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The incidence of rheumatoid arthritis (RA) and its complications are expected to increase with age. Remarkably, RA patients were identified features of accelerated aging, particularly in immunosenescence. As is known, T cells in RA patients readily differentiate into pro-inflammatory phenotypes that maintain chronic and persistent inflammatory changes in joints and many other organ systems. Recent evidence suggests that T cells are most sensitive to aging, and aged CD4+ T cells contribute to inflammaging, which plays a crucial role in accelerating the disease process. In recent years, the molecular mechanisms of T cell immunosenescence were beginning to be understood. Immune aging in RA T cells is associated with thymus insufficiency, metabolic abnormalities, shortened telomere length, and chronic energy stress. Therefore, we summarized the role and mechanism of T cell immunosenescence in RA.A computer-based online search was performed using the PubMed database for published articles concerning T cells aging and rheumatoid arthritis.In this review, we assess the roles of CD4+ T cells in the center of inflammaging especially in RA and emphasize arthritogenic effector functions of senescent T cell; also we discuss the possible molecular mechanisms of senescent T cells and therapeutic targets to intervene T cells immunosenescence for improvement of RA.

Deep convolutional neural network (CNN) has made great progress in medical image classification. However, it is difficult to establish effective spatial associations, and always extracts similar low-level features, resulting in redundancy of information. To solve these limitations, we propose a stereo spatial discoupling network (TSDNets), which can leverage the multi-dimensional spatial details of medical images. Then, we use an attention mechanism to progressively extract the most discriminative features from three directions: horizontal, vertical, and depth. Moreover, a cross feature screening strategy is used to divide the original feature maps into three levels: important, secondary and redundant. Specifically, we design a cross feature screening module (CFSM) and a semantic guided decoupling module (SGDM) to model multi-dimension spatial relationships, thereby enhancing the feature representation capabilities. The extensive experiments conducted on multiple open source baseline datasets demonstrate that our TSDNets outperforms previous state-of-the-art models.

For the past few years, image fusion technology has made great progress, especially in infrared and visible light image infusion. However, the fusion methods, based on traditional or deep learning technology, have some disadvantages such as unobvious structure or texture detail loss. In this regard, a novel generative adversarial network named MSAt-GAN is proposed in this paper. It is based on multi-scale feature transfer and deep attention mechanism feature fusion, and used for infrared and visible image fusion. First, this paper employs three different receptive fields to extract the multi-scale and multi-level deep features of multi-modality images in three channels rather than artificially setting a single receptive field. In this way, the important features of the source image can be better obtained from different receptive fields and angles, and the extracted feature representation is also more flexible and diverse. Second, a multi-scale deep attention fusion mechanism is designed in this essay. It describes the important representation of multi-level receptive field extraction features through both spatial and channel attention and merges them according to the level of attention. Doing so can lay more emphasis on the attention feature map and extract significant features of multi-modality images, which eliminates noise to some extent. Third, the concatenate operation of the multi-level deep features in the encoder and the deep features in the decoder are cascaded to enhance the feature transmission while making better use of the previous features. Finally, this paper adopts a dual-discriminator generative adversarial network on the network structure, which can force the generated image to retain the intensity of the infrared image and the texture detail information of the visible image at the same time. Substantial qualitative and quantitative experimental analysis of infrared and visible image pairs on three public datasets show that compared with state-of-the-art fusion methods, the proposed MSAt-GAN network has comparable outstanding fusion performance in subjective perception and objective quantitative measurement.

To obtain more semantic information with small samples for medical image segmentation, this paper proposes a simple and efficient dual-rotation network (DR-Net) that strengthens the quality of both local and global feature maps. The key steps of the DR-Net algorithm are as follows (as shown in Fig. 1). First, the number of channels in each layer is divided into four equal portions. Then, different rotation strategies are used to obtain a rotation feature map in multiple directions for each subimage. Then, the multiscale volume product and dilated convolution are used to learn the local and global features of feature maps. Finally, the residual strategy and integration strategy are used to fuse the generated feature maps. Experimental results demonstrate that the DR-Net method can obtain higher segmentation accuracy on both the CHAOS and BraTS data sets compared to the state-of-the-art methods.

