Modeling of Polymer Structure and Conformations in Polymer Nanocomposites from Atomistic to Mesoscale: A Review

Structure, Properties, and Applications of Silica Nanoparticles: Recent Theoretical Modeling Advances, Challenges, and Future Directions

Silica nanoparticles (SNPs), one of the most widely researched materials in modern science, are now commonly exploited in surface coatings, biomedicine, catalysis, and engineering of novel self-assembling materials. Theoretical approaches are invaluable to enhancing fundamental understanding of SNP properties and behavior. Tremendous research attention is dedicated to modeling silica structure, the silica-water interface, and functionalization of silica surfaces for tailored applications. In this review, the range of theoretical methodologies are discussed that have been employed to model bare silica and functionalized silica. The evolution of silica modeling approaches is detailed, including classical, quantum mechanical, and hybrid methods and highlight in particular the last decade of theoretical simulation advances. It is started with discussing investigations of bare silica systems, focusing on the fundamental interactions at the silica-water interface, following with a comprehensively review of the modeling studies that examine the interaction of silica with functional ligands, peptides, ions, surfactants, polymers, and carbonaceous species. The review is concluded with the perspective on existing challenges in the field and promising future directions that will further enhance the utility and importance of the theoretical approaches in guiding the rational design of SNPs for applications in engineering and biomedicine.

MARTINI Coarse-Grained Force Field for Thermoplastic Starch Nanocomposites

Thermoplastic starch (TPS) is an excellent film-forming material, and the addition of fillers, such as tetramethylammonium-montmorillonite (TMA-MMT) clay, has significantly expanded its use in packaging applications. We first used an all-atom (AA) simulation to predict several macroscopic (Young's modulus, glass transition temperature, density) and microscopic (conformation along 1-4 and 1-6 glycosidic linkages, composite morphology) properties of TPS melt and TPS-TMA-MMT composite. The interplay of polymer-surface (weakly repulsive), plasticizer-surface (attractive), and polymer-plasticizer (weakly attractive) interactions leads to conformational and dynamics properties distinct from those in systems with either attractive or repulsive polymer-surface interactions. A subset of AA properties was used to parametrize the MARTINI-2 coarse-grained (CG) force field (FF) for the melt and composite systems. The missing bonded parameters of amylose and amylopectin and the bead types for 1-4 and 1-6 linked α-D glucose were determined using two-body excess entropy, density, and bond and angle distributions in the AA TPS melt. This new MARTINI-2 CG model was also compared with the MARTINI-3 model for the TPS melt. However, the requirement of a polarizable water model necessitates the use of MARTINI-2 FF for the composite system. This liquid-liquid partitioning-based FF shows freezing and compaction of polymer chains near the clay surface, further accentuated by lowering of dispersive interactions between pairs of high-covalent-coordination ring units of TPS polymers and the montmorillonite sheet. A rescaling of the effective dispersive component of TPS-MMT cross interactions was used to optimize the MARTINI-2 FF for the composite system with structural (chain size distribution), thermodynamic (chain conformational entropy and density), and dynamic (self-diffusion coefficient) properties obtained from long AA simulations forming the constraints for optimization. The obtained CG FF parameters provided excellent estimates for several other properties of the melt and composite systems not used in parameter estimation, thus establishing the robustness of the developed model.

Development of a coarse-grained molecular dynamics model for poly(dimethyl-co-diphenyl)siloxane

Polydimethylsiloxane is an important polymeric material with a wide range of applications. However, environmental effects like low temperature can induce crystallization in this material with resulting changes in its structural and dynamic properties. The incorporation of phenyl-siloxane components, e.g., as in a poly(dimethyl-co-diphenyl)siloxane random copolymer, is known to suppress such crystallization. Molecular dynamics (MD) simulations can be a powerful tool to understand such effects in atomistic detail. Unfortunately, all-atomistic molecular dynamics (AAMD) is limited in both spatial dimensions and simulation times it can probe. To overcome such constraints and to extend to more useful length- and time-scales, we systematically develop a coarse-grained molecular dynamics (CGMD) model for the poly(dimethyl-co-diphenyl)siloxane system with bonded and non-bonded interactions determined from all-atomistic simulations by the iterative Boltzmann inversion (IBI) method. Additionally, we propose a lever rule that can be useful to generate non-bonded potentials for such systems without reference to the all-atomistic ground truth. Our model captures the structural and dynamic properties of the copolymer material with quantitative accuracy and is useful to study long-time dynamics of highly-entangled systems, sequence-dependent properties, phase behaviour, etc.

Molecular Simulation of Covalent Adaptable Networks and Vitrimers: A Review

Covalent adaptable networks and vitrimers are novel polymers with dynamic reversible bond exchange reactions for crosslinks, enabling them to modulate their properties between those of thermoplastics and thermosets. They have been gathering interest as materials for their recycling and self-healing properties. In this review, we discuss different molecular simulation efforts that have been used over the last decade to investigate and understand the nanoscale and molecular behaviors of covalent adaptable networks and vitrimers. In particular, molecular dynamics, Monte Carlo, and a hybrid of molecular dynamics and Monte Carlo approaches have been used to model the dynamic bond exchange reaction, which is the main mechanism of interest since it controls both the mechanical and rheological behaviors. The molecular simulation techniques presented yield sufficient results to investigate the structure and dynamics as well as the mechanical and rheological responses of such dynamic networks. The benefits of each method have been highlighted. The use of other tools such as theoretical models and machine learning has been included. We noticed, amongst the most prominent results, that stress relaxes as the bond exchange reaction happens, and that at temperatures higher than the glass transition temperature, the self-healing properties are better since more bond BERs are observed. The lifetime of dynamic covalent crosslinks follows, at moderate to high temperatures, an Arrhenius-like temperature dependence. We note the modeling of certain properties like the melt viscosity with glass transition temperature and the topology freezing transition temperature according to a behavior ruled by either the Williams-Landel-Ferry equation or the Arrhenius equation. Discrepancies between the behavior in dissociative and associative covalent adaptable networks are discussed. We conclude by stating which material parameters and atomistic factors, at the nanoscale, have not yet been taken into account and are lacking in the current literature.

