Chemically specific multiscale modeling of clay-polymer nanocomposites reveals intercalation dynamics, tactoid self-assembly and emergent materials properties

Quasi-Reaction Coarse-Grained Simulation: Unveiling the Mesoscale Interfacial Response of CSH/PVA Fiber

The lack of a comprehensive force field and understanding at the mesoscale for hydrated calcium silicate (CSH)/polyvinyl alcohol (PVA) fiber has hindered the upscaling and bridging of nanoscale to macroscale phenomena. In this study, we propose a coarse-grained (CG) force field that incorporates bond-breaking operations to endow fiber reactivity, abrasion, and fracture properties. By employing a cubic lattice modeling, we effectively address the challenges associated with semicrystalline relaxation of fibers. For the first time, quasi-reaction CG simulation successfully replicates slip-hardening behaviors and surface abrasion. We demonstrate that abrasion improves interface load transfer and triggers slip-hardening by redistributing stress. Additionally, the influences of single and coupled factors, such as nonbonding interactions and surface roughness, are investigated. Mesoscale understanding provides insights for enabling precise control of load transfer paths and fabrication of interface damage-predictable materials.

Molecular Dynamics Simulation of the Interaction within the Carboxymethyl Cellulose-Modified Montmorillonite Lamellae at Aggressive CuCl2 Concentrations

To elucidate the degradation mechanism of the CMC-modified MMT composite at aggressive Cu2+ concentrations, large scale molecular dynamics simulation was conducted for CuCl2 concentrations ranging from 0 to 800 mM. Both CMC and MMT followed the Langmuir isotherm for Cu2+ adsorption, and the adsorption capacity of CMC (8.75 mmol/g) was much higher than that of MMT (0.83 mmol/g). Despite the CMC mass ratio being only 4.1%, it adsorbed up to 34.3% of the total adsorbed Cu2+. The Cu2+ attraction ability hierarchy of oxygen-containing functional groups in the CMC is as follows: carboxylic oxygens > alcoholic oxygens > carbinolic oxygens > bridging oxygens > glucose oxygens. Carboxyls were the most effective in chelating and complexing with Cu2+, and they could be intentionally added in artificially synthesized polymer-MMT composites for Cu2+ containment. Formation of the Cu2+ cation bridge between CMC and MMT at aggressive CuCl2 concentrations contributed to the transition of CMC density distribution from unimodality to bimodality and enhanced resistance of polymer elution. As the CuCl2 concentration increased, the stoichiometric ratio between the chelated Cu2+ and carboxylic oxygens increased from 1:2 to 1:1, suggesting the evolution of the Cu2+ chelation mechanism.

Cellulose/silica composite microtubular superfoam with excellent flame retardancy, thermal insulation and ablative resistance

Thermal insulation materials with good flame-retardant properties have attracted widespread attention because of their huge application potential. Traditional petrochemical-based polymer insulation materials are flammable and have problems with environmental pollution. The microtubule structure is a perfect microstructure with excellent thermal insulation performance. In addition, the microtubule structure also has low density and high elasticity. Therefore, the microtubule structure is an important reference microstructure for the development of efficient thermal insulation materials. In this paper, a cellulose/SiO2 composite microtube thermal insulation superfoam has been successfully prepared. Cellulose microtubules were successfully prepared from poplar sawdust by chemical methods. The SiO2 aerogel precursor solution can be quickly adsorbed by the delignified cellulose microtubes. The SiO2 aerogel shells are evenly distributed only on the inner and outer walls of the delignified cellulose microtubes. The cellulose/SiO2 microtube composite (CSMC) superfoam exhibits low density, good mechanical properties, and low thermal conductivity (as low as 0.042 ± 0.0018 W m-1 K-1). The CSMC superfoam exhibits excellent self-extinguishing and flame-retardant properties. After being burned by a butane flame, the superfoam still has certain mechanical properties. The thermal conductivity of the B-CSMC superfoam (the CSMC superfoam burned by a butane flame) is about 0.050 W m-1 K-1. The B-CSMC superfoam remained almost unchanged after being continuously ablated by a butane flame for 3600 seconds.

Temperature-Transferable Coarse-Grained Models for Volumetric Properties of Poly(lactic Acid)

A new coarse-grained (CG) model, for which each monomer is mapped as one bead at its center of mass, was developed for simulating the volumetric properties of the polylactide (PLA) bulk. The three bonded CG potentials are first parametrized against the strain energies of the dimer, trimer, and tetramer, and the nonbonded CG potentials are then optimized to match the melt densities of the decamer. With the derived CG potentials, molecular dynamics (MD) simulations are found to reproduce thermal expansion and glass transition. By rescaling the dihedral and nonbonded potentials with temperature-independent factors, the glass transition temperature (Tg) is also satisfactorily restored with little modifications on the volumetric expansive coefficients at both rubbery and glassy states. Therefore, the finally optimized CG potentials exhibit excellent temperature transferability, as rationalized by the Simha-Boyer relation. Furthermore, it is confirmed that the dihedral torsions and nonbonded interactions play key roles in glass transition. Also, the simulated bulk moduli and conformational properties in a wide temperature range compare well with the referenced data. The proposed multiscale scheme has great potential in simulating thermo-mechanical properties of PLA and other polymers.

