Showing papers by "South China University of Technology published in 2016"
TL;DR: DehazeNet as discussed by the authors adopts convolutional neural network-based deep architecture, whose layers are specially designed to embody the established assumptions/priors in image dehazing.
Abstract: Single image haze removal is a challenging ill-posed problem. Existing methods use various constraints/priors to get plausible dehazing solutions. The key to achieve haze removal is to estimate a medium transmission map for an input hazy image. In this paper, we propose a trainable end-to-end system called DehazeNet, for medium transmission estimation. DehazeNet takes a hazy image as input, and outputs its medium transmission map that is subsequently used to recover a haze-free image via atmospheric scattering model. DehazeNet adopts convolutional neural network-based deep architecture, whose layers are specially designed to embody the established assumptions/priors in image dehazing. Specifically, the layers of Maxout units are used for feature extraction, which can generate almost all haze-relevant features. We also propose a novel nonlinear activation function in DehazeNet, called bilateral rectified linear unit, which is able to improve the quality of recovered haze-free image. We establish connections between the components of the proposed DehazeNet and those used in existing methods. Experiments on benchmark images show that DehazeNet achieves superior performance over existing methods, yet keeps efficient and easy to use.
1,880 citations
TL;DR: A radiomics nomogram that incorporates the radiomics signature, CT-reported LN status, and clinical risk factors can be conveniently used to facilitate the preoperative individualized prediction of LN metastasis in patients with CRC.
Abstract: PurposeTo develop and validate a radiomics nomogram for preoperative prediction of lymph node (LN) metastasis in patients with colorectal cancer (CRC).Patients and MethodsThe prediction model was developed in a primary cohort that consisted of 326 patients with clinicopathologically confirmed CRC, and data was gathered from January 2007 to April 2010. Radiomic features were extracted from portal venous–phase computed tomography (CT) of CRC. Lasso regression model was used for data dimension reduction, feature selection, and radiomics signature building. Multivariable logistic regression analysis was used to develop the predicting model, we incorporated the radiomics signature, CT-reported LN status, and independent clinicopathologic risk factors, and this was presented with a radiomics nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Internal validation was assessed. An independent validation cohort contained 200 consecutive p...
1,211 citations
TL;DR: This paper proposes a brief framework that incorporates industrial wireless networks, cloud, and fixed or mobile terminals with smart artifacts such as machines, products, and conveyors and concludes that the smart factory of Industrie 4.0 is achievable by extensively applying the existing enabling technologies while actively coping with the technical challenges.
Abstract: With the application of Internet of Things and services to manufacturing, the fourth stage of industrialization, referred to as Industrie 4.0, is believed to be approaching. For Industrie 4.0 to come true, it is essential to implement the horizontal integration of inter-corporation value network, the end-to-end integration of engineering value chain, and the vertical integration of factory inside. In this paper, we focus on the vertical integration to implement flexible and reconfigurable smart factory. We first propose a brief framework that incorporates industrial wireless networks, cloud, and fixed or mobile terminals with smart artifacts such as machines, products, and conveyors. Then, we elaborate the operational mechanism from the perspective of control engineering, that is, the smart artifacts form a self-organized system which is assisted with the feedback and coordination blocks that are implemented on the cloud and based on the big data analytics. In addition, we outline the main technical features and beneficial outcomes and present a detailed design scheme. We conclude that the smart factory of Industrie 4.0 is achievable by extensively applying the existing enabling technologies while actively coping with the technical challenges.
1,108 citations
TL;DR: A smart factory framework that incorporates industrial network, cloud, and supervisory control terminals with smart shop-floor objects such as machines, conveyers, and products is presented and an intelligent negotiation mechanism for agents to cooperate with each other is proposed.
1,074 citations
TL;DR: In this article, the newly emerging metal-organic frameworks (MOFs) built from metal ions and polyfunctional organic ligands have proved to be promising self-sacrificing templates and precursors for preparing various carbon-based nanomaterials, benefiting from their high surface areas, abundant metal/organic species, large pore volumes, and extraordinary tunability of structures and compositions.