Conformational and static properties of tagged chains in solvents: effect of chain connectivity in solvent molecules

Polymer chains immersed in different solvent molecules exhibit diverse properties due to multiple spatiotemporal scales and complex interactions. Using molecular dynamics simulations, we study the conformational and static properties of tagged chains in different solvent molecules. Two types of solvent molecules were examined: one type consisted of chain molecules connected by bonds, while the other type consisted of individual bead molecules without any bonds. The only difference between the two solvent molecules lies in the chain connectivity. Our results show a compression of the tagged chains with the addition of bead or chain molecules. Chain molecule confinement induces a stronger compression compared to bead molecule confinement. In chain solvent molecules, the tagged chain's radius of gyration reached a minimum at a monomer volume fraction of ∼0.3. Notably, the probability distributions of chain size remain unchanged at different solvent densities, irrespective of whether the solvent consists of beads or polymers. Furthermore, as solvent density increases, a crossover from a unimodal to a bimodal distribution of bond angles is observed, indicating the presence of both compressed and expanded regions within the chain. The effective monomer-solvent interaction is obtained by calculating the partial radial distribution function and the potential of the mean force. In chain solvents, the correlation hole effect results in a reduced number of nearest neighbors around tagged monomers compared to bead solvents. The calculation of pore size distribution reveals that the solvent nonhomogeneity induced by chain connectivity leads to a broader distribution of pore sizes and larger pore dimensions at low volume fractions. These findings provide a deeper understanding of the conformational behavior of polymer chains in different solvent environments.

Phase Behavior of Polydisperse Y-Shaped Polymer Brushes under Good Solvent Conditions

Y-shaped polymer brushes represent a special class of binary mixed polymer brushes, in which a combination of different homopolymers leads to unique phase behavior. While most theoretical and simulation studies use monodisperse models, experimental systems are always polydisperse. This discrepancy hampers linking theoretical and experimental results. In this theoretical study, we employed dissipative particle dynamics to study the influence of polydispersity on the phase behavior of Y-shaped brushes grafted to flat surfaces under good solvent conditions. Polydispersity was kept within experimentally achievable values and was modeled via Schulz-Zimm distribution. In total, 10 systems were considered, thus covering the phase behavior of monodisperse, partially polydisperse and fully polydisperse systems. Using such generic representation of real polymers, we observed a rippled structure and aggregates in monodisperse systems. In addition, polydisperse brushes formed a stable perforated layer not observed previously in monodisperse studies, and influenced the stability of the remaining phases. Although the perforated layer was experimentally observed under good solvent conditions and in the melt state, further confirmation of its presence in systems under good solvent conditions required mapping real polymers onto mesoscale models that reflected, for example, different polymer rigidity, and excluded volume effects or direct influence of the surface, just to mention a few parameters. Finally, in this work, we show that mesoscale modeling successfully describes polydisperse models, which opens the way for rapid exploring of complex systems such as polydisperse Y-shaped brushes in selective or bad solvents or under non-equilibrium conditions.

Mesoscale Simulations of Structure Formation in Polyacrylonitrile Nascent Fibers Induced by Binary Solvent Mixture

Polyacrylonitrile (PAN) is widely used as a raw material for the production of high-modulus carbon fibers, the internal structure of which is directly affected by the spinning of the precursor. Although PAN fibers have been studied for a long time, the formation of their internal structure has not been sufficiently investigated theoretically. This is due to the large number of stages in the process and the parameters controlling them. In this study, we present a mesoscale model describing the evolution of nascent PAN fibers during the coagulation. It is constructed within the framework of a mesoscale dynamic density functional theory. We use the model to study the influence of a combined solvent of dimethyl sulfoxide (DMSO, a good solvent) and water (a non-solvent) on the microstructure of the fibers. A porous structure of PAN is formed as a result of the microphase separation of the polymer and the residual combined solvent at a high water content in the system. The model shows that one of the possible ways to obtain the homogeneous fiber structure is to slow down the coagulation by increasing the amount of good solvent in the system. This result is in agreement with the existing experimental data and confirms the efficiency of the presented model.

Modification of Macromolecules of Polyimide Films by Electron Irradiation

New polymeric materials formation by controlling their properties is the primary and most challenging problem in developing a methodology for synthesizing a chosen technology and its use. The combined effect of high-energy electron radiation and tensile stress will cause a decrease in crystallinity and the breakage of chemical bonds in polyimide film macromolecules and is a new approach in their production technology. The effect of uniaxial tension and electron irradiation on the modification of polyimide film at room temperature was studied. Irradiation of the films caused an increase in the intensity of the IR spectrum by ~2-6 times and an increase in the width of the bands. The intensity in the range of 1700-3500 cm^-1 increased, indicating an increase in the content of radicals as a result of irradiation. The amplitudes of the electron paramagnetic resonance signal from non-irradiated films increased from 3 × 10³ to 5 × 10³ as a result of uniaxial tension to fracture, indicating an increase in radicals in the material. The lines of the electron paramagnetic resonance spectrum shifted from 3475.0 cm^-1 to 3512.5 cm^-1, with a simultaneous decrease in the signal's amplitude from 6 ×10³ to 4 × 10³, as a result of the electron irradiation of the films, followed by their subjection to tension. This was due to a decrease in the concentration of the radicals of the =N-H and -N-H₂ groups until their disappearance and the formation of new ones.

Molecular Dynamic and Dissipative Particle Dynamic Simulation on the Miscibility of NR/CR Blends

Natural rubber (NR) exhibits good elasticity, flexural resistance, wear resistance, and excellent mechanical properties, and it has been widely used in aerospace, transportation, medical, and health fields. For NR, however, the resistance to thermal-oxidation and ozone aging is fairly poor. Although aging properties of NR can be significantly improved with the incorporation of chloroprene rubber (CR) according to some references, the miscibility between NR and CR, the morphologies of the binary blends, and so on are revealed ambiguously. In this work, molecular dynamics simulation (MD) and dissipative particle dynamics (DPD) simulation were carried out to predict the compatibility between natural rubber and chloroprene rubber in view of Flory-Huggins parameters. The morphologies of the blends were obtained with the use of the DPD method. The simulation results were furtherly examined by means of Fourier transform infrared spectroscopy (FT-IR) and dynamic mechanical analysis (DMA). It was found that the miscibility between NR and CR is poor. Nevertheless, the miscibility could be improved when the content of CR is 50% or 90%. In addition, spinodal decomposition with a critical temperature of 390 K would take place according to the phase diagram. Microphase structure such as spherical, lamellar, and bicontinuous phases can be found with different contents of CR in the blends with the results of morphologies analysis.

Dispersion and orientation patterns in nanorod-infused polymer melts

Introducing nanorods into a polymeric matrix can enhance the physical and mechanical properties of the resulting material. In this paper, we focus on understanding the dispersion and orientation patterns of nanorods in an unentangled polymer melt, particularly as a function of nanorod concentration, using molecular dynamics simulations. The system is comprised of flexible polymer chains and multi-thread nanorods that are equilibrated in the NPT ensemble. All interactions are purely repulsive except for those between polymers and rods. Results with attractive vs repulsive polymer-rod interactions are compared and contrasted. The concentration of rods has a direct impact on the phase behavior of the system. At lower concentrations, rods phase separate into nematic clusters, whereas at higher concentrations more isotropic and less structured rod configurations are observed. A detailed examination of the conformation of the polymer chains near the rod surface shows extension of the chains along the director of the rods (especially within clusters). The dispersion and orientation of the nanorods are a result of the competition between depletion entropic forces responsible for the formation of rod clusters, the enthalpic effects that improve mixing of rods and polymer, and entropic losses of polymers interpenetrating rod clusters.

From Ionic Nanoparticle Organic Hybrids to Ionic Nanocomposites: Structure, Dynamics, and Properties: A Review

Ionic nanoparticle organic hybrids have been the focus of research for almost 20 years, however the substitution of ionic canopy by an ionic-entangled polymer matrix was implemented only recently, and can lead to the formulation of ionic nanocomposites. The functionalization of nanoparticle surface by covalently grafting a charged ligand (corona) interacting electrostatically with the oppositely charged canopy (polymer matrix) can promote the dispersion state and stability which are prerequisites for property "tuning", polymer reinforcement, and fabrication of high-performance nanocomposites. Different types of nanoparticle, shape (spherical or anisotropic), loading, graft corona, polymer matrix type, charge density, molecular weight, can influence the nanoparticle dispersion state, and can alter the rheological, mechanical, electrical, self-healing, and shape-memory behavior of ionic nanocomposites. Such ionic nanocomposites can offer new properties and design possibilities in comparison to traditional polymer nanocomposites. However, to achieve a technological breakthrough by designing and developing such ionic nanomaterials, a synergy between experiments and simulation methods is necessary in order to obtain a fundamental understanding of the underlying physics and chemistry. Although there are a few coarse-grained simulation efforts to disclose the underlying physics, atomistic models and simulations that could shed light on the interphase, effect of polymer and nanoparticle chemistry on behavior, are completely absent.

Polymer solution structure and dynamics within pores of hexagonally close-packed nanoparticles

Using coarse-grained molecular dynamics simulations, we examine structure and dynamics of polymer solutions under confinement within the pores of a hexagonally close-packed (HCP) nanoparticle system with nanoparticle diameter fifty times that of the polymer Kuhn segment size. We model a condition where the polymer chain is in a good solvent (i.e., polymer-polymer interaction is purely repulsive and polymer-solvent and solvent-solvent interactions are attractive) and the polymer-nanoparticle and solvent-nanoparticle interactions are purely repulsive. We probe three polymer lengths (N = 10, 114, and 228 Kuhn segments) and three solution concentrations (1, 10, and 25%v) to understand how the polymer chain conformations and chain center-of-mass diffusion change under confinement within the pores of the HCP nanoparticle structure from those seen in bulk. The known trend of bulk polymer R_g² decreasing with increasing concentration no longer holds when confined in the pores of HCP nanoparticle structure; for example, for the 114-mer, the HCP 〈R_g²〉 at 1%v concentration is lower than HCP 〈R_g²〉 at 10%v concentration. The 〈R_g²〉 of the 114-mer and 228-mer exhibit the largest percent decline going from bulk to HCP at the 1%v concentration and the smallest percent decline at the 25%v concentration. We also provide insight into how the confinement ratio (CR) of polymer chain size to pore size within tetrahedral and octahedral pores in the HCP arrangement of nanoparticles affects the chain conformation and diffusion at various concentrations. At the same concentration, the N = 114 has significantly more movement between pores than the N = 228 chains. For the N = 114 polymer, the diffusion between pores (i.e., inter-pore diffusion) accelerates the overall diffusion rate for the confined HCP system while for the N = 228 polymer, the polymer diffusion in the entire HCP is dominated by the diffusion within the tetrahedral or octahedral pores with minor contributions from inter-pore diffusion. These findings augment the fundamental understanding of macromolecular diffusion through large, densely packed nanoparticle assemblies and are relevant to research focused on fabrication of polymer composite materials for chemical separations, storage, optics, and photonics. We perform coarse-grained molecular dynamics simulations to understand structure and dynamics of polymer solutions under confinement within hexagonal close packed nanoparticles with radii much larger than the polymer chain's bulk radius of gyration.

