the direction of curvature at high curvatures. At low curvatures, we identify a transition from perpendicular to parallel alignment in supported films, which is absent in free standing membranes. Hence both experiments and theory show that curvature can be used to manipulate and align BC patterns.

We use Brownian dynamics simulations and analytical theory to compare two prominent types of single molecule transitions. One is the adsorption transition of a loop (a chain with two ends bound to an attractive substrate) driven by an attraction parameter $\varepsilon$, and the other is the loop-stretch transition in a chain with one end attached to a repulsive substrate, driven by an external end-force $F$ applied to the free end. Specifically, we compare the behavior of the respective order parameters of the transitions, i.e., the mean number of surface contacts in the case of the adsorption transition, and the mean position of the chain end in the case of the loop-stretch transition. Close to the transition points, both the static and the dynamic behavior of chains with different length $N$ are very well described by a scaling Ansatz with the scaling parameters $(\varepsilon - \varepsilon^*) N^\phi$ (adsorption transition) and $(F-F^*) N^\nu$ (loop-stretch transition), respectively, where $\phi$ is the crossover exponent of the adsorption transition, and $\nu$ the Flory exponent. We show that both the loop-stretch and the loop adsorption transitions provide an exceptional opportunity to construct explicit analytical expressions for the crossover functions which perfectly describe all simulation results on static properties in the finite-size scaling regime. Explicit crossover functions are based on the Ansatz for the analytical form of the order parameter distributions at the respective transition points. In contrast to the close similarity in equilibrium static behavior, the dynamic relaxation at the two transitions shows qualitative differences, especially in the strongly ordered regimes., Comment: 14 pages, 10 figures

We study active Brownian particles as a paradigm for genuine non-equilibrium phase transitions. Access to the critical point in computer simulations is obstructed by the fact that the density is conserved. We propose a modification of sampling finite-size fluctuations and successfully test this method for the 2D Ising model. Using this model allows us to determine accurately the critical point of two dimensional active Brownian particles at $\text{Pe}_{\text{cr}}=40(2)$, $\phi_{\text{cr}}=0.597(3)$. Based on this estimate, we study the corresponding critical exponents $\beta$, $\gamma/\nu$, and $\nu$. Our results are incompatible with the 2D-Ising exponents, thus raising the question whether there exists a corresponding non-equilibrium universality class.

Hydrodynamic interactions play an important role in many areas of soft matter science. In simulations with implicit solvent, various techniques such as Brownian or Stokesian dynamics explicitly include hydrodynamic interactions a posteriori by using hydrodynamic diffusion tensors derived from the Stokes equation. However, this equation assumes the interaction to be instantaneous which is an idealized approximation and only valid on long time scales. In the present paper, we go one step further and analyze the time-dependence of hydrodynamic interactions in a compressible fluid on the basis of the linearized Navier-Stokes equation. The theoretical results show that the compressibility of the fluid has a significant impact on frequency-dependent pair interactions. The predictions of the hydrodynamic theory are compared to molecular dynamics simulations of two solid spheres in a Lennard-Jones fluid. For this system we reconstruct memory functions by extending the inverse Volterra technique. The simulation data agree very well with the theory, therefore, the theory can be used to implement dynamically consistent hydrodynamic interactions in the increasingly popular field of non-Markovian modeling., Comment: 12 pages, 15 figures, published by Physics of Fluids

In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations. In this article, we propose an iterative method for memory reconstruction from dynamical correlation functions. Compared to previously proposed noniterative techniques, it ensures by construction that the target correlation functions of the original fine-grained systems are reproduced accurately by the coarse-grained system, regardless of time step and discretization effects. Furthermore, we also propose a new numerical integrator for generalized Langevin equations that is significantly more accurate than the more commonly used generalization of the velocity Verlet integrator. We demonstrate the performance of the above-described methods using the example of backflow-induced memory in the Brownian diffusion of a single colloid. For this system, we are able to reconstruct realistic coarse-grained dynamics with time steps about 200 times larger than those used in the original molecular dynamics simulations., Comment: 9 pages, 10 figures