Scalable Production of 2D Minerals by Polymer Intercalation and Adhesion for Multifunctional Applications

Natural and sustainable 2D minerals have many unique properties and may reduce reliance on petroleum-based products. However, the large-scale production of 2D minerals remains challenging. Herein, a green, scalable, and universal polymer intercalation and adhesion exfoliation (PIAE) method to produce 2D minerals such as vermiculite, mica, nontronite, and montmorillonite with large lateral sizes and high efficiency, is developed. The exfoliation relies on the dual functions of polymers involving intercalation and adhesion to expand interlayer space and weaken interlayer interactions of minerals, facilitating their exfoliation. Taking vermiculite as an example, the PIAE produces 2D vermiculite with an average lateral size of 1.83 ± 0.48 µm and thickness of 2.40 ± 0.77 nm at a yield of ≈30.8%, surpassing state-of-the-art methods in preparing 2D minerals. Flexible films are directly fabricated by the 2D vermiculite/polymer dispersion, exhibiting outstanding performances including mechanical strength, thermal resistance, ultraviolet shielding, and recyclability. The representative application of colorful multifunctional window coatings in sustainable buildings is demonstrated, indicating the potential of massively produced 2D minerals.

Oxide- and Silicate-Water Interfaces and Their Roles in Technology and the Environment

Interfacial reactions drive all elemental cycling on Earth and play pivotal roles in human activities such as agriculture, water purification, energy production and storage, environmental contaminant remediation, and nuclear waste repository management. The onset of the 21st century marked the beginning of a more detailed understanding of mineral aqueous interfaces enabled by advances in techniques that use tunable high-flux focused ultrafast laser and X-ray sources to provide near-atomic measurement resolution, as well as by nanofabrication approaches that enable transmission electron microscopy in a liquid cell. This leap into atomic- and nanometer-scale measurements has uncovered scale-dependent phenomena whose reaction thermodynamics, kinetics, and pathways deviate from previous observations made on larger systems. A second key advance is new experimental evidence for what scientists hypothesized but could not test previously, namely, interfacial chemical reactions are frequently driven by "anomalies" or "non-idealities" such as defects, nanoconfinement, and other nontypical chemical structures. Third, progress in computational chemistry has yielded new insights that allow a move beyond simple schematics, leading to a molecular model of these complex interfaces. In combination with surface-sensitive measurements, we have gained knowledge of the interfacial structure and dynamics, including the underlying solid surface and the immediately adjacent water and aqueous ions, enabling a better definition of what constitutes the oxide- and silicate-water interfaces. This critical review discusses how science progresses from understanding ideal solid-water interfaces to more realistic systems, focusing on accomplishments in the last 20 years and identifying challenges and future opportunities for the community to address. We anticipate that the next 20 years will focus on understanding and predicting dynamic transient and reactive structures over greater spatial and temporal ranges as well as systems of greater structural and chemical complexity. Closer collaborations of theoretical and experimental experts across disciplines will continue to be critical to achieving this great aspiration.

Approaches and Perspective of Coarse-Grained Modeling and Simulation for Polymer-Nanoparticle Hybrid Systems

Molecular modeling and simulations have emerged as effective and indispensable tools to characterize polymeric systems. They provide fundamental and essential insights to design a product of the required properties and to improve the understanding of a phenomenon at the molecular level for a particular system. The polymer-nanoparticle hybrids are materials with outstanding properties and correspondingly large applications whose study has benefited from this new paradigm. However, despite the significant expansion of modern day computational powers, investigation of the long time and large length scale phenomenon in polymeric and polymer-nanoparticle systems is still a challenging task to complete through all-atom molecular dynamics (AA-MD) simulations. To circumvent this problem, a variety of coarse-grained (CG) models have been proposed, ranging from the generic CG models for qualitative properties predictions to more realistic chemically specific CG models for quantitative properties predictions. These CG models have already delivered some success stories in the study of several spatial and temporal evolutions of many processes. Some of these studies were beyond the feasibility of traditional atomistic resolution models due to either the size or the time constraints. This review captures the different types of popular CG approaches that are utilized in the investigation of the microscopic behavior of polymer-nanoparticle hybrid systems. The rationale of this article is to furnish an overview of the popular CG approaches and their applications, to review several important and most recent developments, and to delineate the perspectives on future directions in the field.

A Coarse-Grained Model for the Mechanical Behavior of Na-Montmorillonite Clay

Sodium montmorillonite (Na-MMT) is one of the most commonly found swelling clay minerals with diverse engineering and technological applications. The nanomechanical properties of this mineral have been extensively investigated computationally utilizing molecular dynamics (MD) simulations to portray the molecular-level changes at different environmental conditions. As the environmentally found Na-MMT clays are generally sized within hundreds of nanometers, all-atomistic (AA) MD simulations of clays within such size range are particularly challenging due to computational inefficiency. Informed from atomistic modeling, a coarse-grained (CG) modeling technique can be employed to overcome the spatiotemporal limitation. The current study presents a modeling strategy to develop a computationally efficient model of Na-MMT clay with a typical size over ≃100 nm by shrinking the atomistic platelet thickness and reducing the number of center-layer atoms. Using the "strain-energy conservation" approach, the force field parameters for the CG model are obtained and the developed CG model can well preserve in-plane tension, shear, and bending behaviors of atomistic counterparts. Remarkably, the CG tactoid model of Na-MMT, a hierarchical multilayer structure, can reproduce the interlayer shear and adhesion as well as d-spacing among the clay sheets as of atomistic one to a good approximation while gaining significantly improved computational speed. Our study demonstrates the efficacy of the CG modeling framework, paving the way for the bottom-up multiscale prediction of mechanical behaviors of clay and related minerals.

Stability and passivation of 2D group VA elemental materials: black phosphorus and beyond

Since the successful isolation of graphene in 2004, two-dimensional (2D) materials have become one of the focuses in material science owing to their extraordinary physical and chemical properties. In particular, 2D group VA elemental materials exhibit fascinating thickness-dependent band structures. Unfortunately, the well-known instability issue hinders their fundamental researches and practical applications. In this review, we first discuss the degradation mechanism of black phosphorus (BP), a most studied group VA material. Next, we summarize the methods to enhance BP stability with the focus of multifunctional passivation. Finally, we briefly discuss the protection strategies of other emerging group VA materials in recent years. This review provides insight for the degradation mechanism and protecting strategy for 2D group VA elements materials, which will promote their potential applications in electronics, optoelectronics, and biomedicine.