Modeling Polyzwitterion-Based Drug Delivery Platforms: A Perspective of the Current State-of-the-Art and Beyond

Drug delivery platforms are anticipated to have biocompatible and bioinert surfaces. PEGylation of drug carriers is the most approved method since it improves water solubility and colloid stability and decreases the drug vehicles' interactions with blood components. Although this approach extends their biocompatibility, biorecognition mechanisms prevent them from biodistribution and thus efficient drug transfer. Recent studies have shown (poly)zwitterions to be alternatives for PEG with superior biocompatibility. (Poly)zwitterions are super hydrophilic, mainly stimuli-responsive, easy to functionalize and they display an extremely low protein adsorption and long biodistribution time. These unique characteristics make them already promising candidates as drug delivery carriers. Furthermore, since they have highly dense charged groups with opposite signs, (poly)zwitterions are intensely hydrated under physiological conditions. This exceptional hydration potential makes them ideal for the design of therapeutic vehicles with antifouling capability, i.e., preventing undesired sorption of biologics from the human body in the drug delivery vehicle. Therefore, (poly)zwitterionic materials have been broadly applied in stimuli-responsive "intelligent" drug delivery systems as well as tumor-targeting carriers because of their excellent biocompatibility, low cytotoxicity, insignificant immunogenicity, high stability, and long circulation time. To tailor (poly)zwitterionic drug vehicles, an interpretation of the structural and stimuli-responsive behavior of this type of polymer is essential. To this end, a direct study of molecular-level interactions, orientations, configurations, and physicochemical properties of (poly)zwitterions is required, which can be achieved via molecular modeling, which has become an influential tool for discovering new materials and understanding diverse material phenomena. As the essential bridge between science and engineering, molecular simulations enable the fundamental understanding of the encapsulation and release behavior of intelligent drug-loaded (poly)zwitterion nanoparticles and can help us to systematically design their next generations. When combined with experiments, modeling can make quantitative predictions. This perspective article aims to illustrate key recent developments in (poly)zwitterion-based drug delivery systems. We summarize how to use predictive multiscale molecular modeling techniques to successfully boost the development of intelligent multifunctional (poly)zwitterions-based systems.

Structure and Diffusion of Ionic PDMS Melts

Ionic polymers exhibit mechanical properties that can be widely tuned upon selectively charging them. However, the correlated structural and dynamical properties underlying the microscopic mechanism remain largely unexplored. Here, we investigate, for the first time, the structure and diffusion of randomly and end-functionalized ionic poly(dimethylsiloxane) (PDMS) melts with negatively charged bromide counterions, by means of atomistic molecular dynamics using a united atom model. In particular, we find that the density of the ionic PDMS melts exceeds the one of their neutral counterpart and increases as the charge density increases. The counterions are condensed to the cationic part of end-functionalized cationic PDMS chains, especially for the higher molecular weights, leading to a slow diffusion inside the melt; the counterions are also correlated more strongly to each other for the end-functionalized PDMS. Temperature has a weak effect on the counterion structure and leads to an Arrhenius type of behavior for the counterion diffusion coefficient. In addition, the charge density of PDMS chains enhances the diffusion of counterions especially at higher temperatures, but hinders PDMS chain dynamics. Neutral PDMS chains are shown to exhibit faster dynamics (diffusion) than ionic PDMS chains. These findings contribute to the theoretical description of the correlations between structure and dynamical properties of ion-containing polymers.

Mobility of Polymer Melts in a Regular Array of Carbon Nanotubes

In polymer nanocomposites, mechanical properties essentially depend on the alignment of nanoparticles and polymers. In this work, we investigate an entangled polymer melt in a confinement computationally, in order to get an insight into the mobility behavior of the polymer chains. The confinement consists of nanotubes, arranged in a hexagonal array. We use dissipative particle dynamics, a fast, soft-core simulation method, and reintroduce entanglement dynamics via slip-springs. We observe a distinct influence of the confinement as diffusion is increased in the direction parallel to the nanotubes. Furthermore, we observe that an orientation of the polymers parallel to the nanotubes and chains are compressed in the direction orthogonal to their primitive path. The diffusion parallel to the nanotubes increases further as we increase the nanotube volume fraction in our systems. Moreover, we investigate the slip-spring distribution in the proximity of the nanotube surfaces of our fast and simple slip-spring model, which we find to coincide with results reported for more sophisticated and expensive methods. Our DPD model shows potential applicability to a wide range of polymer nanocomposites while preserving reptation behavior, which is typically lost due to the use of soft-core models.

Capturing Free-Radical Polymerization by Synergetic Ab Initio Calculations and Topological Reactive Molecular Dynamics

Photocurable polymers are used ubiquitously in 3D printing, coatings, adhesives, and composite fillers. In the present work, the free radical polymerization of photocurable compounds is studied using reactive classical molecular dynamics combined with a dynamical approach of the nonequilibrium molecular dynamics (D-NEMD). Different concentrations of radicals and reaction velocities are considered. The mechanical properties of the polymer resulting from 1,6-hexanediol dimethacrylate systems are characterized in terms of viscosity, diffusion constant, and activation energy, whereas the topological ones through the number of cycles (polymer loops) and cyclomatic complexity. Effects like volume shrinkage and delaying of the gel point for increasing monomer concentration are also predicted, as well as the stress-strain curve and Young's modulus. Combining ab initio, reactive molecular dynamics, and the D-NEMD method might lead to a novel and powerful tool to describe photopolymerization processes and to original routes to optimize additive manufacturing methods relying on photosensitive macromolecular systems.