Abstract: Carbon-based nanomaterials have been widely used as catalysts or catalyst supports in the chemical industry or for energy or environmental applications due to their fascinating properties. High surface areas, tunable porosity, and functionalization are considered to be crucial to enhance the catalytic performance of carbon-based materials. Recently, the newly emerging metal–organic frameworks (MOFs) built from metal ions and polyfunctional organic ligands have proved to be promising self-sacrificing templates and precursors for preparing various carbon-based nanomaterials, benefiting from their high BET surface areas, abundant metal/organic species, large pore volumes, and extraordinary tunability of structures and compositions. In comparison with other carbon-based catalysts, MOF-derived carbon-based nanomaterials have great advantages in terms of tailorable morphologies and hierarchical porosity and easy functionalization with other heteroatoms and metal/metal oxides, which make them highly efficient as...
992 citations
TL;DR: A review of the recent developments in LPPs for the synthesis of nanoparticles from the aspects of particle sizes, monodispersity and homogeneity based on the urgent application of bio-imaging, and an exhibition of new products towards diverse application fields.
Abstract: Owing to the unique mechanism of photoelectron storage and release, long persistent phosphorescence, also called long persistent luminescence or long lasting afterglow/phosphorescence, plays a pivotal role in the areas of spectroscopy, photochemistry, photonics and materials science. In recent years, more research has focused on the manipulation of the morphology, operational wavebands and persistent duration of long persistent phosphors (LPPs). These desired achievements stimulated the growing interest in designing bio-labels, photocatalysts, optical sensors, detectors and photonic devices. In this review, we present multidisciplinary research on synthetic methods, afterglow mechanisms, characterization techniques, materials system, and applications of LPPs. First, we introduce the recent developments in LPPs for the synthesis of nanoparticles from the aspects of particle sizes, monodispersity and homogeneity based on the urgent application of bio-imaging. In the later sections, we present the possible mechanisms, which involve the variation of trap distribution during the trapping and de-trapping process, complicated photo-ionization reaction of trap site levels and impurity centers together with their corresponding migration kinetics of carriers. Meanwhile, we emphasize the characterization techniques of defects, used to qualitatively or quantitatively describe the types, concentrations and depths of the traps. This review article also highlights the recent advances in suggested LPPs materials with a focus on the LPPs' hosts and optically active centers as well as their control, tuning and intrinsic links. We further discuss the classification of LPPs based on the different emission and excitation wavebands from the ultraviolet to the near-infrared region along with an overview of the activation mode of afterglow. Afterwards, we provide an exhibition of new products towards diverse application fields, including solar energy utilization, bio-imaging, diagnosis, and photocatalysts. Finally, we summarize the current achievements, discuss the problems and provide suggestions for potential future directions in the aforementioned parts.
837 citations
TL;DR: This paper proposes a trainable end-to-end system called DehazeNet, for medium transmission estimation, which takes a hazy image as input, and outputs its medium transmission map that is subsequently used to recover a haze-free image via atmospheric scattering model.
Abstract: Single image haze removal is a challenging ill-posed problem. Existing methods use various constraints/priors to get plausible dehazing solutions. The key to achieve haze removal is to estimate a medium transmission map for an input hazy image. In this paper, we propose a trainable end-to-end system called DehazeNet, for medium transmission estimation. DehazeNet takes a hazy image as input, and outputs its medium transmission map that is subsequently used to recover a haze-free image via atmospheric scattering model. DehazeNet adopts Convolutional Neural Networks (CNN) based deep architecture, whose layers are specially designed to embody the established assumptions/priors in image dehazing. Specifically, layers of Maxout units are used for feature extraction, which can generate almost all haze-relevant features. We also propose a novel nonlinear activation function in DehazeNet, called Bilateral Rectified Linear Unit (BReLU), which is able to improve the quality of recovered haze-free image. We establish connections between components of the proposed DehazeNet and those used in existing methods. Experiments on benchmark images show that DehazeNet achieves superior performance over existing methods, yet keeps efficient and easy to use.