Principles governing control of aggregation and dispersion of aqueous graphene oxide

Controlling the structure of graphene oxide (GO) phases and their smaller analogues, graphene (oxide) quantum dots (GOQDs), is vitally important for any of their widespread intended applications: highly ordered arrangements of nanoparticles for thin-film or membrane applications of GO, dispersed nanoparticles for composite materials and three-dimensional porous arrangements for hydrogels. In aqueous environments, it is not only the chemical composition of the GO flakes that determines their morphologies; external factors such as pH and the coexisting cations also influence the structures formed. By using accurate models of GO that capture the heterogeneity of surface oxidation and very large-scale coarse-grained molecular dynamics that can simulate the behaviour of GO at realistic sizes of GOQDs, the driving forces that lead to the various morphologies in aqueous solution are resolved. We find the morphologies are determined by a complex interplay between electrostatic, [Formula: see text]-[Formula: see text] and hydrogen bonding interactions. Assembled morphologies can be controlled by changing the degree of oxidation and the pH. In acidic aqueous solution, the GO flakes vary from fully aggregated over graphitic domains to partial aggregation via hydrogen bonding between hydroxylated domains, leading to the formation of planar extended flakes at high oxidation ratios and stacks at low oxidation ratios. At high pH, where the edge carboxylic acid groups are deprotonated, electrostatic repulsion leads to more dispersion, but a variety of aggregation behaviour is surprisingly still observed: over graphitic regions, via hydrogen bonding and "face-edge" interactions. Calcium ions cause additional aggregation, with a greater number of "face-face" and "edge-edge" aggregation mechanisms, leading to irregular aggregated structures. "Face-face" aggregation mechanisms are enhanced by the GO flakes possessing distinct domains of hydroxylated and graphitic regions, with [Formula: see text]-[Formula: see text] and hydrogen bonding interactions prevalent between these regions on aggregated flakes respectively. These findings furnish explanations for the aggregation characteristics of GO and GOQDs, and provide computational methods to design directed synthesis routes for self-assembled and associated applications.

Effect of Nanoparticles Surface Bonding and Aspect Ratio on Mechanical Properties of Highly Cross-Linked Epoxy Nanocomposites: Mesoscopic Simulations

The paper aims to study the mechanical properties of epoxy resin filled with clay nanoparticles (NPs), depending on their shapes and content on the surface of a modifying agent capable of forming covalent bonds with a polymer. The cylindrical clay nanoparticles with equal volume and different aspects ratios (disks, barrel, and stick) are addressed. The NPs' bonding ratio with the polymer (RGC) is determined by the fraction of reactive groups and conversion time and varies from RGC = 0 (non-bonded nanoparticles) to RGC = 0.65 (more than half of the surface groups are linked with the polymer matrix). The performed simulations show the so-called load-bearing chains (LBCs) of chemically cross-linked monomers and modified nanoparticles to determine the mechanical properties of the simulated composites. The introduction of nanoparticles leads to the breaking of such chains, and the chemical cross-linking of NPs with the polymer matrix restores the LBCs and strengthens the composite. At small values of RGC, the largest value of the elastic modulus is found for systems filled with nanoparticles having the smallest surface area, and at high values of RGC, on the contrary, the systems containing disk-shaped particles with the largest surface area have a larger elastic modulus than the others. All calculations are performed within the framework of a mesoscopic model based on accurate mapping of the atomistic structures of the polymer matrix and nanoparticles into coarse-grained representations, which, if necessary, allow reverse data mapping and quantitative assessment of the state of the filled epoxy resin. On the other hand, the obtained data can be used to design the functional materials with specified mechanical properties based on other practically significant polymer matrices and nanofillers.

Selective dispersion of neutral nanoplates and the interfacial structure of copolymers based on coarse-grained molecular dynamics simulations

The selective dispersion of neutral nanoplates (NNP) and the control of the interfacial structure of copolymers are challenging. In this work, we employ coarse-grained molecular dynamics (CGMD) to investigate the dispersion of NNP and the interfacial structure. The introduction of NNP significantly changes the interfacial structure and formation mechanism of diblock copolymers (DBCP), which is related to the matrix phase, distribution, composition, and length of two different chain segments (A and B) in A_mB_n-DBCP. The phase-weak groups that have a poor interaction with NNP will stack easily, whereas the stacking degree for the phase-rich groups that have a strong interaction with NNP decreases due to the addition of NNP. The interaction between two phases will be enhanced, which is favorable for the formation of a random network structure. Due to the strong interaction of the phase-rich groups with NNP, the NNP change the accumulation types of phase-weak groups and enhances the combination of two chain segments in favor of the formation of a cylindrical micelle-like structure. The transmission electron microscopy (TEM) images show that layered double hydroxide (LDH) orientationally distributes in the acrylic acid chain segments in ethylene acrylic acid (EAA) random copolymers, which is in agreement with the theoretical simulation results. This proves that the selective dispersion of LDH in copolymers affects their interfacial structure.

