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The complex physics of glass-forming systems is controlled by the structure of the low-energy portions of their potential energy landscapes. Here we report that a modified metadynamics algorithm efficiently explores and samples low-energy regions of such high-dimensional landscapes. In the energy landscape for a model foam, our algorithm finds and descends meandering canyons in the landscape, which contain dense clusters of energy minima along their floors. Similar canyon structures in the energy landscapes of two model glass formers-hard sphere fluids and the Kob-Andersen glass-allow us to reach high densities and low energies, respectively. In the hard sphere system, fluid configurations are found to form continuous regions that cover the canyon floors up to densities well above the jamming transition. For the Kob-Andersen glass former, our technique samples low-energy states with modest computational effort, with the lowest energies found approaching the predicted Kauzmann limit.
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Advances in polymer chemistry over the last decade have enabled the synthesis of molecularly precise polymer networks that exhibit homogeneous structure. These precise polymer gels create the opportunity to establish true multiscale, molecular to macroscopic, relationships that define their elastic and failure properties. In this work, a theory of network fracture that accounts for loop defects is developed by drawing on recent advances in network elasticity. This loop-modified Lake-Thomas theory is tested against both molecular dynamics (MD) simulations and experimental fracture measurements on model gels, and good agreement between theory, which does not use an enhancement factor, and measurement is observed. Insight into the local and global contributions to energy dissipated during network failure and their relation to the bond dissociation energy is also provided. These findings enable a priori estimates of fracture energy in swollen gels where chain scission becomes an important failure mechanism.
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Inhomogeneous crosslinked polymers are powerful platforms for materials design, because they can be synthesized from materials that provide complimentary properties to the resulting gel. For example, a membrane with both glassy and rubbery domains will be mechanically robust while enabling transport. The dynamics, and mechanical and failure properties of rubbery/glassy conetworks are only beginning to be studied, and there is likely to be strong heterogeneities in the dynamics and mechanical response. In this study, we use coarse-grained molecular dynamics simulations to generate microphase separated rubbery/glassy polymer networks with a bicontinuous morphology via in silico crosslinking. We study the effect of phase boundary on the local mobility gradient, and our simulation results reveal an asymmetric shift in the local mobility gradient across the interface that extends deeper into the phase with a lower Tg when the system temperature is between the glass transition temperatures of the two phases. Moreover, by employing a model that allows bond breaking, we examine the microscopic mechanism for failure in these networks as a function of the molecular weight of polymer strands between crosslinks and the number fraction of the glassy domain. Under uniaxial extension, we find that the stress is initially larger in the glassy domain. As the deformation proceeds, the segmental dynamics of the two phases homogenize, and subsequently bond breaking begins.
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Understanding the dynamics of polymers in confined environments is pivotal for diverse applications ranging from polymer upcycling to bioseparations. In this study, we develop an entropic barrier model using self-consistent field theory that considers the effect of attractive surface interactions, solvation, and confinement on polymer kinetics. In this model, we consider the translocation of a polymer from one cavity into a second cavity through a single-segment-width nanopore. We find that, for a polymer in a good solvent (i.e., excluded volume, u0 > 0), there is a nonmonotonic dependence of mean translocation time (τ) on surface interaction strength, É. At low É, excluded volume interactions lead to an energetic penalty and longer translocation times. As É increases, the surface interactions counteract the energetic penalty imposed by excluded volume and the polymer translocates faster through the nanopore. However, as É continues to increase, an adsorption transition occurs, which leads to significantly slower kinetics due to the penalty of desorption from the first cavity. The É at which this adsorption transition occurs is a function of the excluded volume, with higher u0 leading to an adsorption transition at higher É. Finally, we consider the effect of translocation across different size cavities. We find that the kinetics for translocation into a smaller cavity speeds up while translocation to a larger cavity slows down with increasing É due to higher surface contact under stronger confinement.
