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Block copolymer self-assembly in conjunction with nonsolvent-induced phase separation (SNIPS) has been increasingly leveraged to fabricate integral-asymmetric membranes. The large number of formulation and processing parameters associated with SNIPS, however, has prevented the reliable construction of high performance membranes. In this study, we apply dynamical self-consistent field theory to model the SNIPS process and investigate the effect of various parameters on the membrane morphology: solvent selectivity, nonsolvent selectivity, initial film composition, and glass transition composition. We examine how solvent selectivity and concentration of polymers in the film impact the structure of micelles that connect to form the membrane matrix. In particular, we find that preserving the order in the surface layer and forming a connection between the supporting and surface layer are nontrivial and sensitive to each parameter studied. The effect of each parameter is discussed, and suggestions are made for successfully fabricating viable block copolymer membranes. [ABSTRACT FROM AUTHOR]

The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically. [ABSTRACT FROM AUTHOR]

Using phase-field simulations, we investigate the bulk coarsening dynamics of ternary polymer solutions undergoing a glass transition for two models of phase separation: diffusion only and with hydrodynamics. The glass transition is incorporated in both models by imposing mobility and viscosity contrasts between the polymer-rich and polymer-poor phases of the evolving microstructure. For microstructures composed of polymer-poor clusters in a polymer-rich matrix, the mobility and viscosity contrasts significantly hinder coarsening, effectively leading to structural arrest. For microstructures composed of polymer-rich clusters in a polymer-poor matrix, the mobility and viscosity contrasts do not impede domain growth; rather, they change the transient concentration of the polymer-rich phase, altering the shape of the discrete domains. This effect introduces several complexities to the coarsening process, including percolation inversion of the polymer-rich and polymer-poor phases—a phenomenon normally attributed to viscoelastic phase separation. [ABSTRACT FROM AUTHOR]

Field-theoretic simulations are numerical treatments of polymer field theory models that go beyond the mean-field self-consistent field theory level and have successfully captured a range of mesoscopic phenomena. Inherent in molecularly-based field theories is a "sign problem" associated with complex-valued Hamiltonian functionals. One route to field-theoretic simulations utilizes the complex Langevin (CL) method to importance sample complex-valued field configurations to bypass the sign problem. Although CL is exact in principle, it can be difficult to stabilize in strongly fluctuating systems. An alternate approach for blends or block copolymers with two segment species is to make a "partial saddle point approximation" (PSPA) in which the stiff pressure-like field is constrained to its mean-field value, eliminating the sign problem in the remaining field theory, allowing for traditional (real) sampling methods. The consequences of the PSPA are relatively unknown, and direct comparisons between the two methods are limited. Here, we quantitatively compare thermodynamic observables, order-disorder transitions, and periodic domain sizes predicted by the two approaches for a weakly compressible model of AB diblock copolymers. Using Gaussian fluctuation analysis, we validate our simulation observations, finding that the PSPA incorrectly captures trends in fluctuation corrections to certain thermodynamic observables, microdomain spacing, and location of order-disorder transitions. For incompressible models with contact interactions, we find similar discrepancies between the predictions of CL and PSPA, but these can be minimized by regularization procedures such as Morse calibration. These findings mandate caution in applying the PSPA to broader classes of soft-matter models and systems. [ABSTRACT FROM AUTHOR]

A computational framework that leverages data from self-consistent field theory simulations with deep learning to accelerate the exploration of parameter space for block copolymers is presented. This is a substantial two-dimensional extension of the framework introduced in the work of Xuan et al. [J. Comput. Phys. 443, 110519 (2021)]. Several innovations and improvements are proposed. (1) A Sobolev space-trained, convolutional neural network is employed to handle the exponential dimension increase of the discretized, local average monomer density fields and to strongly enforce both spatial translation and rotation invariance of the predicted, field-theoretic intensive Hamiltonian. (2) A generative adversarial network (GAN) is introduced to efficiently and accurately predict saddle point, local average monomer density fields without resorting to gradient descent methods that employ the training set. This GAN approach yields important savings of both memory and computational cost. (3) The proposed machine learning framework is successfully applied to 2D cell size optimization as a clear illustration of its broad potential to accelerate the exploration of parameter space for discovering polymer nanostructures. Extensions to three-dimensional phase discovery appear to be feasible. [ABSTRACT FROM AUTHOR]