Surface Charges Control the Structure and Properties of Layered Nanocomposite of Cellulose Nanofibrils and Clay Platelets

The interfacial bonding and structure at the nanoscale in the polymer-clay nanocomposites are essential for obtaining desirable material and structure properties. Layered nanocomposite films of cellulose nanofibrils (CNFs)/montmorillonite (MTM) were prepared from the water suspensions of either CNFs bearing quaternary ammonium cations (Q-CNF) or CNFs bearing carboxylate groups (TO-CNF) with MTM nanoplatelets carrying net surface negative charges by using vacuum filtration followed by compressive drying. The effect of the ionic interaction between cationic or anionic charged CNFs and MTM nanoplatelets on the structure, mechanical properties, and flame retardant performance of the TO-CNF/MTM and Q-CNF/MTM nanocomposite films were studied and compared. The MTM nanoplatelets were well dispersed in the network of TO-CNFs in the form of nanoscale tactoids with the MTM content in the range of 5-70 wt %, while an intercalated structure was observed in the Q-CNF/MTM nanocomposites. The resulting TO-CNF/MTM nanocomposite films had a better flame retardant performance as compared to the Q-CNF/MTM films with the same MTM content. In addition, the effective modulus of MTM for the TO-CNF/MTM nanocomposites was as high as 129.9 GPa, 3.5 times higher than that for Q-CNF/MTM (37.1 GPa). On the other hand, the Q-CNF/MTM nanocomposites showed a synergistic enhancement in the modulus and tensile strength together with strain-to-failure and demonstrated a much better toughness as compared to the TO-CNF/MTM nanocomposites.

From digital hype to analogue reality: Universal simulation beyond the quantum and exascale eras

Many believe that the future of innovation lies in simulation. However, as computers are becoming ever more powerful, so does the hyperbole used to discuss their potential in modelling across a vast range of domains, from subatomic physics to chemistry, climate science, epidemiology, economics and cosmology. As we are about to enter the era of quantum and exascale computing, machine learning and artificial intelligence have entered the field in a significant way. In this article we give a brief history of simulation, discuss how machine learning can be more powerful if underpinned by deeper mechanistic understanding, outline the potential of exascale and quantum computing, highlight the limits of digital computing - classical and quantum - and distinguish rhetoric from reality in assessing the future of modelling and simulation, when we believe analogue computing will play an increasingly important role.

Principles Governing Control of Aggregation and Dispersion of Graphene and Graphene Oxide in Polymer Melts

Controlling the structure of graphene and graphene oxide (GO) phases is vitally important for any of its widespread intended applications: highly ordered arrangements of nanoparticles are needed for thin-film or membrane applications of GO, dispersed nanoparticles for composite materials, and 3D porous arrangements for hydrogels. By combining coarse-grained molecular dynamics and newly developed accurate models of GO, the driving forces that lead to the various morphologies are resolved. Two hydrophilic polymers, poly(ethylene glycol) (PEG) and poly(vinyl alcohol) (PVA), are used to illustrate the thermodynamically stable morphologies of GO and relevant dispersion mechanisms. GO self-assembly can be controlled by changing the degree of oxidation, varying from fully aggregated over graphitic domains to intercalated assemblies with polymer bilayers between sheets. The long-term stability of a dispersion is extremely important for many commercial applications of GO composites. For any degree of oxidation, GO does not disperse in PVA as a thermodynamic equilibrium product, whereas in PEG dispersions are only thermodynamically stable for highly oxidized GO. These findings-validated against the extensive literature on GO systems in organic solvents-furnish quantitative explanations for the empirically unpredictable aggregation characteristics of GO and provide computational methods to design directed synthesis routes for diverse self-assemblies and applications.

Rapid and high-concentration exfoliation of montmorillonite into high-quality and mono-layered nanosheets

After montmorillonite (MTM) was first exfoliated into nanosheets as a reinforcing filler in the 1980s, layered clay became a hotspot of interest. However, to date, the exfoliation of the resource-rich and inexpensive layered MTM into high-quality nanosheets still remains a significant challenge. Herein, a simple and effective strategy to exfoliate layered MTM into mono-layered sheets via the aggregation of polyethyl-phosphate glycol ester (Exolit OP 550) is proposed. A significant decrease in exfoliation time from 120 min to 3 min was observed at room temperature only via a gentle stirring process. Moreover, various factors that reduce the viscosity of the mixture could be utilized to boost the exfoliated concentration to a record high value of 100 wt%, which is an increase of 460-2400% compared with that in other works. A tentative model was also proposed to illustrate the exfoliation mechanism based on the detection of segmental confined movement, structural evolution, and polymer-clay interaction. Particularly, the as-observed critical concentration of 200 wt% MTM indicated a saturation effect for the surface-adsorbed polymer. The critical concentration for the onset of exfoliation was 150 wt%. In addition, the structure of the exfoliated nanosheets in Exolit OP 550 underwent a temperature-sensitive and irreversible transformation. Thus, our study may provide new insight for the exfoliation of clay.

Controllable growth of carbon nanosheets in the montmorillonite interlayers for high-rate and stable anode in lithium ion battery

A novel insertable and pseudocapacitive Li⁺ ion material for highly ordered layered montmorillonite/carbon is explored in the present study. The commercially available protonated montmorillonite and 3,3'-diaminobenzidine act as starting materials to synthesize the layered material via hydrothermal intercalation, oxidative polymerization and carbonization. This method of preparing montmorillonite/carbon nanocomposite exhibits several advantages. To be specific, raw materials are low cost and naturally abundant; the montmorillonite can undergo proton exchange easily to form a permutable proton-type material, and the protons in the layered nanocomposite can be directly substituted by the polymerizable molecules (e.g., 3,3'-diaminobenzidine). Accordingly, a sheet-like montmorillonite/carbon layered nanocomposite is achieved with the carbon stacking on the montmorillonite substrate for the intercalation behavior. As revealed from the electrochemical results, montmorillonite/carbon nanocomposite can deliver a high reversible capacity of 1432 mA h g^-1 at 50 mA g^-1 and superior rate capacity of 920 mA h g^-1 at 10 000 mA g^-1 for the lithium ion battery. Furthermore, the full cell with LiFePO₄ as cathode and montmorillonite/carbon as anode maintains 94% capacity retention over 50 cycles as well as high coulombic efficiency.