The control of combustion is a hot and classical topic. Among the combustion technologies, electric-field assisted combustion is an advanced technology that enjoys major advantages such as fast response and low power consumption compared with thermal power. However, its fundamental principle and impacts on the flames are complicated due to the coupling between physics, chemistry, and electromagnetics. In the last two decades, tremendous efforts have been made to understand electric-field assisted combustion. New observations have been reported based on different combustion systems and improved diagnostics. The main impacts, including flame stabilization, emission reduction, and flame propagation, have been revealed by both simulative and experimental studies. These findings significantly facilitate the application of electric-field assisted combustion. This brief review is intended to provide a comprehensive overview of the recent progress of this combustion technology and further point out research opportunities worth investigation.

The early growth process of wheat is vulnerable to various factors, and poor growth leads to vacancies in the planting row. Therefore, the wheat images captured by unmanned aerial vehicles (UAV) are essential for monitoring the growth of wheat and preventing diseases and insect pests. This paper uses wheat images captured by UAV as a dataset, and propose a novel residual-capsule network with threshold convolution (RCTC) for segmentation of wheat plantation rows. The network is achieved by replacing the AveragePooling of the improved ResNet34 with Capsule. Since the capsule network represents the features by vectors, it can explain the direction of features and the relative positions between features. Therefore, deeper feature information can be extracted. In addition, to reduce redundant features and enhance effective features, a new threshold convolution is also proposed. Experiments on the wheat field dataset show that our proposed algorithm can effectively segment the wheat plantation rows images collected by UAV, and is superior to some existing well-known algorithms, and can provide scientific support and reference for the decision-making process of smart agriculture.

Improving thermal transport between substrate and transistors has become a vital solution to the thermal challenge in nanoelectronics. Recently 2D WTe2 has sparked extensive interest because of heavy atomic mass and low Debye temperature. Here, the thermal transport of supported WTe2 was studied via Raman thermometry with electrical heating. The supported 30 nm WTe2 encased with 70 nm Al2O3 delivered 4.8 W·m−1·K−1 in-plane thermal conductivity along zigzag direction at room temperature, which was almost 1.6 times larger than that along armchair direction (3.0 W·m−1·K−1). Interestingly, the superior and inferior directions for thermal transport are just opposite of those for electrical transport. Hence, a heat manipulation model in WTe2 FET device was proposed. Within the designed configuration, waste heat in WTe2 would be mostly dissipated to metal contacts located along zigzag, relieving the local temperature discrepancy in the channel effectively and preventing degradation or breakdown. Our study provides new insight into thermal transport of anisotropic 2D materials, which might inspire energy-efficient nanodevices in the future.

Effects of liquid fuel composition variations on characteristics of self-excited thermo-acoustic instabilities in a lean premixed, pre-vaporized gas turbine model combustor were experimentally studied. Test fuels included practical RP-3 jet fuel and its blending with iso-octane and n-dodecane, which were branched and linear alkanes respectively. Under the test conditions, dynamic pressure measurements indicated that the dominant instability frequency was highest for RP-3 flame, while RP-3/n-dodecane flame exhibited the strongest instability strength. A further analysis showed that the instability frequency correlated well with the profiles of adiabatic flame temperature, and the strength of the instability highly depended on the ignition delay times of the fuels. Measurements of the flame structure and flow field with OH* chemiluminescence (CL) imaging and two-dimensional particle image velocimetry (PIV) techniques indicated that changes in the fuel composition did not alter the unstable modes and general sequences of flame-flow structure oscillations. Further power spectra and proper orthogonal decomposition (POD) analysis suggested that axial oscillations along with precessing vortex core (PVC) induced helical motion predominated periodic flame structure and flow field oscillations.