We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent field theory (SCFT) to predict the structure of the self-assembled, solvated membrane and on-lattice kinetic Monte Carlo (kMC) simulations to model diffusion of solutes. Solvation is simulated in SCFT by constraining the glassy membrane matrix while relaxing the brush-like membrane pore coating against the solvent. The kMC simulations capture the resulting solute spatial distribution and concentration-dependent local diffusivity in the polymer-coated pores; we parameterize the latter using particle-based simulations. We apply our approach to simulate solute diffusion through nonequilibrium morphologies of a model triblock copolymer, and we correlate diffusivity with structural descriptors of the morphologies. We also compare the model's predictions to alternative approaches based on simple lattice random walks and find our multiscale model to be more robust and systematic to parameterize. Our multiscale modeling approach is general and can be readily extended in the future to other chemistries, morphologies, and models for the local solute diffusivity and interactions with the membrane. [ABSTRACT FROM AUTHOR]

Polymer-mediated colloidal interactions control the stability and phase properties of colloid–polymer mixtures that are critical for a wide range of important applications. In this work, we develop a versatile self-consistent field theory (SCFT) approach to study this type of interaction based on a continuum confined polymer solution model with explicit solvent and confining walls. The model is formulated in the grand canonical ensemble, and the potential of mean force for the polymer-mediated interaction is computed from grand potentials. We focus on the case of non-adsorbing linear polymers and present a systematic investigation on depletion effects using SCFT. The properties of confined polymer solutions are probed, and mean-field profiles of induced interactions are shown across different physical regimes. We expose a detailed parametric dependence of the interaction, concerning both attractive and repulsive parts, on polymer concentration, chain length, and solvent quality and explore the effect of wall surface roughness, demonstrating the versatility of the proposed approach. Our findings show good agreement with previous numerical studies and experiments, yet extend prior work to new regimes. Moreover, the mechanisms of depletion attraction and repulsion, along with the influence of individual control factors, are further discussed. We anticipate that this study will provide useful insights into depletion forces and can be readily extended to examine more complex colloid–polymer mixtures. [ABSTRACT FROM AUTHOR]

Achieving thermodynamic faithfulness and transferability across state points is an outstanding challenge in the bottom-up coarse graining of molecular models, with many efforts focusing on augmenting the form of coarse-grained interaction potentials to improve transferability. Here, we revisit the critical role of the simulation ensemble and the possibility that even simple models can be made more predictive through a smarter choice of ensemble. We highlight the efficacy of coarse graining from ensembles where variables conjugate to the thermodynamic quantities of interest are forced to respond to applied perturbations. For example, to learn activity coefficients, it is natural to coarse grain from ensembles with spatially varying external potentials applied to one species to force local composition variations and fluctuations. We apply this strategy to coarse grain both an atomistic model of water and methanol and a binary mixture of spheres interacting via Gaussian repulsions and demonstrate near-quantitative capture of activity coefficients across the whole composition range. Furthermore, the approach is able to do so without explicitly measuring and targeting activity coefficients during the coarse graining process; activity coefficients are only computed after-the-fact to assess accuracy. We hypothesize that ensembles with applied thermodynamic potentials are more "thermodynamically informative." We quantify this notion of informativeness using the Fisher information metric, which enables the systematic design of optimal bias potentials that promote the learning of thermodynamically faithful models. The Fisher information is related to variances of structural variables, highlighting the physical basis underlying the Fisher information's utility in improving coarse-grained models. [ABSTRACT FROM AUTHOR]