Pit and fissure nanocomposite sealants reinforced with organically modified montmorillonite: A study of their mechanical properties, surface roughness and color stability

The aim of the present work was to investigate the effect of the different organically modified nanoclays on clinically significant properties of new synthesized dental pit and fissure nanocomposite sealants. Their morphological characteristics were examined by means of X-ray diffraction (XRD) analysis and scanning electron microscopy (SEM). A universal testing machine was used to conduct the flexural and compression tests. Surface roughness measurements were taken by using a 3D-optical profilometer. Color changes after aging in black tea were determined by recording UV-visible spectra. XRD plots depicted possible structures governed by intercalated regions along with some "tactoids" nanoparticles. SEM images revealed a better dispersion for the methacrylated clay nanofiller. Flexural modulus and microhardness were found to be higher for sealants reinforced with such polymerizable nanoclays. These specific nanocomposites yielded smoother surfaces, as well as clinically accepted color changes even after 1 week aging in black tea.

Preparations of Silver/Montmorillonite Biocomposite Multilayers and Their Antifungal Activity

In this study, the results about the influence of the surface morphology of layers based on montmorillonite (MMT) and silver (Ag) on antimicrobial properties are reported. The coating depositions were performed in the plasma of a radio frequency (RF) magnetron sputtering discharge. The studied layers were single montmorillonite layers (MMT) and silver/montmorillonite multilayers (MMT-Ag) obtained by magnetron sputtering technique with a different surface thickness. The resultant MMT-Ag biocomposite multilayers exhibited a uniform distribution of constituent elements and enhanced antimicrobial properties against fungal biofilm development. Glow-discharge optical emission spectroscopy (GDOES) analysis revealed the formation of MMT-Ag biocomposite multilayers following the deposit of a silver layer for an MMT layer that was initially deposited on a Si substrate. The surface morphology and thickness evaluation of deposited biocomposite layers were performed by scanning electron microscopy (SEM). A qualitative analysis of the chemical composition of thin layers was performed and the elements O, Ag, Mg, Fe, Al, and Si were identified in the MMT-Ag biocomposite multilayers. The in vitro antifungal assay proved that the inhibitory effect against the growth of Candida albicans ATCC 101231 CFU was more emphasized in the case of MMT-Ag biocomposite multilayers that in the case of the MMT layer. Cytotoxicity studies performed on HeLa cells showed that the tested layers did not show significant toxicity at the time intervals during which the assay was performed. On the other hand, it was observed that the MMT layers exhibited slightly higher biocompatible properties than the MMT-Ag composite layers.

Martini Coarse-Grained Model for Clay-Polymer Nanocomposites

We have developed a coarse-grained (CG) model of a polymer-clay system consisting of organically modified montmorillonite (oMMT) nanoclay as the nanoparticle in accordance with the MARTINI force field. We have used mechanical properties and cleavage free energy of the clay particle to respectively parameterize bonded and nonbonded interaction parameters for an oMMT clay particle, where intergallery Na⁺ ions are replaced by tetramethylammonium (TMA) ions. The mechanical properties were determined from the slope of the stress-strain curve and cleavage free energy was determined by allowing for full surface reconstruction corresponding to a slow equilibrium cleavage process. Individual dispersive and polar contributions to oMMT cleavage energy were used for determination of appropriate MARTINI bead types for the CG oMMT sheet. The self-consistency of the developed MARTINIFF parameters for the TMA-montmorillonite-polymer system was verified by comparing estimates for select structural, thermodynamic, and dynamic properties obtained in all-atomistic simulations with that obtained in CG simulations. We have determined the influence of clay particles on properties of three polymer melts (polyethylene, polypropylene, and polystyrene) at two temperatures to establish transferability of the developed parameters. We have also shown that the effect of clay-polymer interactions on structure-property relationships in the polymer-clay nanocomposite system is well captured by Rosenfeld's excess entropy scaling.

The heterogeneous multiscale method applied to inelastic polymer mechanics

Mechanisms emerging across multiple scales are ubiquitous in physics and methods designed to investigate them are becoming essential. The heterogeneous multiscale method (HMM) is one of these, concurrently simulating the different scales while keeping them separate. Owing to the significant computational expense, developments of HMM remain mostly theoretical and applications to physical problems are scarce. However, HMM is highly scalable and is well suited for high performance computing. With the wide availability of multi-petaflop infrastructures, HMM applications are becoming practical. Rare applications to mechanics of materials at low loading amplitudes exist, but are generally confined to the elastic regime. Beyond that, where history-dependent, irreversible or nonlinear mechanisms occur, not only computational cost but also data management issues arise. The micro-scale description loses generality, developing a specific microstructure based on the deformation history, which implies inter alia that as many microscopic models as discrete locations in the macroscopic description must be simulated and stored. Here, we present a detailed description of the application of HMM to inelastic mechanics of materials, with emphasis on the efficiency and accuracy of the scale-bridging methodology. The method is well suited to the estimation of macroscopic properties of polymers (and derived nanocomposites) starting from knowledge of their atomistic chemical structure. Through application of the resulting workflow to polymer fracture mechanics, we demonstrate deviation in the predicted fracture toughness relative to a single-scale molecular dynamics approach, thus illustrating the need for such concurrent multiscale methods in the predictive estimation of macroscopic properties. This article is part of the theme issue 'Multiscale modelling, simulation and computing: from the desktop to the exascale'.

Multiscale computing for science and engineering in the era of exascale performance

In this position paper, we discuss two relevant topics: (i) generic multiscale computing on emerging exascale high-performing computing environments, and (ii) the scaling of such applications towards the exascale. We will introduce the different phases when developing a multiscale model and simulating it on available computing infrastructure, and argue that we could rely on it both on the conceptual modelling level and also when actually executing the multiscale simulation, and maybe should further develop generic frameworks and software tools to facilitate multiscale computing. Next, we focus on simulating multiscale models on high-end computing resources in the face of emerging exascale performance levels. We will argue that although applications could scale to exascale performance relying on weak scaling and maybe even on strong scaling, there are also clear arguments that such scaling may no longer apply for many applications on these emerging exascale machines and that we need to resort to what we would call multi-scaling. This article is part of the theme issue 'Multiscale modelling, simulation and computing: from the desktop to the exascale'.

