Huaqiao University

A universal but simple procedure for identifying the α, β and γ phases in PVDF using FTIR is proposed and validated. An integrated quantification methodology for individual β and γ phase in mixed systems is also proposed.

A composite film of nickel sulfide/platinum/titanium foil (NiS/Pt/Ti) with low cost and high electrocatalytic activity was synthesized by the use of an in situ electropolymerization route and proposed as a counter electrode (CE) catalyst for flexible dye-sensitized solar cells (FDSSCs). The FDSSC with the NiS/Pt/Ti CE exhibited a comparable power conversion efficiency of 7.20% to the FDSSC with the platinum/titanium (Pt/Ti) CE showing 6.07%. The surface morphology of the NiS/Pt/Ti CE with one-dimensional (1D) structure is characterized by using the scanning electron microscopy (SEM). The NiS/Pt/Ti CE also displayed multiple electrochemical functions of excellent conductivity, great electrocatalytic ability for iodine/triiodine, and low charge transfer resistance of 2.61 ± 0.02 Ω cm(2), which were characterized by using the cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and Tafel polarization plots. The photocurrent-photovoltage (J-V) character curves were further used to calculate the theoretical optical light performance parameters of the FDSSCs. It may be said that the NiS/Pt/Ti counter electrode is a promising catalytic material to replace the expensive platinum in FDSSCs.

O-doped g-C(3)N(4) was synthesized for the first time by a facile H(2)O(2) hydrothermal approach. The O-doping in the g-C(3)N(4) lattice could induce intrinsic electronic and band structure modulation, resulting in its absorbance edge up to 498 nm and enhanced visible-light photoactivity, consequently.

Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target. Unfortunately, they typically call for tedious and heuristic configurations. To address this issue, we propose a simple yet effective visual tracking framework (named Siamese Box Adaptive Network, SiamBAN) by exploiting the expressive power of the fully convolutional network (FCN). SiamBAN views the visual tracking problem as a parallel classification and regression problem, and thus directly classifies objects and regresses their bounding boxes in a unified FCN. The no-prior box design avoids hyper-parameters associated with the candidate boxes, making SiamBAN more flexible and general. Extensive experiments on visual tracking benchmarks including VOT2018, VOT2019, OTB100, NFS, UAV123, and LaSOT demonstrate that SiamBAN achieves state-of-the-art performance and runs at 40 FPS, confirming its effectiveness and efficiency. The code will be available at https://github.com/hqucv/siamban.

Recently, deep convolutional neural network (CNN) has achieved great success for image restoration (IR) and provided hierarchical features at the same time. However, most deep CNN based IR models do not make full use of the hierarchical features from the original low-quality images; thereby, resulting in relatively-low performance. In this work, we propose a novel and efficient residual dense network (RDN) to address this problem in IR, by making a better tradeoff between efficiency and effectiveness in exploiting the hierarchical features from all the convolutional layers. Specifically, we propose residual dense block (RDB) to extract abundant local features via densely connected convolutional layers. RDB further allows direct connections from the state of preceding RDB to all the layers of current RDB, leading to a contiguous memory mechanism. To adaptively learn more effective features from preceding and current local features and stabilize the training of wider network, we proposed local feature fusion in RDB. After fully obtaining dense local features, we use global feature fusion to jointly and adaptively learn global hierarchical features in a holistic way. We demonstrate the effectiveness of RDN with several representative IR applications, single image super-resolution, Gaussian image denoising, image compression artifact reduction, and image deblurring. Experiments on benchmark and real-world datasets show that our RDN achieves favorable performance against state-of-the-art methods for each IR task quantitatively and visually.

Dye-sensitized solar cells (DSSCs) are regarded as prospective solar cells for the next generation of photovoltaic technologies and have become research hotspots in the PV field. The counter electrode, as a crucial component of DSSCs, collects electrons from the external circuit and catalyzes the redox reduction in the electrolyte, which has a significant influence on the photovoltaic performance, long-term stability and cost of the devices. Solar cells, dye-sensitized solar cells, as well as the structure, principle, preparation and characterization of counter electrodes are mentioned in the introduction section. The next six sections discuss the counter electrodes based on transparency and flexibility, metals and alloys, carbon materials, conductive polymers, transition metal compounds, and hybrids, respectively. The special features and performance, advantages and disadvantages, preparation, characterization, mechanisms, important events and development histories of various counter electrodes are presented. In the eighth section, the development of counter electrodes is summarized with an outlook. This article panoramically reviews the counter electrodes in DSSCs, which is of great significance for enhancing the development levels of DSSCs and other photoelectrochemical devices.