Dynamic density functionals (DDFs) are popular tools for studying the dynamical evolution of inhomogeneous polymer systems. Here, we present a systematic evaluation of a set of diffusive DDF theories by comparing their predictions with data from particle-based Brownian dynamics (BD) simulations for two selected problems: Interface broadening in compressible A/B homopolymer blends after a sudden change of the incompatibility parameter, and microphase separation in compressible A:B diblock copolymer melts. Specifically, we examine (i) a local dynamics model, where monomers are taken to move independently from each other, (ii) a nonlocal "chain dynamics" model, where monomers move jointly with correlation matrix given by the local chain correlator, and (iii,iv) two popular approximations to (ii), namely (iii) the Debye dynamics model, where the chain correlator is approximated by its value in a homogeneous system, and (iv) the computationally efficient "external potential dynamics" (EPD) model. With the exception of EPD, the value of the compressibility parameter has little influence on the results. In the interface broadening problem, the chain dynamics model reproduces the BD data best. However, the closely related EPD model produces large spurious artefacts. These artefacts disappear when the blend system becomes incompressible. In the microphase separation problem, the predictions of the nonlocal models (ii-iv) agree with each other and significantly overestimate the ordering time, whereas the local model (i) underestimates it. We attribute this to the multiscale character of the ordering process, which involves both local and global chain rearrangements. To account for this, we propose a mixed local/nonlocal DDF scheme which quantitatively reproduces all BD simulation data considered here., Comment: 17 pages, 9 figures, Macromolecules, 2017

We present a multiscale hybrid particle-field scheme for the simulation of relaxation and diffusion behavior of soft condensed matter systems. It combines particle-based Brownian dynamics and field-based local dynamics in an adaptive sense such that particles can switch their level of resolution on the fly. The switching of resolution is controlled by a tuning function which can be chosen at will according to the geometry of the system. As an application, the hybrid scheme is used to study the kinetics of interfacial broadening of a polymer blend, and is validated by comparing the results to the predictions from pure Brownian dynamics and pure local dynamics calculations., Comment: 10 Pages, 5 Figures

Extensive molecular dynamics simulations reveal that the interactions between proteins and poly(ethylene glycol)(PEG) can be described in terms of the surface composition of the proteins. PEG molecules accumulate around non-polar residues while avoiding polar ones. A solvent-accessible-surface-area model of protein adsorption on PEGylated nanoparticles accurately fits a large set of data on the composition of the protein corona recently obtained by label-free proteomic mass spectrometry., Comment: submitted to Nanonscale on Sep. 5th 2016

We study the effect of polydispersity on the structure of polymer brushes by analytical theory, a numerical self-consistent field approach, and Monte Carlo simulations. The polydispersity is represented by the Schulz-Zimm chain-length distribution. We specifically focus on three different polydispersities representing sharp, moderate and extremely wide chain length distributions and derive explicit analytical expressions for the chain end distributions in these brushes. The results are in very good agreement with numerical data obtained with self-consistent field calculations and Monte Carlo simulations. With increasing polydispersity, the brush density profile changes from convex to concave, and for given average chain length $N_n$ and grafting density $\sigma$, the brush height $H$ is found to scale as $(H/H_{\mathrm{mono}}-1)\propto(N_w/N_n-1)^{1/2}$ over a wide range of polydispersity indices $N_w/N_n$ (here $H_{\mathrm{mono}}$ is the height of the corresponding monodisperse brush. Chain end fluctuations are found to be strongly suppressed already at very small polydispersity. Based on this observation, we introduce the concept of the brush as a near-critical system with two parameters (scaling variables), $(N_{n}\sigma^{2/3})^{-1}$ and $(N_w/N_n-1)^{1/2}$, controlling the distance from the critical point. This approach provides a good description of the simulation data. Finally we study the hydrodynamic penetration length $l_\mathrm{p}$ for brush-coated surfaces in flow. We find that it generally increases with polydispersity. The scaling behavior crosses over from $l_\mathrm{p}\sim N_\mathrm{n}^{1/2}\sigma^{-1/6}$ for monodisperse and weakly polydisperse brushes to $l_\mathrm{p}\sim N_{n}^{2/3}$ for strongly polydisperse brushes., Comment: 21pages, 9 figures. Accepted for publication in Macromolecues

This article summarizes a variety of physical mechanisms proposed in the literature, which can generate micro- and nanodomains in multicomponent lipid bilayers and biomembranes. It mainly focusses on lipid-driven mechanisms that do not involve direct protein-protein interactions. Specifically, it considers (i) equilibrium mechanisms based on lipid-lipid phase separation such as critical cluster formation close to critical points, and multiple domain formation in curved geometries, (ii) equilibrium mechanisms that stabilize two-dimensional microemulsions, such as the effect of linactants and the effect of curvature-composition coupling in bilayers and monolayers, and (iii) non-equilibrium mechanisms induced by the interaction of a biomembrane with the cellular environment, such as membrane recycling and the pinning effects of the cytoplasm. Theoretical predictions are discussed together with simulations and experiments. The presentation is guided by the theory of phase transitions and critical phenomena, and the appendix summarizes the mathematical background in a concise way within the framework of the Ginzburg-Landau theory., Comment: Review, 217 references, to appear in BBA-biomembranes