Mastering the scales: a survey on the benefits of multiscale computing software

In the last few decades, multiscale modelling has emerged as one of the dominant modelling paradigms in many areas of science and engineering. Its rise to dominance is primarily driven by advancements in computing power and the need to model systems of increasing complexity. The multiscale modelling paradigm is now accompanied by a vibrant ecosystem of multiscale computing software (MCS) which promises to address many challenges in the development of multiscale applications. In this paper, we define the common steps in the multiscale application development process and investigate to what degree a set of 21 representative MCS tools enhance each development step. We observe several gaps in the features provided by MCS tools, especially for application deployment and the preparation and management of production runs. In addition, we find that many MCS tools are tailored to a particular multiscale computing pattern, even though they are otherwise application agnostic. We conclude that the gaps we identify are characteristic of a field that is still maturing and features that enhance the deployment and production steps of multiscale application development are desirable for the long-term success of MCS in its application fields.

This article is part of the theme issue ‘Multiscale modelling, simulation and computing: from the desktop to the exascale’.

Micromechanical exfoliation of graphene on the atomistic scale

Mechanical exfoliation techniques are widely used to create high quality graphene samples for analytical use. Increasingly, mechanical methods are used to create large quantities of graphene, yet there is surprisingly little molecular insight into the mechanisms involved. We study the exfoliation of graphene with sticky tape using molecular dynamics. This is made possible by using a recently developed molecular dynamics forcefield, GraFF, to represent graphene's dispersion interactions. For nano-sized flakes we observe two different mechanisms depending on the polymer-adhesive used. A peeling mechanism which mixes shearing and normal mode exfoliation promotes synthesis of graphene rather than many-layered graphite. Armed with this new chemical insight we discuss the experimental methods that could preferentially produce graphene by mechanical exfoliation. We also introduce a mathematical model describing the repeated exfoliation of graphite.

The structure-property relationship in LAPONITE® materials: from Wigner glasses to strong self-healing hydrogels formed by non-covalent interactions

Rheology, small-angle X-ray scattering (SAXS), and dynamic light scattering (DLS) analysis, zeta potential measurement, scanning electron microscopy (SEM), and micro-FTIR and absorbance spectroscopy were used to enlighten the controversial literature about LAPONITE® materials. Our data suggest that pristine LAPONITE® in water does not form hydrogels induced by the so-called "house of cards" assembly, but rather forms Wigner glasses governed by repulsive forces. Ionic interactions between anisotropic LAPONITE® nanodiscs, sodium polyacrylate and inorganic salts afforded hydrogels that were transparent, self-standing, moldable, strong, and biocompatible with shear-thinning and self-healing behavior. An extensive study on the role of salts in the gelification process dictates a trend that relates the valence of cations with the viscoelastic properties of the bulk material (G' values follow the trend, monovalent < divalent < trivalent). These hydrogels present G' values up to 5.1 × 104 Pa, which are considered high values for non-covalent hydrogels. Hydrogels crosslinked with sodium phosphate salts are biocompatible, and might be valid candidates for injectable drug delivery systems due to their shear-thinning behavior with rapid self-healing after injection.

Chemically Specific Multiscale Modeling of the Shear-Induced Exfoliation of Clay-Polymer Nanocomposites

We recently showed, using chemically specific modeling and simulation, how the process of intercalation of polymers within clay sheets occurs, transforming the large-scale materials properties by a specific set of spatial and temporal processes that can lead to exfoliation. Here, we use the same hierarchal multiscale modeling scheme to understand the processes that occur during the shear-induced processing of clay-polymer nanocomposites. For both hydrophobic polymers (polyethylene) and hydrophilic polymers (poly(ethylene glycol)), we used free-energy methods to identify the lowest-free-energy separation of the clay sheets; the polymer molecules spontaneously intercalate into the clay interlayer from the surrounding polymer melt. We apply shear forces to investigate exfoliation and find that while exfoliation is promoted by shearing, it is the surfactant molecules that play the dominant role in resisting it.

Polymer-Based Black Phosphorus (bP) Hybrid Materials by in Situ Radical Polymerization: An Effective Tool To Exfoliate bP and Stabilize bP Nanoflakes

Black phosphorus (bP) has been recently investigated for next generation nanoelectronic multifunctional devices. However, the intrinsic instability of exfoliated bP (the bP nanoflakes) toward both moisture and air has so far overshadowed its practical implementation. In order to contribute to fill this gap, we report here the preparation of new hybrid polymer-based materials where bP nanoflakes (bPn) exhibit a significantly improved stability. The new materials have been prepared by different synthetic paths including: (i) the mixing of conventionally liquid-phase exfoliated bP (in dimethyl sulfoxide, DMSO) with poly(methyl methacrylate) (PMMA) solution; (ii) the direct exfoliation of bP in a polymeric solution; (iii) the in situ radical polymerization after exfoliating bP in the liquid monomer (methyl methacrylate, MMA). This last methodology concerns the preparation of stable suspensions of bPn-MMA by sonication-assisted liquid-phase exfoliation (LPE) of bP in the presence of MMA followed by radical polymerization. The hybrids characteristics have been compared in order to evaluate the bP dispersion and the effectiveness of the bPn interfacial interactions with polymer chains aimed at their long-term environmental stabilization. The passivation of the bPn is particularly effective when the hybrid material is prepared by in situ polymerization. By using this synthetic methodology, the nanoflakes, even if with a gradient of dispersion (size of aggregates), preserve their chemical structure from oxidation (as proved by both Raman and 31P-solid state NMR studies) and are particularly stable to air and UV light exposure. The feasibility of this approach, capable of efficiently exfoliating bP while protecting the bPn, has been then verified by using different vinyl monomers (styrene and N-vinylpyrrolidone), thus obtaining hybrids where the nanoflakes are embedded in polymer matrices with a variety of intriguing thermal, mechanical, and solubility characteristics.

A generalized simulation development approach for predicting refugee destinations

In recent years, global forced displacement has reached record levels, with 22.5 million refugees worldwide. Forecasting refugee movements is important, as accurate predictions can help save refugee lives by allowing governments and NGOs to conduct a better informed allocation of humanitarian resources. Here, we propose a generalized simulation development approach to predict the destinations of refugee movements in conflict regions. In this approach, we synthesize data from UNHCR, ACLED and Bing Maps to construct agent-based simulations of refugee movements. We apply our approach to develop, run and validate refugee movement simulations set in three major African conflicts, estimating the distribution of incoming refugees across destination camps, given the expected total number of refugees in the conflict. Our simulations consistently predict more than 75% of the refugee destinations correctly after the first 12 days, and consistently outperform alternative naive forecasting techniques. Using our approach, we are also able to reproduce key trends in refugee arrival rates found in the UNHCR data.

Hydroxyl-triggered fluorescence for location of inorganic materials in polymer-matrix composites

We present a locating technique for inorganic materials in polymer-matrix composites through a post-labeling approach based on specific covalent binding.

There is a long-standing challenge to realize in situ visualization of incorporated inorganic materials in organic–inorganic composites in a post-labeling manner, owing to the lack of specific fluorescent organic dye molecules for targeting inorganic materials. Herein, we observe that the specific covalent B–O binding between the hydroxyl groups of inorganic materials and commercially available aggregation-induced emission (AIE)-active boronic acid could lead to the formation of highly emissive solid-state fluorescent composite materials. The hydroxyl-triggered luminescent probe may serve as a practical method for in situ location of incorporated inorganic materials in polymer-matrix composites by simply dipping the composite film in boronic acid-modified AIE solution. This present work offers a non-invasive avenue to locate inorganic materials which possess hydroxyl-groups in polymer-matrix composites, thereby developing a convenient screening strategy for assessing the advanced properties of composites. This strategy can also be extended to the targeted tracing of other inorganic materials with inherent and functionalized carboxyl, amino, sulfhydryl and other groups via tuning the binding affinity between the inorganic materials and luminescent molecules.

Thermodynamic Mechanism and Interfacial Structure of Kaolinite Intercalation and Surface Modification by Alkane Surfactants with Neutral and Ionic Head Groups

Intercalation and surface modification of clays with surfactants are the essential process to tailor the clays' surface chemistry for their extended applications. A full understanding of the interaction mechanism of surfactants with clay surfaces is crucial to engineer clay surfaces for meeting a particular requirement of industrial applications. In this study, the thermodynamic mechanism involved in the intercalation and surface modification of methanol preintercalated kaolinite by three representative alkane surfactants with different head groups, dodecylamine, cetyltrimethylammonium chloride (CTAC), and sodium stearate, were investigated using the adaptive biasing force accelerated molecular dynamics simulations. In addition, the interaction energies of surfactants with an interlayer environment (alumina surface, siloxane surface, and interlayer methanol) of methanol preintercalated kaolinite were also calculated. It was found that the intercalation free energy of CTAC with a cationic head group was relatively larger than that of stearate with an anionic head group and dodecylamine with a neutral head group. The attractive electrostatic and van der Waals interactions of surfactants with an interlayer environment contributed to the intercalation and surface modification process with the electrostatic force playing the significant role. This study revealed the underlying mechanism involved in the intercalation and surface modification process of methanol preintercalated kaolinite by surfactants, which can help in further design of kaolinite-based organic clays with desired properties for specific applications.

A Review of Multiscale Computational Methods in Polymeric Materials

Polymeric materials display distinguished characteristics which stem from the interplay of phenomena at various length and time scales. Further development of polymer systems critically relies on a comprehensive understanding of the fundamentals of their hierarchical structure and behaviors. As such, the inherent multiscale nature of polymer systems is only reflected by a multiscale analysis which accounts for all important mechanisms. Since multiscale modelling is a rapidly growing multidisciplinary field, the emerging possibilities and challenges can be of a truly diverse nature. The present review attempts to provide a rather comprehensive overview of the recent developments in the field of multiscale modelling and simulation of polymeric materials. In order to understand the characteristics of the building blocks of multiscale methods, first a brief review of some significant computational methods at individual length and time scales is provided. These methods cover quantum mechanical scale, atomistic domain (Monte Carlo and molecular dynamics), mesoscopic scale (Brownian dynamics, dissipative particle dynamics, and lattice Boltzmann method), and finally macroscopic realm (finite element and volume methods). Afterwards, different prescriptions to envelope these methods in a multiscale strategy are discussed in details. Sequential, concurrent, and adaptive resolution schemes are presented along with the latest updates and ongoing challenges in research. In sequential methods, various systematic coarse-graining and backmapping approaches are addressed. For the concurrent strategy, we aimed to introduce the fundamentals and significant methods including the handshaking concept, energy-based, and force-based coupling approaches. Although such methods are very popular in metals and carbon nanomaterials, their use in polymeric materials is still limited. We have illustrated their applications in polymer science by several examples hoping for raising attention towards the existing possibilities. The relatively new adaptive resolution schemes are then covered including their advantages and shortcomings. Finally, some novel ideas in order to extend the reaches of atomistic techniques are reviewed. We conclude the review by outlining the existing challenges and possibilities for future research.