Abstract Although silicon is a promising anode material for lithium-ion batteries, scalable synthesis of silicon anodes with good cyclability and low electrode swelling remains a significant challenge. Herein, we report a scalable top-down technique to produce ant-nest-like porous silicon from magnesium-silicon alloy. The ant-nest-like porous silicon comprising three-dimensional interconnected silicon nanoligaments and bicontinuous nanopores can prevent pulverization and accommodate volume expansion during cycling resulting in negligible particle-level outward expansion. The carbon-coated porous silicon anode delivers a high capacity of 1,271 mAh g −1 at 2,100 mA g −1 with 90% capacity retention after 1,000 cycles and has a low electrode swelling of 17.8% at a high areal capacity of 5.1 mAh cm −2 . The full cell with the prelithiated silicon anode and Li(Ni 1/3 Co 1/3 Mn 1/3 )O 2 cathode boasts a high energy density of 502 Wh Kg −1 and 84% capacity retention after 400 cycles. This work provides insights into the rational design of alloy anodes for high-energy batteries.

Starch is a natural polymer which possesses many unique properties and some shortcoming simultaneously. Some synthetic polymers are biodegradable and can be tailor-made easily. Therefore, by combining the individual advantages of starch and synthetic polymers, starch-based completely biodegradable polymers (SCBP) are potential for applications in biomedical and environmental fields. Therefore it received great attention and was extensively investigated. In this paper, the structure and characteristics of starch and some synthetic degradable polymers are briefly introduced. Then, the recent progress about the preparation of SCBP via physical blending and chemical modification is reviewed and discussed. At last, some examples have been presented to elucidate that SCBP are promising materials for various applications and their development is a good solution for reducing the consumption of petroleum resources and environmental problem.

Active plasmonics is a burgeoning and challenging subfield of plasmonics. It exploits the active control of surface plasmon resonance. In this review, a first-ever in-depth description of the theoretical relationship between surface plasmon resonance and its affecting factors, which forms the basis for active plasmon control, will be presented. Three categories of active plasmonic structures, consisting of plasmonic structures in tunable dielectric surroundings, plasmonic structures with tunable gap distances, and self-tunable plasmonic structures, will be proposed in terms of the modulation mechanism. The recent advances and current challenges for these three categories of active plasmonic structures will be discussed in detail. The flourishing development of active plasmonic structures opens access to new application fields. A significant part of this review will be devoted to the applications of active plasmonic structures in plasmonic sensing, tunable surface-enhanced Raman scattering, active plasmonic components, and electrochromic smart windows. This review will be concluded with a section on the future challenges and prospects for active plasmonics.

Mesoporous silica nanoparticles (MSNs), one of the important porous materials, have garnered interest owing to their highly attractive physicochemical features and advantageous morphological attributes. They are of particular importance for use in diverse fields including, but not limited to, adsorption, catalysis, and medicine. Despite their intrinsic stable siliceous frameworks, excellent mechanical strength, and optimal morphological attributes, pristine MSNs suffer from poor drug loading efficiency, as well as compatibility and degradability issues for therapeutic, diagnostic, and tissue engineering purposes. Collectively, the desirable and beneficial properties of MSNs have been harnessed by modifying the surface of the siliceous frameworks through incorporating supramolecular assemblies and various metal species, and through incorporating supramolecular assemblies and various metal species and their conjugates. Substantial advancements of these innovative colloidal inorganic nanocontainers drive researchers in promoting them toward innovative applications like stimuli (light/ultrasound/magnetic)-responsive delivery-associated therapies with exceptional performance in vivo. Here, a brief overview of the fabrication of siliceous frameworks, along with discussions on the significant advances in engineering of MSNs, is provided. The scope of the advancement in terms of structural and physicochemical attributes and their effects on biomedical applications with a particular focus on recent studies is emphasized. Finally, interesting perspectives are recapitulated, along with the scope toward clinical translation.