837 citations
TL;DR: In this paper, the authors summarize the advances in the preparation methods of N-doped carbons for applications in supercapacitors and discuss and predict futuristic research trends towards the design and syntheses of Ndoped carbon-based carbons with unique properties for electrochemical energy storage.
Abstract: It is of great interest to develop new carbon-based materials as electrodes for supercapacitors because the conventional electrodes of activated carbons in supercapacitors cannot meet the ever-increasing demands for high energy and power densities for electronic devices. Due to their high electronic conductivity and improved hydrophilic properties, together with their easy syntheses and functionalization, N-doped carbons have shown a great potential in energy storage and conversion applications. In this review, after a brief introduction of electrochemical capacitors, we summarize the advances, in the recent six years, in the preparation methods of N-doped carbons for applications in supercapacitors. We also discuss and predict futuristic research trends towards the design and syntheses of N-doped carbons with unique properties for electrochemical energy storage.
821 citations
Proceedings Article•
19 Jun 2016
TL;DR: A generalized large-margin softmax (L-Softmax) loss which explicitly encourages intra-class compactness and inter-class separability between learned features and which not only can adjust the desired margin but also can avoid overfitting is proposed.
Abstract: Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs). Despite its simplicity, popularity and excellent performance, the component does not explicitly encourage discriminative learning of features. In this paper, we propose a generalized large-margin softmax (L-Softmax) loss which explicitly encourages intra-class compactness and inter-class separability between learned features. Moreover, L-Softmax not only can adjust the desired margin but also can avoid overfitting. We also show that the L-Softmax loss can be optimized by typical stochastic gradient descent. Extensive experiments on four benchmark datasets demonstrate that the deeply-learned features with L-softmax loss become more discriminative, hence significantly boosting the performance on a variety of visual classification and verification tasks.
769 citations
Posted Content•
TL;DR: In this article, a generalized large-margin softmax (L-Softmax) loss is proposed to encourage intra-class compactness and inter-class separability between learned features.
Abstract: Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs). Despite its simplicity, popularity and excellent performance, the component does not explicitly encourage discriminative learning of features. In this paper, we propose a generalized large-margin softmax (L-Softmax) loss which explicitly encourages intra-class compactness and inter-class separability between learned features. Moreover, L-Softmax not only can adjust the desired margin but also can avoid overfitting. We also show that the L-Softmax loss can be optimized by typical stochastic gradient descent. Extensive experiments on four benchmark datasets demonstrate that the deeply-learned features with L-softmax loss become more discriminative, hence significantly boosting the performance on a variety of visual classification and verification tasks.
680 citations
TL;DR: The combined pretreatment strategies are reviewed for improving the enzymatic hydrolysis of lignocellulose and realizing the comprehensive utilization of lignecellulosic materials.
TL;DR: A novel perylene bisimide (PBI) acceptor, SdiPBI-Se, in which selenium atoms were introduced into the perylene core, suggesting that non-fullerene acceptors have enormous potential to rival or even surpass the performance of their fullerene counterparts.
Abstract: Non-fullerene acceptors have recently attracted tremendous interest because of their potential as alternatives to fullerene derivatives in bulk heterojunction organic solar cells. However, the power conversion efficiencies (PCEs) have lagged far behind those of the polymer/fullerene system, mainly because of the low fill factor (FF) and photocurrent. Here we report a novel perylene bisimide (PBI) acceptor, SdiPBI-Se, in which selenium atoms were introduced into the perylene core. With a well-established wide-band-gap polymer (PDBT-T1) as the donor, a high efficiency of 8.4% with an unprecedented high FF of 70.2% is achieved for solution-processed non-fullerene organic solar cells. Efficient photon absorption, high and balanced charge carrier mobility, and ultrafast charge generation processes in PDBT-T1:SdiPBI-Se films account for the high photovoltaic performance. Our results suggest that non-fullerene acceptors have enormous potential to rival or even surpass the performance of their fullerene counterparts.