We consider the phase stability of binary fluid mixtures with constituents of contrasting dielectric properties in the presence of a static applied electric field, E0. The dielectric fluid is modeled using a recently developed field-theoretic representation for the equilibrium behavior of a system of polarizable molecular species [J. M. Martin et al., J. Chem. Phys. 145, 154104 (2016)]. The dielectric displacement of the fluid, D, is obtained from a direct E0 derivative of the fluid's free energy, illuminating coupled structural and electrostatic fluctuations that manifest in the dielectric properties of the fluid. Linearizing D with respect to E0 yields an explicit, molecularly based expression for the dielectric constant of the fluid mixture, ϵ, through the relation D = ϵE0. In the linear response regime, the composition dependence of ϵ completely specifies the applied field-dependent contribution to the fluid's miscibility, which we enumerate as a contribution χE to a Flory interaction parameter. Using a Gaussian approximation to the field theory, we obtain an expression for χE that relates structural and electrostatic contrast between dissimilar molecules to miscibility in the presence of an applied field. Specifically, contrast between wavevector-dependent, single-molecule correlation functions, Λ ^ A / B (k) , emerges as a necessary ingredient for electric field-induced mixing, corresponding to χE < 0. The character of χE is considered in three classes of binary systems: a binary simple fluid, a homopolymer blend, and a homopolymer solution. Within each system, the form for Λ ^ A / B accounts for molecular architecture effects, such as chain connectivity. Our findings elucidate the conditions for which one should expect electric field induced mixing or demixing for each class of mixture. [ABSTRACT FROM AUTHOR]

Bottlebrushes are an emerging class of polymers, characterized by a high density of side chains grafted to a linear backbone that offer promise in creating materials with unusual combinations of mechanical, chemical, and optoelectronic properties. Understanding the role of molecular architecture in the organization and assembly of bottlebrushes is of fundamental importance in polymer physics, but also enabling in applications. Here, we apply field-theoretic simulations to study the effect of grafting density, backbone length, and side-chain (SC) length on the structure and thermodynamics of bottlebrush homopolymer melts. Our results provide evidence for a phase transition from an isotropic to a nematic state with increasing grafting density and side-chain length. Variation in the backbone length is also observed to influence the location of the transition, primarily for short polymers just above the star to bottlebrush transition. [ABSTRACT FROM AUTHOR]

Self-coacervation is a phenomenon in which a solution of polyampholytes spontaneously phase separates into a dense liquid coacervate phase, rich in the polyampholyte, coexisting with a dilute supernatant phase. Such coacervation results in the formation of membraneless organelles in vivo and has further been applied industrially as synthetic encapsulants and coatings. It has been suggested that coacervation is primarily driven by the entropy gain from releasing counter-ions upon complexation. Using fully fluctuating field-theoretic simulations employing complex Langevin sampling and complementary molecular dynamics simulations, we have determined that the small ions contribute only weakly to the self-coacervation behavior of charge-symmetric block polyampholytes in solution. Salt partitioning between the supernatant and coacervate is also found to be negligible in the weak-binding regime at low electrostatic strengths. Asymmetries in charge distribution along the polyampholytes can cause net-charges that lead to "tadpole" configurations in dilute solution and the suppression of phase separation at low salt content. The field and particle-based simulation results are compared with analytical predictions from the random phase approximation (RPA) and postulated scaling relationships. The qualitative trends are mostly captured by the RPA, but the approximation fails at low concentration. [ABSTRACT FROM AUTHOR]

We derive the effective Flory-Huggins parameter in polarizable polymeric systems, within a recently introduced polarizable field theory framework. The incorporation of bead polarizabilities in the model self-consistently embeds dielectric response, as well as van der Waals interactions. The latter generate a χ parameter (denoted χ ̃ ) between any two species with polarizability contrast. Using one-loop perturbation theory, we compute corrections to the structure factor S k and the dielectric function ϵ ^ ( k ) for a polarizable binary homopolymer blend in the one-phase region of the phase diagram. The electrostatic corrections to S(k) can be entirely accounted for by a renormalization of the excluded volume parameter B into three van der Waals-corrected parameters BAA, BAB, and BBB, which then determine χ ̃ . The one-loop theory not only enables the quantitative prediction of χ ̃ but also provides useful insight into the dependence of χ ̃ on the electrostatic environment (for example, its sensitivity to electrostatic screening). The unapproximated polarizable field theory is amenable to direct simulation via complex Langevin sampling, which we employ here to test the validity of the one-loop results. From simulations of S(k) and ϵ ^ ( k ) for a system of polarizable homopolymers, we find that the one-loop theory is best suited to high concentrations, where it performs very well. Finally, we measure χ ̃ N in simulations of a polarizable diblock copolymer melt and obtain excellent agreement with the one-loop theory. These constitute the first fully fluctuating simulations conducted within the polarizable field theory framework. [ABSTRACT FROM AUTHOR]