A new nearly cubic NH2CH═NH2PbI3 (FAPbI3) perovskite was synthesized for the mesoscopic solar cells. The measured band gap of bulk FAPbI3 is 1.43 eV and it is therefore potentially superior than the CH3NH3PbI3 (MAPbI3) as the light harvester. A homogeneous FAPbI3 perovskite layer was deposited on the TiO2 surface by utilizing the in situ dipping technology. As a result, a high efficiency of 7.5% was achieved using P3HT as the hole transport material. The nearly cubic crystal structure and appropriate band gap render this new FAPbI3 perovskite extremely attractive for next generation high-efficiency low-cost solar cells.

Three novel complexes, Cd3tma2*13H2O (1), Cd3tma2*dabco*2H2O (2), and Cd3Htma3*8H2O (3) (tma = trimesate), of cadmium(II)-trimesate coordination polymers are obtained from hydrothermal reaction. 1 (C18H32O25Cd3) crystallizes in the monoclinic C2/c space group [a = 18.985(2) A, b = 7.3872(6) A, c = 20.432(2) A, = 97.1660(10), and Z = 4]. 2 (C24H22N2O14Cd3) crystallizes in the monoclinic P2(1)/c space group [a = 10.1323(2) A, b = 19.5669(5) A, c = 13.15880(10) A, = 108.9810(10), and Z = 4]. 3 (C27H28O26Cd3) belongs to the trigonal P31c space group [a = 15.7547(3) A, b = 15.7547(3) A, c = 7.93160(10) A, and Z = 2]. The Cd(II) centers in the three complexes are bridged by tma ligands in the coordination fashion of unidentate, bridging unidentate, bidentate, chelating bis-bidentate, chelating/bridging bis-bidentate, or chelating/bridging bidentate to form the T-shaped molecular bilayer motif for 1, chicken-wire-like motif for 2, and honeycomb-like porous structure for 3, respectively, in which the T-shaped molecular bilayer motif and chicken-wire-like motif are further interlinked in interdigitating or alternating fashion to construct the different coordination architectures. These three complexes exhibit strong fluorescent emission bands at 355 nm (lambda(ex) = 220 nm) for 1, 437 nm (lambda(ex) = 365 nm) for 2, and 353 nm (lambda(ex) = 218 nm) for 3 in the solid state at room temperature.

Wet ball milling was used to exfoliate graphite platelets into graphenes in a liquid medium. Multi-layered graphite nanosheets with a thickness of 30 to 80 nm were dispersed into N,N-dimethylformamide (DMF) and exfoliated by shear-force-dominated ball milling carried out in a planetary mill. After high-speed centrifugation, irregular shaped single- and few-layer graphene sheets (≤3 layers) having a thickness around 0.8–1.8 nm were found from the supernatant. The graphenes were identified and characterized using transmission and scanning electron microscopy, electron diffraction, atomic force microscopy and Raman spectroscopy. The electrical conductivity of the graphene powder was ∼1.2 × 103 S m−1 at room temperature.

at 70 °C).

Although widely used in many applications, accurate and efficient human action recognition remains a challenging area of research in the field of computer vision. Most recent surveys have focused on narrow problems such as human action recognition methods using depth data, 3D-skeleton data, still image data, spatiotemporal interest point-based methods, and human walking motion recognition. However, there has been no systematic survey of human action recognition. To this end, we present a thorough review of human action recognition methods and provide a comprehensive overview of recent approaches in human action recognition research, including progress in hand-designed action features in RGB and depth data, current deep learning-based action feature representation methods, advances in human⁻object interaction recognition methods, and the current prominent research topic of action detection methods. Finally, we present several analysis recommendations for researchers. This survey paper provides an essential reference for those interested in further research on human action recognition.

Abstract Metal‐free heterostructure photocatalysts composed of black phosphorus (BP) and polymeric carbon nitride (CN) are successfully synthesized via a one‐step liquid exfoliation method assisted by sonication. The combination of BP with CN strengthens the visible‐light harvesting ability, facilitates the charge separation in the photocatalytic process, and renders promoted activity of photoinduced molecular oxygen activation, such as superoxide radicals (·O 2 − ) evolution and H 2 O 2 production. This work highlights that coupling semiconductors with well‐matched band levels provide a flexible route to enhance the performance of photocatalysts for producing reactive oxygen species, and gives ideas for the design of highly active and metal‐free materials toward sustainable solar‐to‐chemical energy conversion and environmental remediation.