TL;DR: The improved charge separation and exposed active facets dramatically boost the photocatalytic degradation of methyl orange dye, showing the promise of 2D transition metal carbide for fabricating functional catalytic materials.
Abstract: Effectively harvesting light to generate long-lived charge carriers to suppress the recombination of electrons and holes is crucial for photocatalytic reactions. Exposing the highly active facets has been regarded as a powerful approach to high-performance photocatalysts. Herein, a hybrid comprised of {001} facets of TiO2 nanosheets and layered Ti3C2, an emerging 2D material, was synthesized by a facile hydrothermal partial oxidation of Ti3C2. The in situ growth of TiO2 nanosheets on Ti3C2 allows for the interface with minimized defects, which was demonstrated by high-resolution transmission electron microscopy and density functional theory calculations. The highly active {001} facets of TiO2 afford high-efficiency photogeneration of electron–hole pairs, meanwhile the carrier separation is substantially promoted by the hole trapping effect by the interfacial Schottky junction with 2D Ti3C2 acting as a reservoir of holes. The improved charge separation and exposed active facets dramatically boost the photo...
TL;DR: This paper analyzes the IIoT architecture, including physical layer, IWNs, industrial cloud, and smart terminals, and describes the information interaction among different devices, and proposes a software-defined IIeT architecture to manage physical devices and provide an interface for information exchange.
Abstract: In recent years, there have been great advances in industrial Internet of Things (IIoT) and its related domains, such as industrial wireless networks (IWNs), big data, and cloud computing These emerging technologies will bring great opportunities for promoting industrial upgrades and even allow the introduction of the fourth industrial revolution, namely, Industry 40 In the context of Industry 40, all kinds of intelligent equipment (eg, industrial robots) supported by wired or wireless networks are widely adopted, and both real-time and delayed signals coexist Therefore, based on the advancement of software-defined networks technology, we propose a new concept for industrial environments by introducing software-defined IIoT in order to make the network more flexible In this paper, we analyze the IIoT architecture, including physical layer, IWNs, industrial cloud, and smart terminals, and describe the information interaction among different devices Then, we propose a software-defined IIoT architecture to manage physical devices and provide an interface for information exchange Subsequently, we discuss the prominent problems and possible solutions for software-defined IIoT Finally, we select an intelligent manufacturing environment as an assessment test bed, and implement the basic experimental analysis This paper will open a new research direction of IIoT and accelerate the implementation of Industry 40
TL;DR: In this article, the authors reviewed the research progress in the development of carbon-based electrocatalysts toward hydrogen evolution reaction (HER) in acid electrolytes throughout the past few years.
TL;DR: Combination of the radiomics signature, traditional staging system, and other clinical-pathologic risk factors performed better for individualized DFS estimation in patients with early-stage NSCLC, which might enable a step forward precise medicine.
Abstract: Purpose To develop a radiomics signature to estimate disease-free survival (DFS) in patients with early-stage (stage I-II) non-small cell lung cancer (NSCLC) and assess its incremental value to the traditional staging system and clinical-pathologic risk factors for individual DFS estimation. Materials and Methods Ethical approval by the institutional review board was obtained for this retrospective analysis, and the need to obtain informed consent was waived. This study consisted of 282 consecutive patients with stage IA-IIB NSCLC. A radiomics signature was generated by using the least absolute shrinkage and selection operator, or LASSO, Cox regression model. Association between the radiomics signature and DFS was explored. Further validation of the radiomics signature as an independent biomarker was performed by using multivariate Cox regression. A radiomics nomogram with the radiomics signature incorporated was constructed to demonstrate the incremental value of the radiomics signature to the traditional staging system and other clinical-pathologic risk factors for individualized DFS estimation, which was then assessed with respect to calibration, discrimination, reclassification, and clinical usefulness. Results The radiomics signature was significantly associated with DFS, independent of clinical-pathologic risk factors. Incorporating the radiomics signature into the radiomics-based nomogram resulted in better performance (P < .0001) for the estimation of DFS (C-index: 0.72; 95% confidence interval [CI]: 0.71, 0.73) than with the clinical-pathologic nomogram (C-index: 0.691; 95% CI: 0.68, 0.70), as well as a better calibration and improved accuracy of the classification of survival outcomes (net reclassification improvement: 0.182; 95% CI: 0.02, 0.31; P = .02). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the traditional staging system and the clinical-pathologic nomogram. Conclusion The radiomics signature is an independent biomarker for the estimation of DFS in patients with early-stage NSCLC. Combination of the radiomics signature, traditional staging system, and other clinical-pathologic risk factors performed better for individualized DFS estimation in patients with early-stage NSCLC, which might enable a step forward precise medicine. © RSNA, 2016 Online supplemental material is available for this article.