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Polymer infiltrated nanoporous gold is prepared by infiltrating polymer melts into a bicontinuous, nanoporous gold (NPG) scaffold. Polystyrene (PS) films with molecular weights (Mw) from 424 to 1133 kDa are infiltrated into a NPG scaffold (â¼120 nm), with a pore radius (Rp) and pore volume fraction of 37.5 nm and 50%, respectively. The confinement ratios (Γ=RgRp) range from 0.47 to 0.77, suggesting that the polymers inside the pores are moderately confined. The time for PS to achieve 80% infiltration (τ80%) is determined using in situ spectroscopic ellipsometry at 150 °C. The kinetics of infiltration scales weaker with Mw, τ80%âMw1.30±0.20, than expected from bulk viscosity Mw3.4. Furthermore, the effective viscosity of the PS melt inside NPG, inferred from the Lucas-Washburn model, is reduced by more than one order of magnitude compared to the bulk. Molecular dynamics simulation results are in good agreement with experiments predicting scaling as Mw1.4. The reduced dependence of Mw and the enhanced kinetics of infiltration are attributed to a reduction in chain entanglement density during infiltration and a reduction in polymer-wall friction with increasing polymer molecular weight. Compared to the traditional approach involving adding discrete particles into the polymer matrix, these studies show that nanocomposites with higher loading can be readily prepared, and that kinetics of infiltration are faster due to polymer confinement inside pores. These films have potential as actuators when filled with stimuli-responsive polymers as well as polymer electrolyte and fuel cell membranes.
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Coacervation of charged polymer chains has been a topic of major interest in both polymer and biological sciences, as it is a subset of a phenomenon called liquid-liquid phase separation (LLPS). In this process the polymer-rich phase separates from the polymer-lean supernatant while still maintaining its liquid-like properties. LLPS has been shown to play a crucial role in cellular homeostasis by driving the formation of membraneless organelles. It also has the potential to be harnessed to aid in novel therapeutical applications. Recent studies have demonstrated that there is no one simple mechanism which drives LLPS, which is instead a result of the combined effect of electrostatic, dipolar, hydrophobic, and other weak interactions. Using coarse-grained polymer simulations we investigate the relatively unexplored effects of monomer polarizability and spatially varying dielectric constant on LLPS propensity, and these factors affect the properties of the resulting condensates. In order to produce spatial variations in the dielectric constant, all our simulations include explicit solvent and counterions. We demonstrate that polarizability has only a minor effect on the bulk behaviour of the condensates but plays a major role when ion partitioning and microstructure are considered. We observe that the major contribution comes from the nature of the neutral blocks as endowing them with an induced dipole changes their character from hydrophobic to hydrophilic. We hypothesize that the results of this work can aid in guiding future studies concerned with LLPS by providing a general framework and by highlighting important factors which influence LLPS.
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While recent efforts have shown how local structure plays an essential role in the dynamic heterogeneity of homogeneous glass-forming materials, systems containing interfaces such as thin films or composite materials remain poorly understood. It is known that interfaces perturb the molecular packing nearby, however, numerous studies show the dynamics are modified over a much larger range. Here, we examine the dynamics in polymer nanocomposites (PNCs) using a combination of simulations and experiments and quantitatively separate the role of polymer packing from other effects on the dynamics, as a function of distance from the nanoparticle surfaces. After showing good qualitative agreement between the simulations and experiments in glassy structure and creep compliance, we use a machine-learned structure indicator, softness, to decompose polymer dynamics in our simulated PNCs into structure-dependent and structure-independent processes. With this decomposition, the free energy barrier for polymer rearrangement can be described as a combination of packing-dependent and packing-independent barriers. We find both barriers are higher near nanoparticles and decrease with applied stress, quantitatively demonstrating that the slow interfacial dynamics is not solely due to polymer packing differences, but also the change of structure-dynamics relationships. Finally, we present how this decomposition can be used to accurately predict strain-time creep curves for PNCs from their static configuration, providing additional insights into the effects of polymer-nanoparticle interfaces on creep suppression in PNCs.
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Many soft and biological materials display so-called 'soft glassy' dynamics; their constituents undergo anomalous random motions and complex cooperative rearrangements. A recent simulation model of one soft glassy material, a coarsening foam, suggested that the random motions of its bubbles are due to the system configuration moving over a fractal energy landscape in high-dimensional space. Here we show that the salient geometrical features of such high-dimensional fractal landscapes can be explored and reliably quantified, using empirical trajectory data from many degrees of freedom, in a model-free manner. For a mayonnaise-like dense emulsion, analysis of the observed trajectories of oil droplets quantitatively reproduces the high-dimensional fractal geometry of the configuration path and its associated local energy minima generated using a computational model. That geometry in turn drives the droplets' complex random motion observed in real space. Our results indicate that experimental studies can elucidate whether the similar dynamics in different soft and biological materials may also be due to fractal landscape dynamics.