The monitoring of Li-ion battery temperatures is essential to ensure high efficiency and safety. In this work, two types of recurrent neural networks (RNNs), which are long short-term memory-RNN (LSTM-RNN) and gated recurrent unit-RNN (GRU-RNN), are proposed to estimate the surface temperature of 18650 Li-ion batteries during the discharging processes under different ambient temperatures. The datasets acquired from the Prognostics Center of Excellence (PCoE) of NASA are used to train, validate and test the networks. In previous work, temperature has been set as the output of the networks; however, here the temperature difference along the time axis is adopted as the output. The net heat generated results in net temperature change, which is more closely aligned with electrochemical and thermodynamic laws. Extensive simulation results show that the two RNNs can achieve accurate real-time battery temperature estimation. The maximum absolute error in temperature estimation is approximately 0.75°C and the correlation coefficient between the estimated and measured temperature curves is greater than 0.95. The influences of three crucial parameters, which are the number of hidden neurons, initial learning rate and maximum number of iterations, are also assessed in terms of training time, root mean square error and mean absolute error.

Each sample in the hyperspectral remote sensing image has high-dimensional features and contains rich spatial and spectral information, which greatly increases the difficulty of feature selection and mining. In view of these difficulties, we propose a novel Triple-attention Guided Residual Dense and BiLSTM networks(TARDB-Net) to reduce redundant features while increasing feature fusion capabilities, which ultimately improves the ability to classify hyperspectral images. First, a novel Triple-attention mechanism is proposed to assign different weights to each feature. Then, the residual network is used to perform the residual operation on the features, and the initial features of the multiple residual blocks and the generated deep residual features are intensively fused, retaining a host number of prior features. And use the bidirectional long short-term memory network to integrate the contextual semantics of deep fusion features. Finally, the classification task is completed by Softmax classifier. Experiments on three hyperspectral datasets—Indian Pines, University of Pavia, and Salinas—show that under 10% of the training samples, the overall accuracy of our method is 87%, 96% and 96%, which is superior to several well-known methods.

Volumetric imaging represents one of the major development trends of flow diagnostics due to both the advancement in hardware and the requirement for more information to further understand complicated turbulent and/or reactive flows. Background-oriented Schlieren tomography (BOST) has become increasingly popular due to its experimental simplicity. It has been demonstrated to be capable of simultaneously recovering the distributions of refractive index, density, and temperature of flows. However, its capability in thermometry has only been demonstrated under the axisymmetric assumption, which greatly limits its applicability. In this work, we dedicated to developing a cost-effective BOST system for the simultaneous retrieval of refractive index, density, and temperature distributions for the asymmetric flame. A few representative tomographic inversion algorithms were assessed as well. Both numerical and experimental demonstrations were conducted and the results show that our implemented BOST can successfully reconstruct the three-dimensional temperature distribution with a satisfactory accuracy.

With the growing applications of nanofluid flame, the monitoring and controlling of its combustion process is of paramount importance. Thus, it is necessary to develop diagnosing methods which can simultaneously image important parameters such as temperature and volume fractions of soot, metal-oxide nanoparticles. Tomographic emission spectroscopy is an effective method which has been proposed for this purpose. However, the inversion process was only reported with least-squares QR decomposition (LSQR) so far and there are numerous well-established reconstruction algorithms which have not been utilized yet. Thus, this work aims to perform systematic comparative studies on several representative algorithms for the inversion process. In the simulative studies, algorithms including Tikhonov regularization, algebraic reconstruction technique (ART), LSQR, Landweber algorithm, maximum likelihood expectation maximization (MLEM), and ordered subset expectation maximization (OSEM) were discussed. The effects of the number of iterations, the signal-to-noise ratio, and the number of projections and the calibration error in projection angles on the performance of the algorithms were investigated. Advice on selecting the suitable algorithms under different application conditions is then provided according to the extensive numerical studies.

Multi-user collaborative editors are useful computer-aided tools to support human-to-human collaboration. For multi-user collaborative editors, selective undo is an essential utility enabling users to undo any editing operations at any time. Collaborative editors usually adopt operational transformation (OT) to address concurrency and consistency issues. However, it is still a great challenge to design an efficient and correct OT algorithm capable of handling both normal do operations and user-initiated undo operations because these two kinds of operations can interfere with each other in various forms. In this paper, we propose a semi-transparent selective undo algorithm that handles both do and undo in a unified framework, which separates the processing part of do operations from the processing part of undo operations. Formal proofs are provided to prove the proposed algorithm under the well-established criteria. Theoretical analysis and experimental evaluation are conducted to show that the proposed algorithm outperforms the prior OT-based selective undo algorithms.

Non-intrusive measurement techniques are required to gain a comprehensive understanding about the processes of soot formation, growth and oxidation. Time-resolved laser-induced incandescence (TiRe-LII), commonly performed 0D or 2D within a flame, has proven to be a very suitable tool for the in situ sizing of soot primary particles. In this work, the technique is expanded to the third dimension by employing volumetric illumination and coupling it with a tomographic approach, which allows to computationally gain 3D information from 2D images taken at various angles. To minimize experimental cost, an approach using nine fiber bundles arranged in a semicircle around the flame and imaging the light onto a single camera is used. The technique is demonstrated on an ethene diffusion flame on a standard burner, providing spatially resolved 3D particle sizes. One focus of this work is to reveal the influence of input parameters such as the local bath gas temperature, which we measured by two-color pyrometry, and local laser fluence, which are both required for an accurate evaluation of the local particle size. It is shown that the assumption of an average temperature may result in a wrong picture even of qualitative soot size evaluation. In the end, a concept is proposed for a simultaneous determination of the 3D distribution of particle sizes through TiRe-LII and the required bath gas temperature via two-color pyrometry using a tomographic approach with only three cameras.

Gastric cancer (GC) has a high mortality rate, and metastasis is the main reason for treatment failure. It is important to study the mechanism of tumour invasion and metastasis based on the regulation of key genes. In a previous study comparing the expression differences between GES-1 and SGC-7901 cells, PCDHGA9 was selected for further research. In vitro and in vivo experiments showed that PCDHGA9 inhibited invasion and metastasis. A cluster analysis suggested that PCDHGA9 inhibited epithelial-mesenchymal transition (EMT) through the Wnt/β-catenin and TGF-β pathways. Laser confocal techniques and western blotting revealed that PCDHGA9 inhibited the nuclear translocation of β-catenin, regulated T cell factor (TCF)/ /lymphoid enhancer factor (LEF) transcriptional activity, directly impacted the signal transmission of the TGF-β/Smad2/3 pathway, strengthened the adhesion complex, weakened the effects of TGF-β, and blocked the activation of the Wnt pathway. In addition, PCDHGA9 expression was regulated by methylation, which was closely related to poor clinical prognosis. The aim of this study was to elucidate the molecular mechanism by which PCDHGA9 inhibits EMT and metastasis in GC to provide a new theoretical basis for identifying GC metastasis and a new target for improving the outcome of metastatic GC.

Three-dimensional (3D) imaging techniques, such as computed tomography of chemiluminescence and volumetric laser-induced fluorescence, are advanced combustion diagnostic tools that can provide rich insights on the spatial distribution of combustion intermediates. Besides the flame structure that is directly reconstructed, some deep and underlying information such as the geometric features are quite useful for a complete understanding of combustion mechanisms and, therefore, is desired to be further explored. However, to the best of our knowledge, due to the concave and convex variations on flame surface and the mathematical challenges, almost no attempts have been made to experimentally calculate the 3D geometric features of a turbulent swirl flame. In this work, we propose a point-extracted method that can effectively extract a point cloud from the reconstructed turbulent swirl flame. In addition, the two principal curvatures, mean curvature and the Gaussian curvature were evaluated with the so-called triangle-mesh-based method (TMB). One main contribution of this work is to perform a comparison between TMB and direct numerical simulation for curvature evaluation. The quantities obtained by this method are expected to be valuable for the validation of combustion modeling and for the investigation of combustion mechanisms. The 3D curvatures including principle curvatures, mean curvature and Gaussian curvature were experimentally evaluated in a turbulent swirl flame for the first time. The Gaussian curvatures can be related to three typical kinds of curved surfaces, i.e. elliptical, cylindrical and saddle surfaces. For the swirl flame used in this work, the cylindrical surface is regarded as a “base flame surface”, based on which some humps called flame wrinkles would form at some positions. At the tip of each hump, the flame will present an elliptical cup-like surface, where the Gaussian curvatures are relatively large. The transition region from cylindrical surface to elliptical surface mostly manifests a saddle surface.

Pure ZnO and a series of Al and Er co-doped ZnO nanomaterials (AEZ) have been synthesized and characterized by various analytical and spectroscopic techniques such as TEM, EDS, XRD, FTIR, Raman, UV–Vis and SQUID. Al concentration has been varied from 1, 2 and 3% keeping fixed concentration of Er at 2% to obtain the co-doped ZnO. TEM images show uniform and homogeneously distributed plates-like nanostructure for ZnO and predominately spherical shape with hexagonal facets for AEZ. XRD Rietvield analysis confirms the crystallinity of ZnO and AEZ with ZnO wurtzite crystal structure. It also clearly demonstrates the coexistence of Al and Er into ZnO lattice as evidenced by the shift of reflections towards lower 2θ values. The change of magnetic behavior from ferromagnetic into paramagnetic originated from point defects depending on the concentration of the doping elements. The as-prepared nanopowders have been tested under visible light (554 nm wavelength) irradiation to evaluate the photocatalytic activity towards Rhodamine B (RhB); the degradation rate was found to be more than 93% in 40 min with the combination 3% Al, 2% Er co-doped ZnO.

A novel pendant-type cross-linked anion exchange membrane (pc-AEM) was successfully synthesized using a pre-synthesis approach to precisely control the IEC value and the degree of cross-linking. The physical properties of the pc-AEMs and the non-cross-linked pc-AEMs as well as Nafion 117 were determined, and the results were systematically compared. It was found that the synthesized pc-AEMs show much better dimensional retention capacity than the non-cross-linked pc-AEM and Nafion 117. In addition, the mechanical strength of the pc-AEMs was also remarkably enhanced. By increasing the IEC value of the pc-AEMs to the same level of Nafion 117, the highest ionic conductivity of 0.036 S/cm at 80 °C was reached. The remarkable enhancement of conductivity is chiefly attributed to the construction of highly efficient ionic transport channels resulting from the combined pendant-type and cross-linked architectures of the pc-AEMs.

Objective Vasculogenic mimicry (VM) is a novel mechanism of tumor blood supply distinct from endothelial vessel (EV). VM is associated with malignancy, invasion, metastasis, and poor prognosis. Hitherto a noninvasive method for the assessment of VM in vivo has been lacking. Methods Contrast-enhanced ultrasound (CEUS) was performed to evaluate the quantitative parameters of tumors in mice. CD31 immunohistochemistry-Periodic Acid-Schiff double staining was conducted to identify the VM or EV in tumor tissues. Correlations between perfusion parameters and VM density was analyzed by Pearson correlation test. Results By the 15th day after tumor inoculation, the EV and VM density was 31.15 ± 7.14 and 14.11 ± 2.99 per 200× field. The maximal intensity (IMAX) was 301.19 ± 191.56%, and the rise time (RT), time to peak (TTP) and mean transit time (mTT) were 17.38 ± 7.82 s, 20.27 ± 9.61 s and 58.09 ± 26.44 s, respectively. VM density positively correlated to RT (r = 0.3598, P = 0.0226), TTP (r = 0.3733, P = 0.0177) and mTT(r = 0.6483, P

Multispectral absorption tomography (MAT) is evolving into a mature imaging technique for flow diagnostics due to recent progress in both laser sources and nonlinear tomography. For the absorption-based technique, how to determine and utilize the most informative spectral lines are critical for successful implementation of the technique. In this work, we propose a method to select the optimal combination of spectral lines from the candidate set for MAT. We select the Gram determinant of selected spectral lines in given temperature interval as the cost function of the optimization problem, which can then be maximized by enumerating all the possible combinations of the candidate spectral lines. The numerical studies performed in this work verified the effectiveness of the proposed method, whose purpose was to achieve the best performance for the reconstruction of temperature distribution.

Porous zirconia (ZrO2) microspheres with incontinuous multicavities were prepared via emulsion method combined with phase separation in the presence of polyvinylpyrrolidone (PVP). The morphology of the microspheres is derived from the spherical oil droplets by high-speed shearing and the sol–gel reaction on the droplets, while the PVP acts as a phase separation inducer to form incontinuous multicavities inside the microspheres. The addition of PVP does not change the particle size distribution and smooth surface morphology of the microspheres, while the size of cavities inside microspheres increases gradually with the increase in PVP amount. The particle characteristics, phase transformation and cavity formation mechanism of porous ZrO2 microspheres are analyzed in detail. Porous ZrO2 microspheres with incontinuous multicavities were prepared via emulsion method combined with phase separation in the presence of polyvinylpyrrolidone (PVP). The morphology of the microspheres is derived from the spherical oil droplets by high-speed shearing and the sol–gel reaction on the droplets, while the PVP acts as a phase separation inducer to form incontinuous multicavities inside the microspheres.

Ethyl cellulose porous spheres (ECPSs) loaded with superparamagnetic iron oxide nanoparticles (SPIONs) have been successfully synthesized via a physical method in oil-in-water (O/W) emulsion. The as-prepared ECPSs possess open pores in the shell and interconnected pores inside the spheres by means of phase separation. The SPIONs with an average size of around 5 nm synthesized by co-precipitation method are added into oil phase precursor in the preparation of ECPSs to synthesize the ECPSs-SPIONs. The loading of SPIONs does not change the morphology of ECPSs, while endows the ECPSs with high ferromagnetic properties at room temperature. The resultant ECPSs-SPIONs can be easily separated from dispersion liquid or driven to specific sites under an external magnet.

Understanding the abundance change of certain bacterial taxa is quite important for the study of soil microbiology. However, the observed differences of relative abundances by high-throughput techniques may not accurately reflect those of the actual taxon abundances. This study investigated whether soil microbial abundances coupling with microbial quantities can be more informative in describing the microbial population distribution under different locations. We analyzed relative abundances of the major species in soil microbial communities from Beijing and Tibet grasslands by using 16 S rRNA high-throughput sequencing technique, and quantified the absolute bacterial cell numbers directly or indirectly by multiple culture-independent measurements, including adenosine tri-phosphate (ATP), flow cytometry (FCM), quantitative real-time PCR (qPCR), phospholipid fatty acids (PLFA) and microbial biomass Carbon (MBC). By comparison of the relative abundance and the estimated absolute abundances (EAA) of the major components in soil microbial communities, several dominant phyla, including Actinobacteria, Bacteroidetes, Verrucomicrobia, Chloroflexi, Gemmatimonates and Planctomycetes, showed significantly different trends. These results indicated that the change in EAA might be more informative in describing the dynamics of a population in a community. Further studies of soil microbes should combine the quantification and relative abundances of the microbial communities for the comparisons among various locations.

Background Activation of macrophage is involved in many inflammation diseases. Lipopolysaccharide (LPS) is a powerful inflammatory signal contributing to monocytes/macrophages activation associated with increased proinflammatory cytokines expressions. We recently identified that vaccarin was expected to protect endothelial cells from injury. Hypaphorine was abundantly found in vaccaria semen. However, the potential roles and underlying mechanisms of vaccaria hypaphorine on macrophage inflammation have been poorly defined. Methods This study was designed to determine the effects of vaccaria hypaphorine on LPS-mediated inflammation in RAW 264.7 cells. Results In this study, we demonstrated that vaccaria hypaphorine dramatically ameliorated LPS-induced nitric oxide (NO) release and productions of proinflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), IL-6, IL-10, monocyte chemoattractant protein 1 (MCP-1) and prostaglandin E2 (PGE2) in RAW 264.7 cells. LPS-stimulated expressions of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) were down-regulated by vaccaria hypaphorine. Furthermore, vaccaria hypaphorine retarded LPS-induced phosphorylation of ERK, nuclear factor kappa beta (NFκB), NFκB inhibitor IκBα, and IKKβ. Immunofluorescence staining revealed that vaccaria hypaphorine eliminated the nuclear translocation of NFκB in LPS-treated RAW 264.7 cells. Conclusion It was seen that vaccaria hypaphorine counteracted inflammation via inhibition of ERK or/and NFκB signaling pathways. Collectively, we concluded that vaccaria hypaphorine can be served as an anti-inflammatory candidate. Electronic supplementary material The online version of this article (doi:10.1186/s12906-017-1635-1) contains supplementary material, which is available to authorized users.

The isotope labeled graphene was synthesized in the concentration of 13 C carbon atom in 1%, 25%, 50%, 75% and 99%. The isotope effect on the phonon behavior in graphene was investigated based on the micro-Raman analysis of 13 C isotope labeled graphene samples. We found that the phonon scattering is affected by the isotopic carbon atom as a point defect. Based on the experiment results, the Klemens-Callaway model and uncertainty principle were used to obtain the mean free path of the G and D phonons. The results agree with the thermal conductivity measurement by non-contact optical method and with other theoretical calculations.

Lithium poly(pyromellitic acid borate) (PPAB) was synthesized via polymerization of lithium tetramethanolatoborate and silylated pyromellitic acid. The synthesized material was characterized by Fourier transformation infrared spectroscopy, 11B nuclear magnetic resonance, scanning electron microscopy, and thermogravimetric analysis. And electrochemical characterizations were carried out on the blended PPAB/PVDF-HFP membrane. The PPAB-based composite membrane exhibits high lithium ionic conductivity, a broad electrochemical window and a high lithium-ion transference number. The battery cells assembled with the PPAB/PVDF-HFP/EC:PC composite membrane as the electrolyte perform reasonably well not only at elevated temperature but also at room temperature with good cyclability and discharge capacity, making the material suitable for applications in lithium-ion batteries.

A novel linear non-fluorinated sulfonimide functionalized polyamide (SPA) polymer electrolyte was successfully synthesized via an aromatic sulfonimide monomer with superior thermal stability and superacidity. The aromatic sulfonimide remains stable below 220 °C. To fabricate membranes with strong mechanical strength and dimensional stability, the polymer was blended with various quantities of PVdF. The PVdF/SPA blend membranes exhibit an excellent capacity of water uptake and high dimensional stability. However, their proton conductivity was found to be substantially lower than that of Nafion 211. Analysis on the SEM images of the PVdF/SPA blend membranes reveals that the low proton conductivity is primarily caused by the large pore structures (>1 μm), which lead to breakdown of the continuous proton transport channels.

In addition to its exotic electronic properties graphene exhibits unusually high intrinsic thermal conductivity. The physics of phonons--the main heat carriers in graphene--has been shown to be substantially different in two-dimensional (2D) crystals, such as graphene, from in three-dimensional (3D) graphite. Here, we report our experimental study of the isotope effects on the thermal properties of graphene. Isotopically modified graphene containing various percentages of 13C were synthesized by chemical vapour deposition (CVD). The regions of different isotopic compositions were parts of the same graphene sheet to ensure uniformity in material parameters. The thermal conductivity, K, of isotopically pure 12C (0.01% 13C) graphene determined by the optothermal Raman technique, was higher than 4,000 W mK(-1) at the measured temperature T(m)~320 K, and more than a factor of two higher than the value of K in graphene sheets composed of a 50:50 mixture of 12C and 13C. The experimental data agree well with our molecular dynamics (MD) simulations, corrected for the long-wavelength phonon contributions by means of the Klemens model. The experimental results are expected to stimulate further studies aimed at a better understanding of thermal phenomena in 2D crystals.

The effect of Ag nanoislands on the Raman of graphene was investigated in this work. Compared with that on the bare silicon wafer, Raman enhancement was observed in the graphene film that covered on Ag/Si surface with nanoscale Ag islands, which would be induced by the localized plasmon resonance in Ag nanostructures. The interaction between the graphene sheet and Ag/Si substrate was further studied. The peak shift and line shape of Raman spectroscopy indicated a nonuniform strain distribution in the Ag/Si supported graphene film.

This work provides an effective low-cost synthesis and in-depth mechanistic study of high quality large-area nitrogen-doped graphene (NG) films. These films were synthesized using urea as nitrogen source and methane as carbon source, and were characterized by scanning electron microscopy (SEM), Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). The N doping level was determined to be 3.72 at.%, and N atoms were suggested to mainly incorporated in a pyrrolic N configuration. All distinct Raman peaks display a shift due to the nitrogen-doping and compressive strain. The increase in urea concentration broadens the D and 2D peak’s Full Width at Half Maximum (FWHM), due to the decrease of mean free path of phonons. The N-doped graphene exhibited an n-type doping behavior with a considerably high carrier mobility of about 74.1 cm2/(V s), confirmed by electrical transport measurements.

Large-area In2O3 ordered pore arrays were prepared on glass and silicon substrates by the sol–gel technique based on colloidal monolayer spheres. The morphologies of such arrays are determined by precursor concentration used and colloidal sphere size, and are thus controllable. It has been shown that the formed ordered pore arrays consist of In2O3 polycrystallites. The photoluminescence measurement of the In2O3 ordered pore arrays shows that there is a strong photoluminescence band in the blue-green region centered around 465 nm, which does not exist in the bulk materials. Further experiments reveal that this peak originates from the oxygen deficiencies in In2O3 skeletons. This polydomain ordered pore-structured array could be of great potential for Si-based integrated nanophotonics and optoelectronic devices of the next generation, in addition to new gas sensors.

Raman spectroscopy was used to study the evolution of host lattice recrystallization in Mn+-implanted GaAs. A high dose of Mn+-ions (> 10(15) cm(-2)) was introduced into semi-insulating GaAs by the combinatorial implantation method. Subsequent thermal annealing at 920 degreesC was carried out to re-grow the implantation-induced amorphous layers. The dependence of the recrystallization behavior on the Mn content was systematically observed. The lattice orientation of recrystallized layers in the surface changed after high-dose implantation (> 1.6 x 10(15) cm(-2)) and annealing. The size of the recrystallized crystallites decreased with increasing Mn+ dose, as indicated by images from atomic force microscopy. The decrease in the phonon frequency-of the Raman lines with the size reduction of microcrystals was in good agreement with the spatial correlation model. However, at higher doses (> 7 x 10(16) cm(-2)), a blue shift of the frequency was observed due to the compressive stress exerted on the microcrystals.

The hydrogen-enhanced recrystallization during thermal annealing in N+-implanted GaAs has been studied by combinatorial implantation process. Raman spectroscopy was used to study the crystallization properties of a set of hydrogenated cells on the N+-implanted GaAs wafer. A whole competitive process between H+ implantation-induced damage and recovery in the regrowth process of amorphous GaAs was observed within the proton dose region of 1.6×1015 to 1.1×1017 cm-2. In H+ dose region of 2.1×1016 to 5.4×1016 cm-2, H-enhanced recovery of crystal dominates the regrowth process. The crystal quality is better than that of unhydrogenated cell of N+-implanted GaAs in the H+ dose range from 4.7×1016 to 8.1×1016 cm-2. It is suggested that the vacancy supersaturation produced during hydrogen irradiation is dominantly responsible for the enhancement of thermal regrowth in the N+-implanted GaAs. Both the crystallization and amorphization process are clearly observed in different proton implantation dose regions.