It is a great challenge to fully understand the microscopic dispersion and aggregation of nanoparticles (NPs) in polymer nanocomposites (PNCs) through experimental techniques. Here, coarse-grained molecular dynamics is adopted to study the dispersion and aggregation mechanisms of spherical NPs in polymer melts. By tuning the polymer-filler interaction in a wide range at both low and high filler loadings, we qualitatively sketch the phase behavior of the PNCs and structural spatial organization of the fillers mediated by the polymers, which emphasize that a homogeneous filler dispersion exists just at the intermediate interfacial interaction, in contrast with traditional viewpoints. The conclusion is in good agreement with the theoretically predicted results from Schweizer et al. Besides, to mimick the experimental coarsening process of NPs in polymer matrixes (ACS Nano 2008, 2, 1305), by grafting polymer chains on the filler surface, we obtain a good filler dispersion with a large interparticle distance. Considering the PNC system without the presence of chemical bonding between the NPs and the grafted polymer chains, the resulting good dispersion state is further used to investigate the effects of the temperature, polymer-filler interaction, and filler size on the filler aggregation process. It is found that the coarsening or aggregation process of the NPs is sensitive to the temperature, and the aggregation extent reaches the minimum in the case of moderate polymer-filler interaction, because in this case a good dispersion is obtained. That is to say, once the filler achieves a good dispersion in a polymer matrix, the properties of the PNCs will be improved significantly, because the coarsening process of the NPs will be delayed and the aging of the PNCs will be slowed.

By tuning the polymer-filler interaction, filler size and filler loading, we use a coarse-grained model-based molecular dynamics simulation to study the polymer-filler interfacial structural (the orientations at the bond, segment and chain length scales, chain size and conformation), dynamic and stress-strain properties. Simulated results indicate that the interfacial region is composed of partial segments of different polymer chains, which is consistent with the experimental results presented by Chen et al. (Macromolecules, 2010, 43, 1076). Moreover, it is found that the interfacial region is within one single chain size (R(g)) range, irrespective of the polymer-filler interaction and the filler size, beyond which the bulk behavior appears. In the interfacial region, the orientation and dynamic behaviors are induced by the interfacial enthalpy, while the size and conformation of polymer chains near the filler are controlled by the configurational entropy. In the case of strong polymer-filler interaction (equivalent to the hydrogen bond), the innerest adsorbed polymer segments still undergo adsorption-desorption process, the transport of chain mass center in the interfacial region exhibits away from the glassy behavior, and no plastic-like yielding point appears in the stress-strain curve, which indicates that although the mobility of interfacial polymer chains is restricted, there exist no "polymer glassy layers" surrounding the filler. In addition, it is evidenced that the filler particle prefers selectively adsorbing the long polymer chains for attractive polymer-filler interaction, validating the experimental explanation of the change of the bound rubber (BR). In short, this work provides important information for further experimental and simulation studies of polymer-nanoparticle interfacial behavior.

Among all carbon nanostructured materials, helical nanosprings or nanocoils have attracted particular interest as a result of their special mechanical behavior. Here, carbon nanosprings are used to adjust the viscoelasticity and reduce the resulting hysteresis loss (HL) of elastomeric polymer materials. Two types of nanospring‐filled elastomer composites are constructed as follows: system I is obtained by directly blending polymer chains with nanosprings; system II is composed of the self‐assembly of a tri‐block structure such as chain‐nanospring‐chain. Coarse‐grained molecular dynamics simulations show that the incorporation of nanosprings can improve the mechanical strength of the elastomer matrix through nanoreinforcement and considerably decrease the hysteresis loss. This finding is significant for reducing fuel consumption and improving fuel efficiency in the automobile tire industry. Furthermore, it is revealed that the spring constant of nanosprings and the interfacial chemical coupling between chains and nanosprings both play crucial roles in adjusting the viscoelasticity of elastomers. It is inferred that elastomer/carbon nanostructured materials with good flexibility and reversible mechanical response (carbon nanosprings, nanocoils, nanorings, and thin graphene sheets) have both excellent mechanical and low HL properties; this may open a new avenue for fabrication of high performance automobile tires and facilitate the large‐scale industrial application of these materials.