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We explore the relationship between a machine-learned structural quantity (softness) and excess entropy in simulations of supercooled liquids. Excess entropy is known to scale well the dynamical properties of liquids, but this quasi-universal scaling is known to breakdown in supercooled and glassy regimes. Using numerical simulations, we test whether a local form of the excess entropy can lead to predictions similar to those made by softness, such as the strong correlation with particles' tendency to rearrange. In addition, we explore leveraging softness to compute excess entropy in the traditional fashion over softness groupings. Our results show that the excess entropy computed over softness-binned groupings is correlated with activation barriers to rearrangement.
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In this paper, we announce the public release of a massively parallel, graphics processing unit (GPU)-accelerated software, which is the first to combine both coarse-grained particle simulations and field-theoretic simulations in one simulation package. MATILDA.FT (Mesoscale, Accelerated, Theoretically Informed, Langevin, Dissipative particle dynamics, and Field Theory) was designed from the ground-up to run on CUDA-enabled GPUs with Thrust library acceleration, enabling it to harness the possibility of massive parallelism to efficiently simulate systems on a mesoscopic scale. It has been used to model a variety of systems, from polymer solutions and nanoparticle-polymer interfaces to coarse-grained peptide models and liquid crystals. MATILDA.FT is written in CUDA/C++ and is object oriented, making its source-code easy to understand and extend. Here, we present an overview of the currently available features, and the logic of parallel algorithms and methods. We provide the necessary theoretical background and present examples of systems simulated using MATILDA.FT as the simulation engine. The source code, along with the documentation, additional tools, and examples, can be found on the GitHub MATILDA.FT repository.
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After more than two decades of study, many fundamental questions remain unanswered about the dynamics of glass-forming materials confined to thin films. Experiments and simulations indicate that free interfaces enhance dynamics over length scales larger than molecular sizes, and this effect strengthens at lower temperatures. The nature of the influence of interfaces, however, remains a point of significant debate. In this work, we explore the properties of the nonequilibrium phase transition in dynamics that occurs in trajectory space between high- and low-mobility basins in a set of model polymer freestanding films. In thick films, the film-averaged mobility transition is broader than the bulk mobility transition, while in thin films it is a variant of the bulk result shifted toward a higher bias. Plotting this transition's local coexistence points against the distance from the films' surface shows thick films have surface and film-center transitions, while thin films practically have a single transition throughout the film. These observations are reminiscent of thermodynamic capillary condensation of a vapor-liquid phase between parallel plates, suggesting they constitute a demonstration of such an effect in a trajectory phase transition in the dynamics of a structural glass former. Moreover, this transition bears similarities to several experiments exhibiting anomalous behavior in the glass transition upon reducing film thickness below a material-dependent onset, including the broadening of the glass transition and the homogenization of surface and bulk glass transition temperatures.
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External stress can accelerate molecular mobility of amorphous solids by several orders of magnitude. The changes in mobility are commonly interpreted through the Eyring model, which invokes an empirical activation volume. Here, we analyze constant-stress molecular dynamics simulations and propose a structure-dependent Eyring model, connecting activation volume to a machine-learned field, softness. We show that stress has a heterogeneous effect on the mobility that depends on local structure through softness. The barrier impeding relaxation reduces more for well-packed particles, which explains the narrower distribution of relaxation time observed under stress.