We discuss in detail a recently proposed hybrid particle-continuum scheme for complex fluids and evaluate it at the example of a confined homopolymer solution in slit geometry. The hybrid scheme treats polymer chains near the impenetrable walls as particles keeping the configuration details, and chains in the bulk region as continuous density fields. Polymers can switch resolutions on the fly, controlled by an inhomogeneous tuning function. By properly choosing the tuning function, the representation of the system can be adjusted to reach an optimal balance between physical accuracy and computational efficiency. The hybrid simulation reproduces the results of a reference particle simulation and is significantly faster (about a factor of 3.5 in our application example).

Exact values for bulk and shear viscosity are important to characterize a fluid and they are a necessary input for a continuum description. Here we present two novel methods to compute bulk viscosities by non-equilibrium molecular dynamics (NEMD) simulations of steady-state systems with periodic boundary conditions -- one based on frequent particle displacements and one based on the application of external bulk forces with an inhomogeneous force profile. In equilibrium simulations, viscosities can be determined from the stress tensor fluctuations via Green-Kubo relations; however, the correct incorporation of random and dissipative forces is not obvious. We discuss different expressions proposed in the literature and test them at the example of a dissipative particle dynamics (DPD) fluid., Comment: 8 pages, 7 figures. The following article has been accepted by Journal of Chemical Physics. After it is published, it will be found at http://scitation.aip.org/content/aip/journal/jcp

We study the complex formation between one long polyanion chain and many short oligocation chains by computer simulations. We employ a coarse-grained bead-spring model for the polyelectrolyte chains, and model explicitly the small salt ions. We systematically vary the concentration and the length of the oligocation, and examine how the oligocations affects the chain conformation, the static structure factor, the radial and axial distribution of various charged species, and the number of bound ions in the complex. At low oligocation concentration, the polyanion has an extended structure. Upon increasing the oligocation concentration, the polyanion chain collapses and forms a compact globule, but the complex still carries a net negative charge. Once the total charge of the oligocations is equal to that of the polyanion, the collapse stops and is replaced by a slow expansion. In this regime, the net charge on the complexes is positive or neutral, depending on the microion concentration in solution. The expansion can be explained by the reduction of the oligocation bridging. We find that the behavior and the structure of the complex are largely independent of the length of oligocations, and very similar to that observed when replacing the oligocations by multivalent salt cations, and conclude that the main driving force keeping the complex together is the release of monovalent counterions and coions. We speculate on the implications of this finding for the problem of controlled oligolyte release and oligolyte substitution., Comment: 13 pages, 11 figures, submitted to J. Chem. Phys

We study a generic model for quorum-sensing bacteria in circular confinement. Every bacterium produces signaling molecules, the local concentration of which triggers a response when a certain threshold is reached. If this response lowers the motility then an aggregation of bacteria occurs, which differs fundamentally from standard motility-induced phase separation due to the long-ranged nature of the concentration of signal molecules. We analyze this phenomenon analytically and by numerical simulations employing two different protocols leading to stationary cluster and ring morphologies, respectively., Comment: to appear in Phys. Rev. Lett

The reaction of $AB_m$ monomers (m=2,3) with a multifunctional B_f-type polymer chain ("hypergrafting") is studied by coarse-grained molecular dynamics simulations. The $AB_m$ monomers are hypergrafted using the slow monomer addition strategy. Fully dendronized, i.e., perfectly branched polymers are also simulated for comparison. The degree of branching DB of the molecules obtained with the "hypergrafting" process critically depends on the rate with which monomers attach to inner monomers compared to terminal monomers. This ratio is more favorable if the $AB_m$ monomers have lower reactivity, since the free monomers then have time to diffuse inside the chain. Configurational chain properties are also determined, showing that the stretching of the polymer backbone as a consequence of the "hypergrafting" procedure is much less pronounced than for perfectly dendronized chains. Furthermore, we analyze the scaling of various quantities with molecular weight M for large M (M>100). The Wiener index scales as $M^2.3$, which is intermediate between linear chains ($M^3$) and perfectly branched polymers ($M^2 \ln(M)$). The polymer size, characterized by the radius of gyration $R_g$ or the hydrodynamic radius $R_h$, is found to scale as $R_{g,h}~M^{\nu}$ with $\nu~0.38$, which lies between the exponent of diffusion limited aggregation ($\nu=0.4$) and the mean-field exponent predicted by Konkolewicz and coworkers ($\nu=0.33$)., Comment: minor typos corrected, to appear in The Journal of Chemical Physics