TL;DR: In this paper, a core-shell In2S3@MIL-125(Ti) photocatalytic adsorbent was successfully prepared by a facile solvothermal method.
Abstract: Metal-organic frameworks (MOFs) have been attracted considerable attention in the field of energy generation and environmental remediation. In this article, a novel core–shell In2S3@MIL-125(Ti) (MLS) photocatalytic adsorbent was successfully prepared by a facile solvothermal method. The as-obtained materials were characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, N2 adsorption–desorption isotherm, X-ray photoelectron spectroscopy, UV–vis diffuse reflection spectroscopy and zeta potentials. It is indicated that the hybrids consisted of MIL-125(Ti) as the core and three-dimensional In2S3 sheets network as the shell has high surface area, mesoporous structure, and improved electronegativity and visible-light absorption. The MLS exhibited excellent adsorption performance for the removal of tetracycline (TC) from water. The adsorption process is sensitive to the solution pH, ionic strength and initial TC concentration. The Langmuir isotherm and pseudo-second-order mode could well describe the adsorption process and adsorption kinetics. The adsorption mechanism is mainly responsible for surface complexation, π–π interactions, hydrogen bonding and electrostatic interactions. Further, in TC degradation experiments under visible light exposure in presence of core–shell MLS, the optimal additive content of MIL-125(Ti) in synthesis process was 0.1 g, and the corresponding photodegradation efficiency for TC was 63.3%, which was higher than that of pure In2S3 and pure MIL-125(Ti). The improved photocatalytic performance was mainly ascribed to the opened porous structure, effective transfer of photo-generated carriers, Ti3+–Ti4+ intervalence electron transfer and the synergistic effect between MIL-125(Ti) and In2S3. The degradation by-products of TC molecules were monitored by three-dimensional excitation-emission matrix fluorescence spectroscopy. Parts of TC molecules were mineralized into CO2 and H2O. The core–shell MLS composites also revealed good performance for the removal of TC from real wastewater including medical wastewater, municipal wastewater and river water. Therefore, the novel hybrids may be used as promising photocatalytic adsorbent for wastewater purification.
TL;DR: In this paper, a rational design principle based on intrinsic molecular-structure engineering was proposed to tune the aromatic subunits in arylphenones to achieve a balanced lifetime and efficiency.
TL;DR: Two novel naphthalene diimide-based, self-doped, n-type water/alcohol-soluble conjugated polymers (WSCPs) that can be processed with a broad thickness range of 5 to 100 nm as efficient electron transporting layers (ETLs) for high-performance PSCs are reported.
Abstract: With the demonstration of small-area, single-junction polymer solar cells (PSCs) with power conversion efficiencies (PCEs) over the 10% performance milestone, the manufacturing of high-performance large-area PSC modules is becoming the most critical issue for commercial applications. However, materials and processes that are optimized for fabricating small-area devices may not be applicable for the production of high-performance large-area PSC modules. One of the challenges is to develop new conductive interfacial materials that can be easily processed with a wide range of thicknesses without significantly affecting the performance of the PSCs. Toward this goal, we report two novel naphthalene diimide-based, self-doped, n-type water/alcohol-soluble conjugated polymers (WSCPs) that can be processed with a broad thickness range of 5 to 100 nm as efficient electron transporting layers (ETLs) for high-performance PSCs. Space charge limited current and electron spin resonance spectroscopy studies confirm that ...