Big data need big theory too

The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their 'depth' and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote 'blind' big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

Systematic comparison of model polymer nanocomposite mechanics

Polymer nanocomposites render a range of outstanding materials from natural products such as silk, sea shells and bones, to synthesized nanoclay or carbon nanotube reinforced polymer systems. In contrast to the fast expanding interest in this type of material, the fundamental mechanisms of their mixing, phase behavior and reinforcement, especially for higher nanoparticle content as relevant for bio-inorganic composites, are still not fully understood. Although polymer nanocomposites exhibit diverse morphologies, qualitatively their mechanical properties are believed to be governed by a few parameters, namely their internal polymer network topology, nanoparticle volume fraction, particle surface properties and so on. Relating material mechanics to such elementary parameters is the purpose of this work. By taking a coarse-grained molecular modeling approach, we study an range of different polymer nanocomposites. We vary polymer nanoparticle connectivity, surface geometry and volume fraction to systematically study rheological/mechanical properties. Our models cover different materials, and reproduce key characteristics of real nanocomposites, such as phase separation, mechanical reinforcement. The results shed light on establishing elementary structure, property and function relationship of polymer nanocomposites.

Cartilage-inspired superelastic ultradurable graphene aerogels prepared by the selective gluing of intersheet joints

In this study, we demonstrate a cartilage-inspired superelastic and ultradurable nanocomposite strategy for the selective inclusion of viscoelastic poly(dimethylsiloxane) (PDMS) into graphene sheet junctions to create effective stress-transfer pathways within three-dimensional (3D) graphene aerogels (GAs). Inspired by the joint architectures in the human body, where small amounts of soft cartilage connect stiff (or hard) but hollow (and thus lightweight) bones, the 3D internetworked GA@PDMS achieves synergistic toughening. The resulting GA@PDMS nanocomposites exhibit fully reversible structural deformations (99.8% recovery even at a 90% compressive strain) and high compressive mechanical strength (448.2 kPa at a compressive strain of 90%) at repeated compression cycles. Owing to the combination of excellent mechanical and electrical properties, the GA@PDMS nanocomposites are used as signal transducers for strain sensors, showing very short response and recovery times (in the millisecond range) with reliable sensitivity and extreme durability. Furthermore, the proposed system is applied to electronic scales with a large detectable weight of about 4600 times greater than its own weight. Such bio-inspired cartilage architecture opens the door to fabricate new 3D multifunctional and mechanically durable nanocomposites for emerging applications, which include sensors, actuators, and flexible devices.

Fluorescence microscopy as an alternative to electron microscopy for microscale dispersion evaluation of organic-inorganic composites

Inorganic dispersion is of great importance for actual implementation of advanced properties of organic-inorganic composites. Currently, electron microscopy is the most conventional approach for observing dispersion of inorganic fillers from ultrathin sections of organic-inorganic composites at the nanoscale by professional technicians. However, direct visualization of macrodispersion of inorganic fillers in organic-inorganic composites using high-contrast fluorescent imaging method is hampered. Here we design and synthesize a unique fluorescent surfactant, which combines the properties of the aggregation-induced emission (AIE) and amphiphilicity, to image macrodispersion of montmorillonite and layered double hydroxide fillers in polymer matrix. The proposed fluorescence imaging provides a number of important advantages over electron microscope imaging, and opens a new avenue in the development of direct three-dimensional observation of inorganic filler macrodispersion in organic-inorganic composites.

Simulations of inorganic-bioorganic interfaces to discover new materials: insights, comparisons to experiment, challenges, and opportunities

Natural and man-made materials often rely on functional interfaces between inorganic and organic compounds. Examples include skeletal tissues and biominerals, drug delivery systems, catalysts, sensors, separation media, energy conversion devices, and polymer nanocomposites. Current laboratory techniques are limited to monitor and manipulate assembly on the 1 to 100 nm scale, time-consuming, and costly. Computational methods have become increasingly reliable to understand materials assembly and performance. This review explores the merit of simulations in comparison to experiment at the 1 to 100 nm scale, including connections to smaller length scales of quantum mechanics and larger length scales of coarse-grain models. First, current simulation methods, advances in the understanding of chemical bonding, in the development of force fields, and in the development of chemically realistic models are described. Then, the recognition mechanisms of biomolecules on nanostructured metals, semimetals, oxides, phosphates, carbonates, sulfides, and other inorganic materials are explained, including extensive comparisons between modeling and laboratory measurements. Depending on the substrate, the role of soft epitaxial binding mechanisms, ion pairing, hydrogen bonds, hydrophobic interactions, and conformation effects is described. Applications of the knowledge from simulation to predict binding of ligands and drug molecules to the inorganic surfaces, crystal growth and shape development, catalyst performance, as well as electrical properties at interfaces are examined. The quality of estimates from molecular dynamics and Monte Carlo simulations is validated in comparison to measurements and design rules described where available. The review further describes applications of simulation methods to polymer composite materials, surface modification of nanofillers, and interfacial interactions in building materials. The complexity of functional multiphase materials creates opportunities to further develop accurate force fields, including reactive force fields, and chemically realistic surface models, to enable materials discovery at a million times lower computational cost compared to quantum mechanical methods. The impact of modeling and simulation could further be increased by the advancement of a uniform simulation platform for organic and inorganic compounds across the periodic table and new simulation methods to evaluate system performance in silico.

Mechanism of Exfoliation and Prediction of Materials Properties of Clay-Polymer Nanocomposites from Multiscale Modeling

We describe the mechanism that leads to full exfoliation and dispersion of organophilic clays when mixed with molten hydrophilic polymers. This process is of fundamental importance for the production of clay-polymer nanocomposites with enhanced materials properties. The chemically specific nature of our multiscale approach allows us to probe how chemistry, in combination with processing conditions, produces such materials properties at the mesoscale and beyond. In general agreement with experimental observations, we find that a higher grafting density of charged quaternary ammonium surfactant ions promotes exfoliation, by a mechanism whereby the clay sheets slide transversally over one another. We can determine the elastic properties of these nanocomposites; exfoliated and partially exfoliated morphologies lead to substantial enhancement of the Young's modulus, as found experimentally.