Nanoparticle Shape Influence over Poly(lactic acid) Barrier Properties by Molecular Dynamics Simulations

Climate change is leading us to search for new materials that allow a more sustainable environmental situation in the long term. Poly(lactic acid) (PLA) has been proposed as a substitute for traditional plastics due to its high biodegradability. Various components have been added to improve their mechanical, thermal, and barrier properties. The modification of the PLA barrier properties by introducing nanoparticles with different shapes is an important aspect to control the molecular diffusion of oxygen and other gas compounds. In this work, we have described changes in oxygen diffusion by introducing nanoparticles of different shapes through molecular dynamics simulations. Our model illustrates that the existence of curved surfaces and the deposition of PLA around them by short chains generate small holes where oxygen accumulates, forming clusters and reducing their mobility. From the several considered shapes, the sphere is the most suitable structure to improve the barrier properties of the PLA.

Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that provides 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating realistic coordinates for polymer melt simulations, single-stranded as well as circular single-stranded DNA. We further demonstrate the power of our approach by setting up a microphase-separated block copolymer system, and by generating a liquid-liquid phase separated system inside a lipid vesicle.

Hydrolytic Degradation of Polylactic Acid Fibers as a Function of pH and Exposure Time

Polylactic acid (PLA) is a widely used bioresorbable polymer in medical devices owing to its biocompatibility, bioresorbability, and biodegradability. It is also considered a sustainable solution for a wide variety of other applications, including packaging. Because of its widespread use, there have been many studies evaluating this polymer. However, gaps still exist in our understanding of the hydrolytic degradation in extreme pH environments and its impact on physical and mechanical properties, especially in fibrous materials. The goal of this work is to explore the hydrolytic degradation of PLA fibers as a function of a wide range of pH values and exposure times. To complement the experimental measurements, molecular-level details were obtained using both molecular dynamics (MD) simulations with ReaxFF and density functional theory (DFT) calculations. The hydrolytic degradation of PLA fibers from both experiments and simulations was observed to have a faster rate of degradation in alkaline conditions, with 40% of strength loss of the fibers in just 25 days together with an increase in the percent crystallinity of the degraded samples. Additionally, surface erosion was observed in these PLA fibers, especially in extreme alkaline environments, in contrast to bulk erosion observed in molded PLA grafts and other materials, which is attributed to the increased crystallinity induced during the fiber spinning process. These results indicate that spun PLA fibers function in a predictable manner as a bioresorbable medical device when totally degraded at end-of-life in more alkaline conditions.

Ionic Polymer Nanocomposites Subjected to Uniaxial Extension: A Nonequilibrium Molecular Dynamics Study

We explore the behavior of coarse-grained ionic polymer nanocomposites (IPNCs) under uniaxial extension up to 800% strain by means of nonequilibrium molecular dynamics simulations. We observe a simultaneous increase of stiffness and toughness of the IPNCs upon increasing the engineering strain rate, in agreement with experimental observations. We reveal that the excellent toughness of the IPNCs originates from the electrostatic interaction between polymers and nanoparticles, and that it is not due to the mobility of the nanoparticles or the presence of polymer-polymer entanglements. During the extension, and depending on the nanoparticle volume fraction, polymer-nanoparticle ionic crosslinks are suppressed with the increase of strain rate and electrostatic strength, while the mean pore radius increases with strain rate and is altered by the nanoparticle volume fraction and electrostatic strength. At relatively low strain rates, IPNCs containing an entangled matrix exhibit self-strengthening behavior. We provide microscopic insight into the structural, conformational properties and crosslinks of IPNCs, also referred to as polymer nanocomposite electrolytes, accompanying their unusual mechanical behavior.

Fracture in Silica/Butadiene Rubber: A Molecular Dynamics View of Design-Property Relationships

Despite intense investigation, the mechanisms governing the mechanical reinforcement of polymers by dispersed nanoparticles have only been partially clarified. This is especially true for the ultimate properties of the nanocomposites, which depend on their resistance to fracture at large deformations. In this work, we adopt molecular dynamics simulations to investigate the mechanical properties of silica/polybutadiene rubber, using a quasi-atomistic model that allows a meaningful description of bond breaking and fracture over relatively large length scales. The behavior of large nanocomposite models is explored systematically by tuning the cross-linking, grafting densities, and nanoparticle concentration. The simulated stress-strain curves are interpreted by monitoring the breaking of chemical bonds and the formation of voids, up to complete rupture of the systems. We find that some chemical bonds, and particularly the S-S linkages at the rubber-nanoparticle interface, start breaking well before the appearance of macroscopic features of fracture and yield.

Molecular dynamics investigation of structural and mechanical properties of silica nanorod reinforced dental resin composites

In this work, molecular dynamics simulations are conducted to investigate the structural and mechanical properties of dental materials, i.e., the silica nanorod reinforced Bis-GMA/TEGDMA resin composite. The effects of loading content and size of the silica nanorods on the composite stiffness were performed by examining resin chain conformation, hydrogen bonds and matrix/filler binding energy. It is revealed that the presence of the silica nanorod causes polymer chain expansion, endowing the resins with higher stiffness. Moreover, the volumetric hydrogen bonds and binding energy increase considerably with the loading content, but decrease gradually with the diameter or show almost independence of the length. Furthermore, the composite moduli were quantified by the micromechanics models and the transverse moduli were well predicted by the Counto model, signifying a perfect bonding between the matrix and nanorod. The chain expansion and energetic matrix/filler interactions are believed to contribute to the significant mechanical reinforcement of the composites with the loading content. However, the length of the nanorod has a little effect on the composite moduli due to the unaltered interfacial interaction. In contrast, a smaller diameter is supposed to give a larger modulus, and this is not observed in this work due to the synergic effects of improved matrix/filler interaction and actual reduced filler volume fraction. The mechanical enhancement by the rod-like structures is more influenced by the loading content, but less so by the size of the nanorod, and it also exhibits superior mechanical performance as compared to nanoparticles. The findings thus extend the current understanding of the nanostructure and mechanical properties of silica nanorod reinforced dental resin composites from an atomic/molecular perspective.