TL;DR: Wang et al. as mentioned in this paper proposed a method to solve the problem of high computational complexity in the context of Chemical and Biomedical Engineering at Nanyang Technological University in Singapore.
Abstract: Dr. S. Q. Wang, L. Xia, Prof. H. H. Wang School of Chemistry and Chemical Engineering South China University of Technology Guangzhou 510640 , China E-mail: hhwang@scut.edu.cn Dr. L. Zhang, Prof. H. H. Wang School of Chemical Engineering The University of Adelaide SA 5005 , Australia L. Yu, Prof. X. W. Lou School of Chemical and Biomedical Engineering Nanyang Technological University 62 Nanyang Drive Singapore 637459 , Singapore E-mail: xwlou@ntu.edu.sg
TL;DR: Diverse strategies that are proposed in the literature to provide incentives for stimulating users to participate in mobile crowd sensing applications are surveyed and divided into three categories: entertainment, service, and money.
Abstract: Recent years have witnessed the fast proliferation of mobile devices (e.g., smartphones and wearable devices) in people's lives. In addition, these devices possess powerful computation and communication capabilities and are equipped with various built-in functional sensors. The large quantity and advanced functionalities of mobile devices have created a new interface between human beings and environments. Many mobile crowd sensing applications have thus been designed which recruit normal users to contribute their resources for sensing tasks. To guarantee good performance of such applications, it's essential to recruit sufficient participants. Thus, how to effectively and efficiently motivate normal users draws growing attention in the research community. This paper surveys diverse strategies that are proposed in the literature to provide incentives for stimulating users to participate in mobile crowd sensing applications. The incentives are divided into three categories: entertainment, service, and money. Entertainment means that sensing tasks are turned into playable games to attract participants. Incentives of service exchanging are inspired by the principle of mutual benefits. Monetary incentives give participants payments for their contributions. We describe literature works of each type comprehensively and summarize them in a compact form. Further challenges and promising future directions concerning incentive mechanism design are also discussed.
TL;DR: In this paper, a fundamental investigation of the development of grain structure of 316L stainless steel fabricated by selective laser melting (SLM) was conducted, which revealed the growth mechanism of grains under rapid solidification conditions.
TL;DR: In this paper, the authors reported the production of highly thermal stable and functional cellulose nanocrystals (CNC) and nanofibrils (CNF) by hydrolysis using concentrated organic acids.
TL;DR: In this article, a PVA/ CEO/β-cyclodextrin (PVA/CEO/β -CD) antimicrobial nanofibrous film with average diameter 240 ± 40 nm was successfully fabricated under the optimal conditions.
TL;DR: The attractive fuel-free propulsion performance, fast movement triggering response, low light energy requirement, and precise motion control of the TiO2-Au Janus photocatalytic micromotor hold considerable promise for diverse practical applications.
Abstract: A highly efficient light-driven photocatalytic TiO2–Au Janus micromotor with wireless steering and velocity control is described. Unlike chemically propelled micromotors which commonly require the addition of surfactants or toxic chemical fuels, the fuel-free Janus micromotor (diameter ∼1.0 μm) can be powered in pure water under an extremely low ultraviolet light intensity (2.5 × 10–3 W/cm2), and with 40 × 10–3 W/cm2, they can reach a high speed of 25 body length/s, which is comparable to common Pt-based chemically induced self-electrophoretic Janus micromotors. The photocatalytic propulsion can be switched on and off by incident light modulation. In addition, the speed of the photocatalytic TiO2–Au Janus micromotor can be accelerated by increasing the light intensity or by adding low concentrations of chemical fuel H2O2 (i.e., 0.1%). The attractive fuel-free propulsion performance, fast movement triggering response, low light energy requirement, and precise motion control of the TiO2–Au Janus photocataly...
