Core–Shell Structure and Interaction Mechanism of γ‐MnO2 Coated Sulfur for Improved Lithium‐Sulfur Batteries

Lithium‐sulfur batteries have attracted worldwide interest due to their high theoretical capacity of 1672 mAh g^?1 and low cost. However, the practical applications are hampered by capacity decay, mainly attributed to the polysulfide shuttle. Here, the authors have fabricated a solid core–shell γ‐MnO₂‐coated sulfur nanocomposite through the redox reaction between KMnO₄ and MnSO₄. The multifunctional MnO₂ shell facilitates electron and Li⁺ transport as well as efficiently prevents polysulfide dissolution via physical confinement and chemical interaction. Moreover, the γ‐MnO₂ crystallographic form also provides one‐dimensional (1D) tunnels for the Li⁺ incorporation to alleviate insoluble Li₂S₂/Li₂S deposition at high discharge rate. More importantly, the MnO₂ phase transformation to Mn₃O₄ occurs during the redox reaction between polysulfides and γ‐MnO₂ is first thoroughly investigated. The S@γ‐MnO₂ composite exhibits a good capacity retention of 82% after 300 cycles (0.5 C) and a fade rate of 0.07% per cycle over 600 cycles (1 C). The degradation mechanism can probably be elucidated that the decomposition of the surface Mn₃O₄ phase is the cause of polysulfide dissolution. The recent work thus sheds new light on the hitherto unknown surface interaction mechanism and the degradation mechanism of Li‐S cells.     

Metal‐containing Polymers via Electropolymerization

Electropolymerization represents a suitable and well‐established approach for the assembly of polymer structures, in particular with regard to the formation of thin, insoluble films. Utilization of monomers that are functionalized with metal complex units allows the combination of structural and functional benefits of polymers and metal moieties. Since a broad range of both electropolymerizable monomers and metal complexes are available, various structures and, thus, applications are possible. Recent developments in the field of synthesis and potential applications of metal‐functionalized polymers obtained via electropolymerization are presented, highlighting the significant advances in this field of research.     

Multi‐modal brain tumor image segmentation based on SDAE

Accurate tumor segmentation has the ability to provide doctors with a basis for surgical planning. Moreover, brain tumor segmentation needs to extract different tumor tissues (Edema, tumor, tumor enhancement, and necrosis) from normal tissues which is a big challenge because tumor structures vary considerably across patients in terms of size, extension, and localization. In this article, we evaluate a fully automated method for segmenting brain tumor images from multi‐modal magnetic resonance imaging volumes based on stacked de‐noising auto‐encoders (SDAEs). Specially, we adopted multi‐modality information from T1, T1c, T2, and Flair images, respectively. We extracted gray level patches from different modalities as the input of the SDAE. After trained by the SDAE, the raw network parameters will be obtained, which are adopted as a parameter of the feed forward neural network for classification. A simple post‐processing is implemented by threshold segmentation method to generate a mask to get the final segmentation result. By evaluating the proposed method on the BRATS 2015, it can be proven that our method obtains the better performance than other state‐of‐the‐art counterpart methods. And a preliminary dice score of 0.86 for whole tumor segmentation has been achieved.     

Hybrid Perovskite Light‐Emitting Diodes Based on Perovskite Nanocrystals with Organic–Inorganic Mixed Cations

Organic–inorganic hybrid perovskite materials with mixed cations have demonstrated tremendous advances in photovoltaics recently, by showing a significant enhancement of power conversion efficiency and improved perovskite stability. Inspired by this development, this study presents the facile synthesis of mixed‐cation perovskite nanocrystals based on FA_{(1?x )}Cs_x PbBr₃ (FA = CH(NH₂)₂). By detailed characterization of their morphological, optical, and physicochemical properties, it is found that the emission property of the perovskite, FA_{(1?x )}Cs_x PbBr₃, is significantly dependent on the substitution content of the Cs cations in the perovskite composition. These mixed‐cation perovskites are employed as light emitters in light‐emitting diodes (LEDs). With an optimized composition of FA_0.8Cs_0.2PbBr₃, the LEDs exhibit encouraging performance with a highest reported luminance of 55 005 cd m^?2 and a current efficiency of 10.09 cd A^?1. This work provides important instructions on the future compositional optimization of mixed‐cation perovskite for obtaining high‐performance LEDs. The authors believe this work is a new milestone in the development of bright and efficient perovskite LEDs.     

An efficient sparse matrix‐vector multiplication on CUDA‐enabled graphic processing units for finite element method simulations

Finite element method (FEM) is a well‐developed method to solve real‐world problems that can be modeled with differential equations. As the available computational power increases, complex and large‐size problems can be solved using FEM, which typically involves multiple degrees of freedom (DOF) per node, high order of elements, and an iterative solver requiring several sparse matrix‐vector multiplication operations. In this work, a new storage scheme is proposed for sparse matrices arising from FEM simulations with multiple DOF per node. A sparse matrix‐vector multiplication kernel and its variants using the proposed scheme are also given for CUDA‐enabled GPUs. The proposed scheme and the kernels rely on the mesh connectivity data from FEM discretization and the number of DOF per node. The proposed kernel performance was evaluated on seven test matrices for double‐precision floating point operations. The performance analysis showed that the proposed GPU kernel outperforms the ELLPACK (ELL) and CUSPARSE Hybrid (HYB) format GPU kernels by an average of 42% and 32%, respectively, on a Tesla K20c card. Copyright © 2016 John Wiley & Sons, Ltd.     