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Through coarse-grained molecular dynamics simulations, we have studied the effects of grafting density (Σ) and grafted chain length (Lg) on the structural, mechanical and visco-elastic properties of end-grafted nanoparticles (NPs) filled polymer nanocomposites (PNCs). It is found that increasing the grafting density and grafted chain length both enhance the brush/matrix interface thickness and improve the dispersion of NPs, but there seems to exist an optimum grafting density, above which the end-grafted NPs tend to aggregate. The uniaxial stress-strain behavior of PNCs is also examined, showing that the tensile stress is more enhanced by increasing Lg compared to increasing Σ. The tensile modulus as a function of the strain is fitted following our previous work (Soft Matter, 2014, 10, 5099), exhibiting a gradually reduced non-linearity with the increase of Σ and Lg. Meanwhile, by imposing a sinusoidal external shear strain, for the first time we probe the effects of Σ and Lg on the visco-elastic properties such as the storage modulus G', loss modulus G'' and loss factor tan δ of end-grafted NPs filled PNCs. It is shown that the non-linear relation of G' and G'' as a function of shear strain amplitude decreases with the increase of Σ and Lg, which is consistent with experimental observations. We infer that the increased mechanical and reduced non-linear visco-elastic properties are correlated with the enhanced brush/matrix interface and therefore better dispersion of NPs and stronger physical cross-linking. This work may provide some rational means to tune the mechanical and visco-elastic properties of end-grafted NPs filled polymer nanocomposites.

Achieving energy sustainability has imposed a great challenge to improve fuel efficient vehicles. Tires, to overcome the rolling resistance, are responsible for a rather large fraction of energy consumed by vehicles, and a 10% reduction in the rolling resistance corresponds to a 2% decline in the fuel consumption, which, for instance, would save 1 to 2 billion gallon of fuel per year consumed by the entire passenger vehicle fleet in the United States. From the materials' perspective, the key bottleneck to lower the rolling resistance of tires lies in designing a novel kind of advanced elastomeric polymer nanocomposites tailored for tire tread, with remarkably low dynamic hysteresis loss (DHL). Here we show that, a nanoparticle chemically end-linking elastomer network, with nanoparticles (NPs) acting as netpoints to chemically connect the dual end-groups of each polymer chain to form a network, exhibits excellent static and dynamic mechanical properties of super-low DHL. The DHL is reduced for ~50% compared to silica NPs filled elastomer that is conventionally used for tire tread. By taking advantage of a library of other

By employing reverse nonequilibrium molecular dynamics simulations in a full atomistic resolution, the effect of surface-grafted chains on the thermal conductivity of graphene-polyamide-6.6 (PA) nanocomposites has been investigated. The interfacial thermal conductivity perpendicular to the graphene plane is proportional to the grafting density, while it first increases and then saturates with the grafting length. Meanwhile, the intrinsic in-plane thermal conductivity of graphene drops sharply as the grafting density increases. The maximum overall thermal conductivity of nanocomposites appears at an intermediate grafting density because of these two competing effects. The thermal conductivity of the composite parallel to the graphene plane increases with the grafting density and grafting length which is attributed to better interfacial coupling between graphene and PA. There exists an optimal balance between grafting density and grafting length to obtain the highest interfacial and parallel thermal conductivity. Two empirical formulas are suggested, which quantitatively account for the effects of grafting length and density on the interfacial and parallel thermal conductivity. Combined with effective medium approximation, for ungrafted graphene in random orientation, the model overestimates the thermal conductivity at low graphene volume fraction (f < 10%) compared with experiments, while it underestimates it at high graphene volume fraction (f > 10%). For unoriented grafted graphene, the model matches the experimental results well. In short, this work provides some valuable guides to obtain the nanocomposites with high thermal conductivity by grafting chain on the surface of graphene.

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube–polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa–1) and a broad response range (0–18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices.