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A facile and efficient approach was developed to simultaneously functionalize and tune the reduction state of graphene oxide (GO) with γ-aminopropyl triethoxysilane (APTES) aided by NH3 solution. X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy indicated that many surface groups of GO sheets were removed, and APTES were successfully functionalized onto GO sheets. The APTES-functionalized GO sheets (GO-APTES) were dispersed in water and further incorporated into nitrile butadiene rubber (NBR) by latex co-coagulation to form GO-APTES/NBR composites. These composites featured high degrees of exfoliation and intercalation of GO-APTES sheets throughout the NBR matrix. More significantly, the GO-APTES/NBR composites exhibited a relatively high dielectric constant (∼30.8) and a small loss factor (

A combined experimental and computational approach is applied to amorphous polycarbonates (PCs) to link the macroscopic behavior and molecular features. The Simha–Somcynsky equation of phase (EOS) provides a more accurate description than the Tait EOS for describing the pressure–volume–temperature (PVT) relationship and thermal expansivity. The relationship between the specific volume and the hole free volume was investigated using PVT measurements, positron annihilation lifetime spectra, and molecular dynamics (MD) techniques, to examine the correlations between changes in the behavior of specific volume and molecular packing. We found that the specific volume and hole free volume have linear relationships with temperature. However, the occupied volume displayed remarkable compressibility. The analyses revealed that the PC with side methyl groups and long C–Si bonds contributed to the formation of large free volume. The MD results validate the effectiveness of molecular simulation techniques in designing...

Background/Purpose Rubber nanocomposites have been widely used in many engineering fields due to their unique properties such as high elasticity and viscoelasticity. Much attention has been paid to the viscoelasticity of rubbers because it directly relates to the performance of the rubber products. Methods Based on the micromechanical theory, the finite element method is used to analyze the effect of elastic modulus and volume content of spring-shape nanofillers on the dynamic viscosity of composites. Results The simulation results show that there is an optimal elastic modulus of spring-shape nanofillers to make the loss factor a minimum. There is a threshold value of spring-shape nanofiller content for the dissipation energy density of composite. Conclusion The elastic modulus of spring-shape nanofillers has a large effect on the loss factor of composites. The selection of elastic modulus of spring-shape nanofillers is critical for applications of composites. The efficiency of spring-shape nanofillers in reducing the dynamic viscosity of composites is so high that volume content of spring-shape nanofillers as low as 0.1% can greatly reduce the loss factor of composites with bonding interface.

The effect of organophosphorus (OP) content on the flame retardancy and the flame retardancy mode of thermoplastic polyurethane (TPU) are reported. The limiting oxygen index (LOI) value for TPU increased from 23.1% to 24.6% and 33.5% by adding 20 wt% and 40 wt% of OP, respectively. UL-94 test showed V-2 rating for pure TPU, and V-1 rating and V-0 rating for the blends with 20 wt% and 40 wt% of OP, respectively. Potential reasons for the improved flame retardancy of TPU blends with increasing OP content were discussed based on the morphology of the char layers resulting from the combustion of TPU blends. The gas phase flame retardancy mode dominated in the composite with 20 wt% of OP by forming a loose, thin, and breakable porous char layer. The condensed phase charring mode dominated for the composite with 40 wt% of OP by forming a continuous, thicker, and denser char layer during combustion, which acted as a more effective barrier to reduce heat feedback to the polymer surface and thus resulted in the better flame retardancy. This study indicated for the first time that the content of flame retardant plays an important role in the flame retardancy mode of OP for TPU.

An artificial neural network (ANN) based on an improved radial basis function (RBF) was established to predict the stress relaxation property of diene rubber composites during ozone aging. The compression ratio, ozone concentration, ozonation time, and rubber type were used as the input vectors, and the stress relaxation coefficient (F/F0) was used as the output vector. Regularization was introduced into the RBF ANN, and the average prediction accuracy of the established ANN for three types of diene rubber was 98.1%. Compared with back-propagation (BP) ANN, the proposed model displays better prediction performance. Moreover, a sensitivity analysis based on the analytical expression generated by the RBF indicates that compression ratio is the most important factor affecting the stress relaxation response. The RBF prediction shows that rubber under a high compression ratio possesses a higher F/F0 than that under a low compression ratio in the range of 25% to 35%, indicating that highly compressed rubber experiences a low degree of ozone attack. Analysis of the relationship between the microstructure and the stress relaxation property of the polymer reveals that application of a high compression ratio reduces the free volume and degree of cracks and that rubber under a high compression ratio has high ozone resistance. This finding is in agreement with the above RBF prediction. Comparisons between the RBF model predictions and the experimental data indicate that the well-trained model provides a deep understanding of the stress relaxation property and has the potential to guide development of materials highly resistant to ozonation.

Thermoplastic vulcanizates (TPVs) have attracted considerable attention as typical “green” polymers in recent years and have been widely used in industry because they combine the excellent resilien...

A combined study of experimental and molecular dynamics (MD) simulation methods is presented for hindered phenol AO-80/nitrile-butadiene rubber/poly(vinyl chloride) (AO-80/NBR/PVC) composites with different AO-80 contents to establish the microstructure-damping property relations. MD simulation found that the AO-80/NBR/PVC composite (abbreviated as AO-80/NBVC) with an AO-80 content of 99 phr had the largest hydrogen bonds (H-bonds) and highest binding energy, indicating a good compatibility between NBR and AO-80 and good damping performance of AO-80/NBVC composites. Experimental results from SEM, DSC, and DMA were in good agreement with the MD simulation results. The tensile test results showed that the AO-80/NBVC composite with an AO-80 content of 99 phr had high tensile strength because of the strong H-bonds of the composites and the disintegration and reintegration of the H-bonds. The MD simulation technique proves to be a promising tool for the design and prediction of high damping properties of advanced composites in a microscopic view.

Natural rubber (NR) composites highly filled with nano-α-alumina (nano-α-Al2O3) modified in situ by the silane coupling agent bis-(3-triethoxysilylpropyl)-tetrasulfide (Si69) were prepared. The effects of various modification conditions and filler loading on the properties of the nano-α-Al2O3/NR composites were investigated. The results indicated that the preparation conditions for optimum mechanical (both static and dynamic) properties and thermal conductivity were as follows: 100 phr of nano-α-Al2O3, 6 phr of Si69, heat-treatment time of 5 min at 150°C. Furthermore, two other types of fillers were also investigated as thermally conductive reinforcing fillers for the NR systems: (1) hybrid fillers composed of 100 phr of nano-α-Al2O3 and various amounts of the carbon black (CB) N330 and (2) nano-γ-Al2O3, the particles of which are smaller than those of nano-α-Al2O3. The hybrid fillers had better mechanical properties and dynamic performance with higher thermal conductivity, which means that it can be expected to endow the rubber products serving under dynamic conditions with much longer service life. The smaller sized nano-γ-Al2O3 particles performed better than the larger-sized nano-α-Al2O3 particles in reinforcing NR. However, the composites filled with nano-γ-Al2O3 had lower thermal conductivity than those filled with nano-α-Al2O3 and badly deteriorated dynamic properties at loadings higher than 50 phr, both indicating that nano-γ-Al2O3 is not a good candidate for novel thermally conductive reinforcing filler. POLYM. COMPOS., 2014. © 2014 Society of Plastics Engineers

The effect of the acrylonitrile content in nitrile-butadiene rubber (NBR) on the compatibility and damping properties of AO-60/NBR was investigated by molecular dynamics (MD) simulation and experimental methods. The hindered phenol AO-60 had poor compatibility with NBR with an acrylonitrile content of 41% (denoted by N220S), but had good compatibility with NBR with an acrylonitrile content of 34% (denoted by N230S). The AO-60/N230S composite had larger H-bonds and higher binding energy than the AO-60/N220S composite at the same AO-60 content, both indicating stronger interactions between N230S and AO-60 and better damping performance of AO-60/N230S. Moreover, SEM, DSC, and DMA were used to evaluate the compatibility and damping of AO-60/NBR composites. Phase separation occurred between N220S and AO-60, but a fine dispersion of AO-60 in N230S was obtained. The present study hopes to provide theoretical guidance to the design of damping rubber materials.

Unsaturated metal methacrylate (UMM) as one kind of functional filler has played an important role in reinforcing rubber materials. The in situ self-polymerization of UMM in UMM/rubber composite leads to the uniform dispersion of poly(UMM) in the rubber matrix, while the crosslinking of rubber and grafting between UMM and rubber chains occur simultaneously, making it difficult to clarify the effect of the in situ polymerization on the dispersion of poly(UMM) in the rubber matrix. In this work, we investigated the dispersion mechanism of UMM without rubber matrix for the first time using differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR) spectroscopy. Three types of UMMs including zinc methacrylate (Zn(MA) 2 ), sodium methacrylate (Na(MA)) and samarium methacrylate (Sm(MA) 3 ) were chosen to investigate the in situ self-polymerization of UMM. Based on DSC results, we conclude that the crystals with low melting point tend to self-polymerize first and generate a large amount of heat in the presence of peroxide. The high heat of reaction can melt the crystals with high melting point, and more UMM molecules are dissolved in the rubber matrix, thus increasing the extent of the in situ polymerization. Hence, the UMM with low melting point can self-polymerize to a large extent. Our findings provide in-depth understanding of the dispersion mechanism of UMM in rubber.

Rubber, as a special polymer material with high elasticity at room temperature, has been widely used in industries. However, rubber has to be reinforced by using nanofillers to meet the needs of industrial applications because of its low mechanical strength. Fibrillar attapulgite (AT) with a unique structure and low cost, has attracted massive interests as a good filler for reinforcing rubber. In this chapter, the composition, morphology, physical and chemical characteristic of AT will be introduced. Then, the preparation methods, interfacial design, dispersion and filler network, structure-properties relationship of AT/rubber composites will be summarized. The synergistic effect of fibrillar attapulgite and other microfibers on the mechanical properties of rubber will be summarized.

The compressive stress relaxation tests of butadiene rubber (BR) at different thermo-oxidative aging temperatures were carried out. Fourier transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) was used to observe the variations of internal groups before and after the thermo-oxidative aging. Magnetic resonance-crosslink density (MR-XLD) spectroscopy was used to measure the crosslink densities. The results showed the compressive stress relaxation of BR during thermo-oxidative aging was dominated by chemical reactions: crosslinking, chain scission, and oxidation. Then an empirical model and an amendatory standard linear solid (SLS) model were put forward to describe the compressive stress relaxation behavior of BR. Both models fitted the data well. The SLS model, based on the aging mechanism of BR, not only made up the disadvantages of the empirical model, but also considered the changes of intrinsic viscosity (η) during the thermo-oxidative aging of BR. The SLS model showed that the thermo-oxidative aging of BR was mainly dominated by the crosslinking and oxidation reactions. This research proposes the amendatory SLS model and has important significance for study the stress relaxation behavior of cross-linked rubbers during thermo-oxidative aging. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 44630.

The use of conductive polymer composites (CPCs) as strain sensors has been widely investigated. A wide range of strain sensitivities and high repeatability are vital for different applications of CPCs. In this study, the relations of the conductive filler network and the strain-sensing behavior and electrical stability under fatigue cycles were studied systematically for the first time based on the conductive polymethylvinylsiloxane (PMVS) composites filled with both carbon nanotubes arrays (CNTAs) and carbon black (CB). It was proved that the composites could be fabricated with large strain-sensing capability and a wide range of strain sensitivities by controlling the volume ratio of CNTA/CB and their amounts. Additionally, the CNTA/CB/PMVS composite with 3 vol % content of fillers showed high sensitivity (GF is 10 at 60% strain), high repeatability (the relative standard deviation (RSD) of the max R/R0 value is 3.58%), and electrical stability under fatigue cycles (value range of R/R0 is 1.62 to 1.82) at the same time due to the synergistic effects of the dual conductive network of CNTAs and CB. This could not be achieved by relying on a single CNTA or CB conductive network. This study may provide guidance for the preparation of high performance CPCs for applications in strain sensors.

We successfully prepared bromo-isobutylene–isoprene rubber (BIIR)/polyamide 12 (PA 12) thermoplastic vulcanizate (TPV) by dynamic vulcanization (DV), and studied the microstructure and properties of BIIR/PA 12 TPV toward recyclable inner liners for green tires, to reduce fuel consumption and carbon emissions. The as-prepared BIIR/PA 12 TPV exhibits good mechanical properties, good elasticity, easy processability and good gas barrier properties. More importantly, our BIIR/PA 12 TPV still exhibits good properties after recycling several times. The mechanism for the formation of the phase morphology and morphological evolution during dynamic vulcanization, and the microstructure–property relationship of BIIR/PA 12 TPV were thoroughly studied to provide guidance for the preparation of high-performance BIIR/PA 12 TPVs toward tire inner liners. As the DV proceeded, the size of the dispersed BIIR particles and the thickness of the PA 12 ligaments decreased, leading to the strengthening of the rubber network. Although the rheological properties slightly deteriorated, the elasticity, the mechanical properties and the gas barrier properties of the TPVs were obviously improved as the DV proceeded.

We studied the microstructure, morphological evolution and the corresponding mechanism, and the properties of bromo-isobutylene-isoprene rubber (BIIR)/polypropylene (PP) thermoplastic vulcanizates (TPVs). Interestingly, a large number of single rubber nanoparticles were observed in the crosslinked BIIR/PP blends, ascribed to the improvement of compatibility between the BIIR and PP with increasing dynamic vulcanization (DV) time, as demonstrated by the increase in interfacial phase thickness and the decrease in the interfacial tension. Most of these single nanoparticles agglomerated as the DV proceeded, leading to the deterioration of the rubber network. Another interesting observation was that the size of rubber agglomerate decreased as the DV proceeded, leading to the strengthening of the rubber network. Importantly, the as-prepared BIIR/PP TPV exhibits good processability, high elasticity and good mechanical property. The relationship between the unique morphology and properties were studied. Our study provides guidance for the preparation of high-performance BIIR/PP TPV for its industrial applications such as medical bottle stoppers.

Novel mixed antioxidants composed of antioxidant IPPD and lanthanum (La) complex were added as a filler to form natural rubber (NR) composites. By mechanical testing, Fourier transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) and thermogravimetric analysis (TGA), a string of data, including the mechanical properties, the variation of internal groups and the thermal and thermo-oxidative decompositions of NR, was presented in this data article. The data accompanying its research article [1] studied the thermo-oxidative aging properties of NR in detail. The density function theoretical (DFT) calculations were also used as an assistant to study the thermo-oxidative aging mechanism of NR. The data revealed that this new rare-earth antioxidant could indeed enhance the thermo-oxidative aging resistance of NR, which is associated with its different function mechanism from that of the pure antioxidant IPPD.

This paper is concerned with the evaluation of a squeeze flow rheometer for determining the viscosity of a highly viscous filled viscoplastic fluid which is representative of the behavior of some propellants. Ordinarily materials of this nature are difficult to characterize using conventional capillary and rotary rheometers because of melt and edge fracture. A model system was chosen because its viscosity could still be measured up to reasonable shear rates of about 1 s−1 in a parallel disk rheometer. The power-law, Bingham, and Herschel-Bulkley empiricisms of the generalized Newtonian fluid were fitted to the steady shear viscosity data. The lubrication approximation was then used to predict the squeezing force as a function of gap height and the results compared to experimentally determined values. The best results were obtained for the Herschel-Bulkley model and in this case the lubrication approximation predictions were on the average some 20% lower than the experimental values between gap to radius ratios of 0.15 and 0.35. A finite element simulation of squeezing flow was carried out to assess the limitations of the lubrication approximation. The numerical solution was found to give a good description of the squeezing force for gap to radius ratios between 0.18 and 0.35. It was estimated that the error involved in the lubrication approximation was about 25% at a gap to radius ratio of 0.3 and decreased to below 2% at a gap to radius ratio of 0.05 for the material studied. Experiments were carried out to assess the effect of slip on the squeezing flow measurements using both roughened and lubricated plates. It was found that no significant slip occurred at squeezing speeds up to about 2.4 mm/s. Lubrication was found to reduce the squeezing force by an order of magnitude.

CERN-DESY workshop on "HERA and the LHC" DESY-PROC-2009-02; ISBN 978-3-935702-32-4; ISSN 1435-8077; International audience; A proper inclusion of heavy quark mass effects in Parton Distribution Function fits has proved crucial. We present a review these effects in DIS and their impact on global analyses and lay out all elements of a properly defined general mass variable flavor number scheme (GM VFNS) that are shared by all modern formulations of the problem. We also report about progress in a number of theoretical problems related to exclusive measurements of heavy flavors. These topics include fragmentation functions for charmed mesons including finite mass effects, fragmentation functions including non-perturbative corrections based on an effective QCD coupling, a discussion of the status of higherorder calculations for top quark production and for polarized structure functions, heavy quark and quarkonium production in the Regge limit, double heavy baryon production, tests of time reversal and CP symmetry in lamdab decays, as well as a study of the general properties of massive exotic hadrons that will be relevant for an understanding of their detection at the LHC.

We used a novel and simple approach to increase the actuated strain at low electric field of thermoplastic polyurethane (TPU) through the disruption of the hydrogen bonds of TPU by adding diaminonaphthalene (DAN) into the matrix. DAN as proton donors disrupted the original N–H/C=O hydrogen bonds between the TPU chains, improving the polarizability of the chains, thus increasing the dielectric constant of TPU. Meanwhile, DAN greatly decreased the elastic modulus of TPU by disrupting the hydrogen bonds of TPU. The simultaneous increase in dielectric constant and decrease in elastic modulus resulted in a 330% increase in electromechanical sensitivity at 103 Hz and a 500% increase in actuated strain at the low electric field of 20 V μm−1, facilitating the application of dielectric elastomers (DEs) in the biological and medical fields, where a low electric field is required. In addition, our DAN/TPU DE exhibited good mechanical strength.

Time series from complex systems with interacting nonlinear and stochastic subsystems and hierarchical regulations are often multiscaled. In devising measures characterizing such complex time series, it is most desirable to incorporate explicitly the concept of scale in the measures. While excellent scale-dependent measures such as epsilon entropy and the finite size Lyapunov exponent (FSLE) have been proposed, simple algorithms have not been developed to reliably compute them from short noisy time series. To promote widespread application of these concepts, we propose an efficient algorithm to compute a variant of the FSLE, the scale-dependent Lyapunov exponent (SDLE). We show that with our algorithm, the SDLE can be accurately computed from short noisy time series and readily classify various types of motions, including truly low-dimensional chaos, noisy chaos, noise-induced chaos, random 1/f(alpha) and alpha-stable Levy processes, stochastic oscillations, and complex motions with chaotic behavior on small scales but diffusive behavior on large scales. To our knowledge, no other measures are able to accurately characterize all these different types of motions. Based on the distinctive behaviors of the SDLE for different types of motions, we propose a scheme to distinguish chaos from noise.

Due to the ubiquity of time series with long-range correlation in many areas of science and engineering, analysis and modeling of such data is an important problem. While the field seems to be mature, three major issues have not been satisfactorily resolved. (i) Many methods have been proposed to assess long-range correlation in time series. Under what circumstances do they yield consistent results? (ii) The mathematical theory of long-range correlation concerns the behavior of the correlation of the time series for very large times. A measured time series is finite, however. How can we relate the fractal scaling break at a specific time scale to important parameters of the data? (iii) An important technique in assessing long-range correlation in a time series is to construct a random walk process from the data, under the assumption that the data are like a stationary noise process. Due to the difficulty in determining whether a time series is stationary or not, however, one cannot be 100% sure whether the data should be treated as a noise or a random walk process. Is there any penalty if the data are interpreted as a noise process while in fact they are a random walk process, and vice versa? In this paper, we seek to gain important insights into these issues by examining three model systems, the autoregressive process of order 1, on-off intermittency, and Levy motions, and considering an important engineering problem, target detection within sea-clutter radar returns. We also provide a few rules of thumb to safeguard against misinterpretations of long-range correlation in a time series, and discuss relevance of this study to pattern recognition.

Sea clutter refers to the radar returns from a patch of ocean surface. Accurate modeling of sea clutter and robust detection of low observable targets within sea clutter are important problems in remote sensing and radar signal processing applications. Due to lack of fundamental understanding of the nature of sea clutter, however, no simple and effective methods for detecting targets within sea clutter have been proposed. To help solve this important problem, we apply three types of fractal scaling analyses, fluctuation analysis (FA), detrended fluctuation analysis (DFA), and the wavelet-based fractal. scaling analysis to study sea clutter. Our analyses show that sea clutter data exhibit fractal behaviors in the time scale range of about 0.01 seconds to a few seconds. The physical significance of these time scales is discussed. We emphasize that time scales characterizing fractal scaling break are among the most important features for detecting patterns using fractal theory. By systematically studying 392 sea clutter time series measured under various sea and weather conditions, we find very effective methods for detecting targets within sea clutter. Based on the data available to us, the accuracy of these methods is close to 100%.

In time series analysis, it has been considered of key importance to determine whether a complex time series measured from the system is regular, deterministically chaotic, or random. Recently, Gottwald and Melbourne have proposed an interesting test for chaos in deterministic systems. Their analyses suggest that the test may be universally applicable to any deterministic dynamical system. In order to fruitfully apply their test to complex experimental data, it is important to understand the mechanism for the test to work, and how it behaves when it is employed to analyze various types of data, including those not from clean deterministic systems. We find that the essence of their test can be described as to first constructing a random walklike process from the data, then examining how the variance of the random walk scales with time. By applying the test to three sets of data, corresponding to (i) 1/f(alpha) noise with long-range correlations, (ii) edge of chaos, and (iii) weak chaos, we show that the test mis-classifies (i) both deterministic and weakly stochastic edge of chaos and weak chaos as regular motions, and (ii) strongly stochastic edge of chaos and weak chaos, as well as 1/f(alpha) noise as deterministic chaos. Our results suggest that, while the test may be effective to discriminate regular motion from fully developed deterministic chaos, it is not useful for exploratory purposes, especially for the analysis of experimental data with little a priori knowledge. A few speculative comments on the future of multiscale nonlinear time series analysis are made.