Structure and Dynamics of Highly Attractive Polymer Nanocomposites in the Semi-Dilute Regime: The Role of Interfacial Domains and Bridging Chains

Detailed molecular dynamics (MD) simulations are employed to study how the presence of adsorbed domains and nanoparticle bridging chains affect the structural, conformational, thermodynamic, and dynamic properties of attractive polymer nanocomposite melts in the semi-dilute regime. As a model system we have chosen an unentangled poly(ethylene glycol) (PEG) matrix containing amorphous spherical silica nanoparticles with different diameters and at different concentrations. Emphasis is placed on properties such as the polymer mass density profile around nanoparticles, the compressibility of the system, the mean squared end-to-end distance of PEG chains, their orientational and diffusive dynamics, the single chain form factor, and the scattering functions. Our analysis reveals a significant impact of the adsorbed, interfacial polymer on the microscopic dynamic and conformational properties of the nanocomposite, especially under conditions favoring higher surface-to-volume ratios (e.g., for small nanoparticle sizes at fixed nanoparticle loading, or for higher silica concentrations). Simultaneously, adsorbed polymer chains adopt graft-like conformations, a feature that allows them to considerably extend away from the nanoparticle surface to form bridges with other nanoparticles. These bridges drive the formation of a nanoparticle network whose strength (number of tie chains per nanoparticle) increases substantially with increasing concentration of the polymer matrix in nanoparticles, or with decreasing nanoparticle size at fixed nanoparticle concentration. The presence of hydroxyl groups at the ends of PEG chains plays a key role in the formation of the network. If hydroxyl groups are substituted by methoxy ones, the simulations reveal that the number of bridging chains per nanoparticle decreases dramatically, thus the network formed is less dense and less strong mechanically, and has a smaller impact on the properties of the nanocomposite. Our simulations predict further that the isothermal compressibility and thermal expansion coefficient of PEG-silica nanocomposites are significantly lower than those of pure PEG, with their values decreasing practically linear with increasing concentration of the nanocomposite in nanoparticles.

Self-assembly in biobased nanocomposites for multifunctionality and improved performance

Concerns of petroleum dependence and environmental pollution prompt an urgent need for new sustainable approaches in developing polymeric products. Biobased polymers provide a potential solution, and biobased nanocomposites further enhance the performance and functionality of biobased polymers. Here we summarize the unique challenges and review recent progress in this field with an emphasis on self-assembly of inorganic nanoparticles. The conventional wisdom is to fully disperse nanoparticles in the polymer matrix to optimize the performance. However, self-assembly of the nanoparticles into clusters, networks, and layered structures provides an opportunity to address performance challenges and create new functionality in biobased polymers. We introduce basic assembly principles through both blending and in situ synthesis, and identify key technologies that benefit from the nanoparticle assembly in the polymer matrix. The fundamental forces and biobased polymer conformations are discussed in detail to correlate the nanoscale interactions and morphology with the macroscale properties. Different types of nanoparticles, their assembly structures and corresponding applications are surveyed. Through this review we hope to inspire the community to consider utilizing self-assembly to elevate functionality and performance of biobased materials. Development in this area sets the foundation for a new era of designing sustainable polymers in many applications including packaging, construction chemicals, adhesives, foams, coatings, personal care products, and advanced manufacturing.

Effect of surface properties and polymer chain length on polymer adsorption in solution

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.

Insights from modeling into structure, entanglements, and dynamics in attractive polymer nanocomposites

Conformations, entanglements and dynamics in attractive polymer nanocomposites are investigated in this work by means of coarse-grained molecular dynamics simulation, for both weak and strong confinements, in the presence of nanoparticles (NPs) at NP volume fractions φ up to 60%. We show that the behavior of the apparent tube diameter dapp in such nanocomposites can be greatly different from nanocomposites with nonattractive interactions. We find that this effect originates, based on a mean field argument, from the geometric confinement length dgeo at strong confinement (large φ) and not from the bound polymer layer on NPs (interparticle distance ID <2Rg) as proposed recently based on experimental measurements. Close to the NP surface, the entangled polymer mobility is reduced in attractive nanocomposites but still faster than the NP mobility for volume fractions beyond 20%. Furthermore, entangled polymer dynamics is hindered dramatically by the strong confinement created by NPs. For the first time using simulations, we show that the entangled polymer conformation, characterized by the polymer radius of gyration Rg and form factor, remains basically unperturbed by the presence of NPs up to the highest volume fractions studied, in agreement with various experiments on attractive nanocomposites. As a side-result we demonstrate that the loose concept of ID can be made a microscopically well defined quantity using the mean pore size of the NP arrangement.

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.

Molecular Modeling and Simulation of Polymer Nanocomposites with Nanorod Fillers

We present a coarse-grained (CG) molecular dynamics (MD) simulation study of polymer nanocomposites (PNCs) containing nanorods with homogeneous and patchy surface chemistry/functionalization, modeled with isotropic and directional nanorod-nanorod attraction, respectively. We show how the PNC morphology is impacted by the nanorod design (i.e., aspect ratio, homogeneous or patchy surface chemistry/functionalization) for nanorods with a diameter equal to the Kuhn length of the polymer in the matrix. For PNCs with 10 vol % nanorods that have an aspect ratio ≤5, we observe percolated morphology with directional nanorod-nanorod attraction and phase-separated (i.e., nanorod aggregation) morphology with isotropic nanorod-nanorod attraction. In contrast, for nanorods with higher aspect ratios, both types of attractions result in aggregated nanorods morphology due to the dominance of entropic driving forces that cause long nanorods to form orientationally ordered aggregates. For most PNCs with isotropic or directional nanorod-nanorod attractions, the average matrix polymer conformation is not perturbed by the inclusion of up to 20 vol % nanorods. The polymer chains in contact with nanorods (i.e., interfacial chains) are on average extended and statistically different from the conformations the matrix chains adopt in the pure melt state (with no nanorods); in contrast, the polymer chains far from nanorods (i.e., bulk chains) adopt the same conformations as the matrix chains adopt in the pure melt state. We also study the effect of other parameters, such as attraction strength, nanorod volume fraction, and matrix chain length, for PNCs with isotropic or directional nanorod-nanorod attractions. Collectively, our results provide valuable design rules to achieve specific PNC morphologies (i.e., dispersed, aggregated, percolated, and orientationally aligned nanorods) for various potential applications.

Interface and Interphase in Polymer Nanocomposites with Bare and Core-Shell Gold Nanoparticles

Metal nanoparticles are used to modify/enhance the properties of a polymer matrix for a broad range of applications in bio-nanotechnology. Here, we study the properties of polymer/gold nanoparticle (NP) nanocomposites through atomistic molecular dynamics, MD, simulations. We probe the structural, conformational and dynamical properties of polymer chains at the vicinity of a gold (Au) NP and a functionalized (core/shell) Au NP, and compare them against the behavior of bulk polyethylene (PE). The bare Au NPs were constructed via a systematic methodology starting from ab-initio calculations and an atomistic Wulff construction algorithm resulting in the crystal shape with the minimum surface energy. For the functionalized NPs the interactions between gold atoms and chemically adsorbed functional groups change their shape. As a model polymer matrix we consider polyethylene of different molecular lengths, from the oligomer to unentangled Rouse like systems. The PE/Au interaction is parametrized via DFT calculations. By computing the different properties the concept of the interface, and the interphase as well, in polymer nanocomposites with metal NPs are critically examined. Results concerning polymer density profiles, bond order parameter, segmental and terminal dynamics show clearly that the size of the interface/interphase, depends on the actual property under study. In addition, the anchored polymeric chains change the behavior/properties, and especially the chain density profile and the dynamics, of the polymer chain at the vicinity of the Au NP.

Heat diffusion-related damping process in a highly precise coarse-grained model for nonlinear motion of SWCNT

Second sound and heat diffusion in single-walled carbon nanotubes (SWCNT) are well-known phenomena which is related to the high thermal conductivity of this material. In this paper, we have shown that the heat diffusion along the tube axis affects the macroscopic motion of SWCNT and adapting this phenomena to coarse-grained (CG) model can improve the precision of the coarse-grained molecular dynamics (CGMD) exceptionally. The nonlinear macroscopic motion of SWCNT in the free thermal vibration condition in adiabatic environment is demonstrated in the most simplified version of CG modeling as maintaining finite temperature and total energy with suggested dissipation process derived from internal heat diffusion. The internal heat diffusion related to the cross correlated momentum from different potential energy functions is considered, and it can reproduce the nonlinear dynamic nature of SWCNTs without external thermostatting in CG model. Memory effect and thermostat with random noise distribution are not included, and the effect of heat diffusion on memory effect is quantified through Mori-Zwanzig formalism. This diffusion shows perfect syncronization of the motion between that of CGMD and MD simulation, which is started with initial conditions from the molecular dynamics (MD) simulation. The heat diffusion related to this process has shown the same dispersive characteristics to second wave in SWCNT. This replication with good precision indicates that the internal heat diffusion process is the essential cause of the nonlinearity of the tube. The nonlinear dynamic characteristics from the various scale of simple beads systems are examined with expanding its time step and node length.

Development of Coarse-Grained Models for Poly(4-vinylphenol) and Poly(2-vinylpyridine): Polymer Chemistries with Hydrogen Bonding

In this paper, we identify the modifications needed in a recently developed generic coarse-grained (CG) model that captured directional interactions in polymers to specifically represent two exemplary hydrogen bonding polymer chemistries-poly(4-vinylphenol) and poly(2-vinylpyridine). We use atomistically observed monomer-level structures (e.g., bond, angle and torsion distribution) and chain structures (e.g., end-to-end distance distribution and persistence length) of poly(4-vinylphenol) and poly(2-vinylpyridine) in an explicitly represented good solvent (tetrahydrofuran) to identify the appropriate modifications in the generic CG model in implicit solvent. For both chemistries, the modified CG model is developed based on atomistic simulations of a single 24-mer chain. This modified CG model is then used to simulate longer (36-mer) and shorter (18-mer and 12-mer) chain lengths and compared against the corresponding atomistic simulation results. We find that with one to two simple modifications (e.g., incorporating intra-chain attraction, torsional constraint) to the generic CG model, we are able to reproduce atomistically observed bond, angle and torsion distributions, persistence length, and end-to-end distance distribution for chain lengths ranging from 12 to 36 monomers. We also show that this modified CG model, meant to reproduce atomistic structure, does not reproduce atomistically observed chain relaxation and hydrogen bond dynamics, as expected. Simulations with the modified CG model have significantly faster chain relaxation than atomistic simulations and slower decorrelation of formed hydrogen bonds than in atomistic simulations, with no apparent dependence on chain length.

Polymer Conformations, Entanglements and Dynamics in Ionic Nanocomposites: A Molecular Dynamics Study

We investigate nanoparticle (NP) dispersion, polymer conformations, entanglements and dynamics in ionic nanocomposites. To this end, we study nanocomposite systems with various spherical NP loadings, three different molecular weights, two different Bjerrum lengths, and two types of charge-sequenced polymers by means of molecular dynamics simulations. NP dispersion can be achieved in either oligomeric or entangled polymeric matrices due to the presence of electrostatic interactions. We show that the overall conformations of ionic oligomer chains, as characterized by their radii of gyration, are affected by the presence and the amount of charged NPs, while the dimensions of charged entangled polymers remain unperturbed. Both the dynamical behavior of polymers and NPs, and the lifetime and amount of temporary crosslinks, are found to depend on the ratio between the Bjerrum length and characteristic distance between charged monomers. Polymer-polymer entanglements start to decrease beyond a certain NP loading. The dynamics of ionic NPs and polymers is very different compared with their non-ionic counterparts. Specifically, ionic NP dynamics is getting enhanced in entangled matrices and also accelerates with the increase of NP loading.

Phase Behavior of Gradient Copolymer Melts with Different Gradient Strengths Revealed by Mesoscale Simulations

Design and preparation of functional nanomaterials with specific properties requires precise control over their microscopic structure. A prototypical example is the self-assembly of diblock copolymers, which generate highly ordered structures controlled by three parameters: the chemical incompatibility between blocks, block size ratio and chain length. Recent advances in polymer synthesis have allowed for the preparation of gradient copolymers with controlled sequence chemistry, thus providing additional parameters to tailor their assembly. These are polydisperse monomer sequence, block size distribution and gradient strength. Here, we employ dissipative particle dynamics to describe the self-assembly of gradient copolymer melts with strong, intermediate, and weak gradient strength and compare their phase behavior to that of corresponding diblock copolymers. Gradient melts behave similarly when copolymers with a strong gradient are considered. Decreasing the gradient strength leads to the widening of the gyroid phase window, at the expense of cylindrical domains, and a remarkable extension of the lamellar phase. Finally, we show that weak gradient strength enhances chain packing in gyroid structures much more than in lamellar and cylindrical morphologies. Importantly, this work also provides a link between gradient copolymers morphology and parameters such as chemical incompatibility, chain length and monomer sequence as support for the rational design of these nanomaterials.

Slip-spring simulations of different constraint release environments for linear polymer chains

The constraint release (CR) mechanism has important effects on polymer relaxation and the chains will show different relaxation behaviour in conditions of monodisperse, bidisperse and other topological environments. By comparing relaxation data of linear polyisoprene (PI) chains dissolved in very long matrix and monodisperse melts, Matsumiya et al. showed that CR mechanism accelerates both dielectric and viscoelastic relaxation (Matsumiya et al. 2013 Macromolecules 46, 6067. (doi:10.1021/ma400606n)). In this work, the experimental data reported by Matsumiya et al. are reproduced using the single slip-spring (SSp) model and the CR accelerating effects on both dielectric and viscoelastic relaxation are validated by simulations. This effect on viscoelastic relaxation is more pronounced. The coincidence for end-to-end relaxation and the viscoelastic relaxation has also been checked using probe version SSp model. A variant of SSp with each entanglement assigning a characteristic lifetime is also proposed to simulate various CR environment flexibly. Using this lifetime version SSp model, the correct relaxation function can be obtained with equal numbers of entanglement destructions by CR and reptation/contour length fluctuation (CLF) for monodisperse melts. Good agreement with published experiment data is also obtained for bidisperse melts, which validates the ability to correctly describe the CR environment of the lifetime version model.

Vegetable Additives in Food Packaging Polymeric Materials

Plants are the most abundant bioresources, providing valuable materials that can be used as additives in polymeric materials, such as lignocellulosic fibers, nano-cellulose, or lignin, as well as plant extracts containing bioactive phenolic and flavonoid compounds used in the healthcare, pharmaceutical, cosmetic, and nutraceutical industries. The incorporation of additives into polymeric materials improves their properties to make them suitable for multiple applications. Efforts are made to incorporate into the raw polymers various natural biobased and biodegradable additives with a low environmental fingerprint, such as by-products, biomass, plant extracts, etc. In this review we will illustrate in the first part recent examples of lignocellulosic materials, lignin, and nano-cellulose as reinforcements or fillers in various polymer matrices and in the second part various applications of plant extracts as active ingredients in food packaging materials based on polysaccharide matrices (chitosan/starch/alginate).

An unexpected N-dependence in the viscosity reduction in all-polymer nanocomposite

Adding small nanoparticles (NPs) into polymer melt can lead to a non-Einstein-like decrease in viscosity. However, the underlying mechanism remains a long-standing unsolved puzzle. Here, for an all-polymer nanocomposite formed by linear polystyrene (PS) chains and PS single-chain nanoparticles (SCNPs), we perform large-scale molecular dynamics simulations and experimental rheology measurements. We show that with a fixed (small) loading of the SCNP, viscosity reduction (VR) effect can be largely amplified with an increase in matrix chain length \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N$$\end{document}N, and that the system with longer polymer chains will have a larger VR. We demonstrate that such \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N$$\end{document}N-dependent VR can be attributed to the friction reduction experienced by polymer segment blobs which have similar size and interact directly with these SCNPs. A theoretical model is proposed based on the tube model. We demonstrate that it can well describe the friction reduction experienced by melt polymers and the VR effect in these composite systems.

Addition of small nanoparticles into polymer melt can lead to decrease in viscosity but the underlying mechanism for such viscosity reduction remains unclear. Here, the authors investigate the reduction in viscosity by large-scale molecular dynamics simulation and experimental rheology measurements for an all-polymer nanocomposite formed by linear polystyrene chains and PS single-chain nanoparticle.

Toward Design of Novel Materials for Organic Electronics

Materials for organic electronics are presently used in prominent applications, such as displays in mobile devices, while being intensely researched for other purposes, such as organic photovoltaics, large-area devices, and thin-film transistors. Many of the challenges to improve and optimize these applications are material related and there is a nearly infinite chemical space that needs to be explored to identify the most suitable material candidates. Established experimental approaches struggle with the size and complexity of this chemical space. Herein, the development of simulation methods is addressed, with a particular emphasis on predictive multiscale protocols, to complement experimental research in the identification of novel materials and illustrate the potential of these methods with a few prominent recent applications. Finally, the potential of machine learning and methods based on artificial intelligence is discussed to further accelerate the search for new materials.

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

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