In 1970, Edwards and Freed presented an elegant representation of interacting branched polymers that resembles the coherent states (CS) formulation of second-quantized field theory. This CS polymer field theory has been largely overlooked during the intervening period in favor of more conventional “auxiliary field” (AF) interacting polymer representations that form the basis of modern self-consistent field theory (SCFT) and field-theoretic simulation approaches. Here we argue that the CS representation provides a simpler and computationally more efficient framework than the AF approach for broad classes of reversibly bonding polymers encountered in supramolecular polymer science. The CS formalism is reviewed, initially for a simple homopolymer solution, and then extended to supramolecular polymers capable of forming reversible linkages and networks. In the context of the Edwards model of a non-reacting homopolymer solution and one and two-component models of telechelic reacting polymers, we discuss the structure of CS mean-field theory, including the equivalence to SCFT, and show how weak-amplitude expansions (random phase approximations) can be readily developed without explicit enumeration of all reaction products in a mixture. We further illustrate how to analyze CS field theories beyond SCFT at the level of Gaussian field fluctuations and provide a perspective on direct numerical simulations using a recently developed complex Langevin technique. [ABSTRACT FROM AUTHOR]

We present a new molecularly informed statistical field theory model of inhomogeneous polarizable soft matter. The model is based on fluid elements, referred to as beads, that can carry a net monopole of charge at their center of mass and a fixed or induced dipole through a Drude-type distributed charge approach. The beads are thus polarizable and naturally manifest attractive van der Waals interactions. Beyond electrostatic interactions, beads can be given soft repulsions to sustain fluid phases at arbitrary densities. Beads of different types can be mixed or linked into polymers with arbitrary chain models and sequences of charged and uncharged beads. By such an approach, it is possible to construct models suitable for describing a vast range of soft-matter systems including electrolyte and polyelectrolyte solutions, ionic liquids, polymerized ionic liquids, polymer blends, ionomers, and block copolymers, among others. These bead models can be constructed in virtually any ensemble and converted to complex-valued statistical field theories by Hubbard-Stratonovich transforms. One of the fields entering the resulting theories is a fluctuating electrostatic potential; other fields are necessary to decouple non-electrostatic interactions. We elucidate the structure of these field theories, their consistency with macroscopic electrostatic theory in the absence and presence of external electric fields, and the way in which they embed van der Waals interactions and non-uniform dielectric properties. Their suitability as a framework for computational studies of heterogeneous soft matter systems using field-theoretic simulation techniques is discussed. [ABSTRACT FROM AUTHOR]

The string method is a useful numerical technique for resolving minimum energy paths in rare-event barrier-crossing problems. However, when applied to systems with relatively small energy barriers, the string method becomes inconvenient since many images trace out physically uninteresting regions where the barrier has already been crossed and recrossing is unlikely. Energy weighting alleviates this difficulty to an extent, but typical implementations still require the string's endpoints to evolve to stable states that may be far from the barrier, and deciding upon a suitable energy weighting scheme can be an iterative process dependent on both the application and the number of images used. A second difficulty arises when treating nucleation problems: for later images along the string, the nucleus grows to fill the computational domain. These later images are unphysical due to confinement effects and must be discarded. In both cases, computational resources associated with unphysical or uninteresting images are wasted. We present a new energy weighting scheme that eliminates all of the above difficulties by actively truncating the string as it evolves and forcing all images, including the endpoints, to remain within and cover uniformly a desired barrier region. The calculation can proceed in one step without iterating on strategy, requiring only an estimate of an energy value below which images become uninteresting. [ABSTRACT FROM AUTHOR]

Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical sim-ulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density op-erators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complex Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theo-ries of the species type. Here, we introduce an extension of the exchange model to an arbitrary num-ber of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simu-lations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites. [ABSTRACT FROM AUTHOR]

We introduce a stable and efficient complex Langevin (CL) scheme to enable the first direct numerical simulations of the coherent-states (CS) formulation of polymer field theory. In contrast with Edwards' well-known auxiliary-field (AF) framework, the CS formulation does not contain an embedded nonlinear, non-local, implicit functional of the auxiliary fields, and the action of the field theory has a fully explicit, semi-local, and finite-order polynomial character. In the context of a polymer solution model, we demonstrate that the new CS-CL dynamical scheme for sampling fluctuations in the space of coherent states yields results in good agreement with now-standard AF-CL simulations. The formalism is potentially applicable to a broad range of polymer architectures and may facilitate systematic generation of trial actions for use in coarse-graining and numerical renormalization-group studies. [ABSTRACT FROM AUTHOR]

Using the zero-temperature string method, we investigate nucleation of a stable lamellar phase from a metastable disordered phase of the renormalized Landau-Brazovskii model at parameters explicitly connected to those of an experimentally accessible diblock copolymer melt. We find anisotropic critical nuclei in qualitative agreement with previous experimental and analytic predictions; we also find good quantitative agreement with the predictions of a single-mode analysis. We conduct a thorough search for critical nuclei containing various predicted and experimentally observed defect structures. The predictions of the renormalized model are assessed by simulating the bare Landau-Brazovskii model with fluctuations. We find that the renormalized model makes reasonable predictions for several important quantities, including the order-disorder transition (ODT). However, the critical nucleus size depends sharply on proximity to the ODT, so even small errors in the ODT predicted by the renormalized model lead to large errors in the predicted critical nucleus size. We conclude that the renormalized model is a poor tool to study nucleation in the fluctuating Landau-Brazovskii model, and recommend that future studies work with the fluctuating bare model directly, using well-chosen collective variables to investigate kinetic pathways in the disorder → lamellar transition. [ABSTRACT FROM AUTHOR]

The complexation of mixtures of cationic and anionic polymers to produce complex-coacervate phases is a subject of fundamental importance to colloid and polymer science as well as to applications including drug delivery, sensing technologies, and bio-inspired adhesives. Unfortunately the theoretical underpinnings of complex coacervation are widely misunderstood and conceptual mistakes have propagated in the literature. Here, a simple symmetric polyelectrolyte mixture model in the absence of salt is used to discuss the salient features of the phase diagram, including the location of the critical point, binodals, and spinodals. It is argued that charge compensation by dimerization in the dilute region renders the phase diagram of an oppositely charged polyelectrolyte mixture qualitatively and quantitatively similar to that of a single-component symmetric diblock polyampholyte solution, a system capable of "self-coacervation." The theoretical predictions are verified using fully fluctuating field-theoretic simulations for corresponding polyelectrolyte and diblock polyampholyte models. These represent the first comprehensive, approximation-free phase diagrams for coacervate and self-coacervate systems to appear in the literature.

We introduce a stable and efficient complex Langevin (CL) scheme to enable the first direct numerical simulations of the coherent-states (CS) formulation of polymer field theory. In contrast with Edwards' well-known auxiliary-field (AF) framework, the CS formulation does not contain an embedded nonlinear, non-local, implicit functional of the auxiliary fields, and the action of the field theory has a fully explicit, semi-local, and finite-order polynomial character. In the context of a polymer solution model, we demonstrate that the new CS-CL dynamical scheme for sampling fluctuations in the space of coherent states yields results in good agreement with now-standard AF-CL simulations. The formalism is potentially applicable to a broad range of polymer architectures and may facilitate systematic generation of trial actions for use in coarse-graining and numerical renormalization-group studies.