Though the mechanism of MEA-CO2 system has been widely studied, there is few literature on the detailed mechanism of CO2 capture into MEA solution with different CO2 loading during absorption/desorption processes. To get a clear picture of the process mechanism, (13)C nuclear magnetic resonance (NMR) was used to analyze the reaction intermediates under different CO2 loadings and detailed mechanism on CO2 absorption and desorption in MEA was evaluated in this work. The results demonstrated that the CO2 absorption in MEA started with the formation of carbamate according to the zwitterion mechanism, followed by the hydration of CO2 to form HCO3(-)/CO3(2-), and accompanied by the hydrolysis of carbamate. It is interesting to find that the existence of carbamate will be influenced by CO2 loading and that it is rather unstable at high CO2 loading. At low CO2 loading, carbamate is formed fast by the reaction between CO2 and MEA. At high CO2 loading, it is formed by the reaction of CO3(-)/CO3(2-) with MEA, and the formed carbamate can be easily hydrolyzed by H(+). Moreover, CO2 desorption from the CO2-saturated MEA solution was proved to be a reverse process of absorption. Initially, some HCO3(-) were heated to release CO2 and other HCO3(-) were reacted with carbamic acid (MEAH(+)) to form carbamate, and the carbamate was then decomposed to MEA and CO2.

Nitrogen-deficient graphitic carbon nitride (g-C3N4−x) was synthesized by a hydrothermal treatment using ammonium thiosulfate as an oxidant. The as-prepared photocatalyst was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), nitrogen adsorption–desorption, Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), elemental analysis (EA), electron paramagnetic resonance (EPR), UV-vis diffuse reflectance spectroscopy (UV-vis DRS) and photoluminescence (PL) spectroscopy. The visible-light-driven photocurrent measurement was performed by several on–off cycles of intermittent irradiation. The photocatalytic activity of catalysts was evaluated by splitting water under visible-light irradiation (λ > 420 nm). Results demonstrated that the photoactivity of g-C3N4−x was enhanced greatly by the deficiency of the terminal amino species on the catalysts. The average H2 evolution rate on g-C3N4−x was 31.6 μmol h−1, which was ca. 3 times higher than that on pristine g-C3N4. It was revealed that the unique nitrogen-deficient structure of g-C3N4−x played an important role in broadened visible-light absorption and efficient electron–hole separation, mainly accounting for the improved photocatalytic activity.

In this paper, a novel heuristic structure optimization methodology for radial basis probabilistic neural networks (RBPNNs) is proposed. First, a minimum volume covering hyperspheres (MVCH) algorithm is proposed to select the initial hidden-layer centers of the RBPNN, and then the recursive orthogonal least square algorithm (ROLSA) combined with the particle swarm optimization (PSO) algorithm is adopted to further optimize the initial structure of the RBPNN. The proposed algorithms are evaluated through eight benchmark classification problems and two real-world application problems, a plant species identification task involving 50 plant species and a palmprint recognition task. Experimental results show that our proposed algorithm is feasible and efficient for the structure optimization of the RBPNN. The RBPNN achieves higher recognition rates and better classification efficiency than multilayer perceptron networks (MLPNs) and radial basis function neural networks (RBFNNs) in both tasks. Moreover, the experimental results illustrated that the generalization performance of the optimized RBPNN in the plant species identification task was markedly better than that of the optimized RBFNN.

Chest X-ray film is the most widely used and common method of clinical examination for pulmonary nodules. However, the number of radiologists obviously cannot keep up with this outburst due to the sharp increase in the number of pulmonary diseases, which increases the rate of missed diagnosis and misdiagnosis. The method based on deep learning is the most appropriate way to deal with such problems so far. The main research in this paper was using inception-v3 transfer learning model to classify pulmonary images, and finally to get a practical and feasible computer-aided diagnostic model. The computer-aided diagnostic model could improve the accuracy and rapidity of doctors in the diagnosis of thoracic diseases. In this experiment, we augmented the data of pulmonary images, then used the fine-tuned Inception-v3 model based on transfer learning to extract features automatically, and used different classifiers (Softmax, Logistic, SVM) to classify the pulmonary images. Finally, it was compared with various models based on the original Deep Convolution Neural Network (DCNN) model. The experiment proved that the experiment based on transfer learning was meaningful for pulmonary image classification. The highest sensitivity and specificity are 95.41% and 80.09% respectively in the experiment, and the better pulmonary image classification performance was obtained than other methods.