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Stable glasses (SGs) are formed through surface-mediated equilibration (SME) during physical vapor deposition (PVD). Unlike intermolecular interactions, the role of intramolecular degrees of freedom in this process remains unexplored. Here, using experiments and coarse-grained molecular dynamics simulations, we demonstrate that varying dihedral rotation barriers of even a single bond, in otherwise isomeric molecules, can strongly influence the structure and stability of PVD glasses. These effects arise from variations in the degree of surface mobility, mobility gradients, and mobility anisotropy, at a given deposition temperature (Tdep). At high Tdep, flexible molecules have access to more configurations, which enhances the rate of SME, forming isotropic SGs. At low Tdep, stability is achieved by out of equilibrium aging of the surface layer. Here, the poor packing of rigid molecules enhances the rate of surface-mediated aging, producing stable glasses with layered structures in a broad range of Tdep. In contrast, the dynamics of flexible molecules couple more efficiently to the glass layers underneath, resulting in reduced mobility and weaker mobility gradients, producing unstable glasses. Independent of stability, the flattened shape of flexible molecules can also promote in-plane orientational order at low Tdep. These results indicate that small changes in intramolecular relaxation barriers can be used as an approach to independently tune the structure and mobility profiles of the surface layer and, thus, the stability and structure of PVD glasses.
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Glasses formed by physical vapor deposition (PVD) are an interesting new class of materials, exhibiting properties thought to be equivalent to those of glasses aged for thousands of years. Exerting control over the structure and properties of PVD glasses formed with different types of glass-forming molecules is now an emerging challenge. In this work, we study coarse-grained models of organic glass formers containing fluorocarbon tails of increasing length, corresponding to an increased tendency to form microstructures. We use simulated PVD to examine how the presence of the microphase-separated domains in the supercooled liquid influences the ability to form stable glasses. This model suggests that increasing molecule tail length results in decreased thermodynamic stability of the molecules in PVD films. The reduced stability is further linked to the reduced ability of these molecules to equilibrate at the free surface during PVD. We find that, as the tail length is increased, the relaxation times near the surface of the supercooled equilibrium liquid films of these molecules are slowed and become essentially bulk-like, due to the segregation of the fluorocarbon tails to the free surface. Surface diffusion is also markedly reduced due to clustering of the molecules at the surface. Based on these results, we propose a trapping mechanism where tails are unable to move between local phase-separated domains on the relevant deposition time scales.
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In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface-fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. We find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface-fluid interactions; however, a threshold value of surface-fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface-polymer interaction relative to the surface-solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface-fluid interactions, although polymers desorb more quickly from highly curved surfaces.
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Polymer nanocomposites (PNCs), a class of composites consisting of typically inorganic nanoparticles (NPs) embedded in a polymer matrix, have become an emerging class of materials due to their significant potential to combine the functionality of NPs with the toughness of polymers. However, many applications are limited by their mechanical properties, and a fundamental understanding of NPs' effect on the nonlinear mechanical properties is lacking. In this study, we used molecular dynamics simulations to investigate the influence of NPs on the tendency of a polymer nanopillar to form a shear band. Even though we restrict ourselves to sufficiently low NP loadings that the elastic and yield behaviors are unaffected compared to the pure polymer, the polymer-NP interactions have a surprisingly strong effect on the location of a shear band in the sample. Different polymer-NP interactions have been used to explore their effect on the local structure of materials which is described using a recently developed machine-learned quantity, softness. Our calculations reveal a strong correlation between the strain localization pattern and the local structural signatures. Lastly, we show that weak interactions between NP and polymer matrix can form a soft region near the NP, and this leads to an attraction of the shear band to the NP surface.
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The self-assembly of gold nanorods (AuNRs) of different sizes with a block copolymer (BCP) is studied. Polystyrene-block-poly(2-vinylpyridine) (PS-b-P2VP) films containing P2VP functionalized AuNRs are solvent annealed resulting in a BCP morphology of vertical P2VP cylinders in a PS matrix. At the surface of the PS-b-P2VP films long AuNRs are found in the bridging and vertical states. The bridging state is where the long axis of the AuNR is parallel to the film surface, the AuNR is embedded in the film, and each end of the AuNR is at the top of nearest neighbor P2VP cylinders. The vertical state is where the AuNR is localized within a vertical P2VP cylinder, the AuNR long axis is perpendicular to the film surface and the upper tip of the AuNR is at the film surface. Short AuNRs were found in the bridging and vertical states as well as in a state not observed for the long AuNRs, the centered state. The centered state is where an AuNR has its long axis parallel to the film surface, is embedded in the film, and is centered over a vertical P2VP cylinder. Hybrid particle-field theory (HPFT) simulations modeling the experimental system predict that for the long AuNRs only the bridging state should be observed while for the short AuNRs only the bridging and centered states should be observed. Possible explanations for why the vertical state is observed in experiments despite being thermodynamically unfavorable in simulations are discussed. HPFT simulations also show that when a nanorod is in the bridging state the two cylinders it bridges remain intact and extend from the nanorod to the substrate. Further, the minority block of the BCP is shown to wet the bottom of the bridging nanorod. The bridging state is very promising for the future development of self-assembled nanoscale devices.