Red‐Emitting Upconverting Nanoparticles for Photodynamic Therapy in Cancer Cells Under Near‐Infrared Excitation

Upconverting nanoparticles (UCNPs) have attracted considerable attention as potential photosensitizer carriers for photodynamic therapy (PDT) in deep tissues. In this work, a new and efficient NIR photosensitizing nanoplatform for PDT based on red‐emitting UCNPs is designed. The red emission band matches well with the efficient absorption bands of the widely used commercially available photosensitizers (Ps), benefiting the fluorescence resonance energy transfer (FRET) from UCNPs to the attached photosensitizers and thus efficiently activating them to generate cytotoxic singlet oxygen. Three commonly used photosensitizers, including chlorine e6 (Ce6), zinc phthalocyanine (ZnPc) and methylene blue (MB), are loaded onto the alpha‐cyclodextrin‐modified UCNPs to form Ps@UCNPs complexes that efficiently produce singlet oxygen to kill cancer cells under 980 nm near‐infrared excitation. Moreover, two different kinds of drugs are co‐loaded onto these nanoparticles: chemotherapy drug doxorubicin and PDT agent Ce6. The combinational therapy based on doxorubicin (DOX)‐induced chemotherapy and Ce6‐triggered PDT exhibits higher therapeutic efficacy relative to the individual means for cancer therapy in vitro.     

Shape‐Controlled Synthesis of High‐Quality Cu7S4 Nanocrystals for Efficient Light‐Induced Water Evaporation

Copper sulfides (Cu_2–xS), are a novel kind of photothermal material exhibiting significant photothermal conversion efficiency, making them very attractive in various energy conversion related devices. Preparing high quality uniform Cu_2‐xS nanocrystals (NCs) is a top priority for further energy‐and sustainability relevant nanodevices. Here, a shape‐controlled high quality Cu₇S₄ NCs synthesis strategy is reported using sulfur in 1‐octadecene as precursor by varying the heating temperature, as well as its forming mechanism. The performance of the Cu₇S₄ NCs is further explored for light‐driven water evaporation without the need of heating the bulk liquid to the boiling point, and the results suggest that as‐synthesized highly monodisperse NCs perform higher evaporation rate than polydisperse NCs under the identical morphology. Furthermore, disk‐like NCs exhibit higher water evaporation rate than spherical NCs. The water evaporation rate can be further enhanced by assembling the organic phase Cu₇S₄ NCs into a dense film on the aqueous solution surface. The maximum photothermal conversion efficiency is as high as 77.1%.     

Color‐edge detection based on discrimination of noticeable color contrasts

Color‐edge detection is an important research task in the field of image processing. Efficient and accurate edge detection will lead to higher performance of subsequent image processing techniques, including image segmentation, object‐based image coding, and image retrieval. To improve the performance of color‐edge detection while considering that human eyes are ultimate receiver of color images, the perceptually insignificant edges should avoid being over‐detected. In this article, a color‐edge detection scheme based on the perceptual color contrast is proposed. The perceptual color contrast is defined as the visible color difference across an edge in the CIE‐Lab color space. A perceptual metric for measuring the visible color difference of a target color pixel is defined by utilizing the associated perceptually indistinguishable region. The perceptually indistinguishable region for each color pixel in the CIE‐Lab color space is estimated by the design of an experiment that considers the local property due to local changes in luminance. Simulation results show that the perceptual color contrast is effectively defined and the color edges in color images are detected while most of the perceptually insignificant edges are successfully suppressed through the proposed color‐edge detection scheme. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 332–339, 2009     

DNA‐Directed Gold Nanodimers with Tunable Sizes and Interparticle Distances and Their Surface Plasmonic Properties

A quantitative understanding of the localized surface plasmon resonances (LSPRs) of metallic nanostructures has received tremendous interest. However, most of the current studies are concentrated on theoretical calculation due to the difficulty in experimentally obtaining monodisperse discrete metallic nanostructures with high purity. In this work, endeavors to assemble symmetric and asymmetric gold nanoparticle (AuNP) dimer structures with exceptional purity are reported using a DNA self‐assembly strategy through a one‐step gel electrophoresis, which greatly facilitates the preparation process and improves the final purity. In the obtained Au nanodimers, the sizes of AuNPs (13, 20, and 40 nm) and the interparticle distances (5, 10, and 15 nm) are tunable. The size‐ and distance‐dependent plasmon coupling of ensembles of single, isolated dimers in solution are subsequently investigated. The experimental measurements are correlated with the modeled plasmon optical properties of Au nanodimers, showing an expected resonance shift with changing particle sizes and interparticle distances. This new strategy of constructing monodisperse metallic nanodimers will be helpful for building more complicated nanostructures, and our theoretical and experimental understanding of the intrinsic dependence of plasmon property of metallic nanodimer on the sizes and interparticle distances will benefit the future investigation and exploitation of near‐field plasmonic properties.     

Two‐fluid model with interface sharpening

Two‐fluid models are applicable for simulations of all types of two‐phase flows ranging from separated flows with large characteristic interfacial length scales to highly dispersed flows with very small characteristic interfacial length scales. The main drawback of the two‐fluid model, when used for simulations of stratified flows, is the numerical diffusion of the interface. Stratified flows can be easily and more accurately solved with interface tracking methods; however, these methods are limited to the flows, that do not develop into dispersed types of flows. The present paper describes a new approach, where the advantage of the two‐fluid model is combined with the conservative level set method for interface tracking. The advection step of the volume fraction transport equation is followed by the interface sharpening, which preserves the thickness of the interface during the simulation. The proposed two‐fluid model with interface sharpening was found to be more accurate than the existing two‐fluid models. The mixed flow with both: stratified and dispersed flow, is simulated with the coupled model in this paper. In the coupled model, the dispersed two‐fluid model and two‐fluid model with interface sharpening are used locally, depending on the parameter which recognizes the flow regime. Copyright © 2010 John Wiley & Sons, Ltd.