TL;DR: This state-of-the-art review will provide a platform for understanding the intricate details of heteroatom-doped CDs, a summary of the latest progress in the field, and related applications in biology and is expected to inspire further developments in this exciting class of materials.
Abstract: Heteroatom-doped carbon dots (CDs), due to their excellent photoluminescence (PL) properties, attracted widespread attention recently and demonstrated immense promise for diverse applications, particularly for biological applications. The objective of this feature article is to provide a comprehensive overview of the recent progress in the research and development of heteroatom-doped CDs and a detailed description of the influence of single or co-doping heteroatoms on their PL behavior. The most recent understanding and critical insights into the PL mechanism of heteroatom-doped CDs are also highlighted. Moreover, potential bio-related applications of heteroatom-doped CDs in biosensing, bioimaging, and theranostics are also reviewed. This state-of-the-art review will provide a platform for understanding the intricate details of heteroatom-doped CDs, a summary of the latest progress in the field, and related applications in biology and is expected to inspire further developments in this exciting class of materials.
TL;DR: The chemical structure, composites, morphologies and optical properties of the obtained products are well-characterized by XRD, FTIR, TEM, EDS, XPS and UV-Vis DRS, and the photocatalyst exhibits high stability and reusability.
Abstract: Ag nanoparticles were deposited on the surface of g-C3N4 by a chemical reduction method to increase visible-light absorption via the localized surface plasmon resonance effect, resulting in the reduced recombination of photo-generated electron–holes and enhanced photocatalytic activity. The Ag/g-C3N4 composite with a Ag loading of 3 wt% has the optimum photoactivity that is almost 3.6 and 3.4 times higher than pure g-C3N4 and the same photocatalysis system which has been reported, respectively. Fluorescein was introduced as a photosensitizer and H2 evolution soared to 2014.20 μmol g−1 h−1 and the rate is even about 4.8 times higher than that of the 3 wt% Ag/g-C3N4 composite. The chemical structure, composites, morphologies and optical properties of the obtained products are well-characterized by XRD, FTIR, TEM, EDS, XPS and UV-Vis DRS. Meanwhile, the photocatalyst exhibits high stability and reusability.
TL;DR: In this paper, a facile, inexpensive and green method to implement lightweight biodegradable poly ( l -lactic acid) (PLLA)-multiwalled carbon nanotubes (MWCNTs) nanocomposite foams using a combinatorial technology of pressure-induced flow (PIF) processing and supercritical carbon dioxide (Sc-CO2) foaming was reported.
TL;DR: This review covers existing research achievements on the mechanisms of isolated mushroom polysaccharides, particularly (1→3)-β-D-glucans, and describes the function in modulating the immune system and potential tumor-inhibitory effects of polySaccharides.
TL;DR: Computational calculations demonstrate that sulfur-doped graphene (SGS) has a stronger affinity for Sb2S3 and the discharge products than pure graphene, resulting in a robust composite architecture for outstanding cycling stability.
Abstract: Sodium ion batteries (SIBs) have been considered a promising alternative to lithium ion batteries for large-scale energy storage. However, their inferior electrochemical performances, especially cyclability, become the major challenge for further development of SIBs. Large volume change and sluggish diffusion kinetics are generally considered to be responsible for the fast capacity degradation. Here we report the strong chemical bonding of nanostructured Sb2S3 on sulfur-doped graphene sheets (Sb2S3/SGS) that enables a stable capacity retention of 83% for 900 cycles with high capacities and excellent rate performances. To the best of our knowledge, the cycling performance of the Sb2S3/SGS composite is superior to those reported for any other Sb-based materials for SIBs. Computational calculations demonstrate that sulfur-doped graphene (SGS) has a stronger affinity for Sb2S3 and the discharge products than pure graphene, resulting in a robust composite architecture for outstanding cycling stability. Our stu...