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The use of nanoparticle reinforced polymer matrices in continuous fiber composites for infrastructure applications requires a comprehensive understanding of viscoelastic creep. Critical parameters affecting the mechanical reinforcement offered by nanoparticles include nanoparticle size and concentration, as well as the interaction between the nanoparticle surface and polymer matrix. Here, we study the viscoelastic creep of nanocomposite systems comprised of glassy thermoplastic polymers and spherical silica nanoparticles of varying sizes and surface functionalization using a dynamic mechanical analysis (DMA) accelerated testing methodology. Significant differences in the nanoparticle dispersions in these nanocomposites were observed via transmission electron microscopy (TEM) and small-angle X-ray scattering (SAXS) and are attributed to differences in the polymer-polymer and polymer-particle interaction strengths. The DMA measurements indicate a decrease in compliance at short times with increased nanoparticle loading that is largely independent of nanoparticle dispersion morphology and polymer-particle interaction strength. Conversely, long term creep behavior shows a much stronger dependence on these parameters with the creep onset time increasing by up to three orders of magnitude. For similar nanoparticle loadings, the time to critical deformation in systems with well-distributed, networked nanoparticle morphologies was larger by an order of magnitude compared to systems exhibiting strong nanoparticle aggregation. The networked systems delayed the time to critical deformation by three orders of magnitude over that of neat polymer. The increase in time to critical deformation is also greater in composites with smaller nanoparticles at similar loadings, which we attribute to the development of percolated nanoparticle networks. These results demonstrate the significant effects polymer-particle interactions and dispersion morphologies can have on the long-term creep compliance of thermoplastic nanocomposites.
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Understanding the structure and dynamics of polymers under confinement has been of widespread interest, and one class of polymers that have received comparatively little attention under confinement is that of ring polymers. The properties of non-concatenated ring polymers can also be important in biological fields because ring polymers have been proven to be a good model to study DNA organization in the cell nucleus. From our previous study, linear polymers in a cylindrically confined polymer melt were found to segregate from each other as a result of the strong correlation hole effect that is enhanced by the confining surfaces. By comparison, our subsequent study of linear polymers in confined thin films at similar levels of confinements found only the onset of segregation. In this study, we use molecular dynamics simulation to investigate the chain conformations and dynamics of ring polymers under planar (1D) confinement as a function of film thickness. Our results show that conformations of ring polymers are similar to the linear polymers under planar confinement, except that ring polymers are less compressed in the direction normal to the walls. While we find that the correlation hole effect is enhanced under confinement, it is not as pronounced as the linear polymers under 2D confinement. Finally, we show that chain dynamics far above Tg are primarily affected by the friction from walls based on the monomeric friction coefficient we get from the Rouse mode analysis.
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Brittle failure is ubiquitous in amorphous materials that are sufficiently cooled below their glass transition temperature, Tg. This catastrophic failure mode is limiting for amorphous materials in many applications, and many fundamental questions surrounding it remain poorly understood. Two challenges that prevent a more fundamental understanding of the transition between a ductile response at temperatures near Tg to brittle failure at lower temperatures are (i) a lack of computationally inexpensive molecular models that capture the failure modes observed in experiments and (ii) the lack of quantitative metrics that can distinguish various failure mechanisms. In this work, we use molecular dynamics simulations to capture ductile-to-brittle transition in glass-forming oligomeric polymer systems where we systematically vary both the temperature relative to Tg and the form of the interaction potential to induce a variety of failure modes. We characterized the effects of this new potential on macroscopic mechanical properties as well as microscopic structural and dynamical response during deformation. Finally, we develop several quantitative metrics to distinguish between different failure modes, and we find that the transition between catastrophic brittle failure, necking, and homogeneous plastic flow is gradual as the temperature is increased.