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Through adjusting the pH of the silver ammonia solution (Ag(NH3)2OH), different microstructure of silver phosphate (Ag3PO4) was prepared via simple precipitation method. The effect of pH on the mic...

AgBr/BiVO4 photocatalysts with heterojunction structures were prepared using a hydrothermal method. To analyse phase composition and microstructure, samples were characterised by X-ray diffraction ...

Pure copper is widely used in integrated circuit (IC) and national defense fields for its good electrical and thermal conductivity. Extreme requirements such as large diameter to thickness ratio, low flatness and high surface integrity for thin substrates of pure copper are difficult to achieve due to its poor rigidity and high plasticity. Processing methods relying on mechanical action such as turning, lapping and chemical mechanical polishing (CMP) may cause high residual stress and subsurface damage which results in deteriorating the flatness and surface integrity of substrates. As an alternative method, electrochemical mechanical polishing (ECMP) is adopted to achieve low flatness and high surface integrity of copper substrates. Flatness and surface integrity of substrates after ECMP were investigated in this paper. Surface integrity indicators including surface roughness, residual stress, micro hardness, and subsurface damage were quantitatively evaluated. The results show that flatness, surface roughness, micro hardness, residual stress as well as thickness of deformation layer were decreased by ECMP.

In the electrochemical mechanical polishing (ECMP) of copper, hydroxyethylidene diphosphonic acid (HEDP) can work with other water treatment agents to suppress electrolysis and smooth the metal surface. According to Faraday's law, a conventional operating potential lower than 4 V vs. SCE limits the material removal rate (MRR). To solve this problem, potentiodynamic corrosion, potentiostatic corrosion and ECMP experiments were conducted at higher potentials to study the feasibility of the process. The results show that at 6 V vs. SCE, the roughness of a copper wafer was improved, with a MRR of about 0.9 μm·min−1, higher than that obtained at the conventional potential. A sample of the barrier film on the copper surface was collected and analyzed by energy dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FTIR) and mass spectrometry to investigate the reaction mechanism. It is shown that the copper ions ionized from the working electrode (WE) react with two HEDP molecules to form the coordination compound [CuL2]6−, then K+ combines with [CuL2]6− to produce the coordination compound [KCuL2]5−. Keywords: Hydroxyethylidene diphosphonic acid, Electrochemical mechanical polishing, Copper, Reaction mechanism

In this paper, submicron-sized spherical Sr2MgSi2O7:Eu2+, Dy3+ phosphors were prepared via sol–gel methods and hydrothermal coprecipitation methods. The effect of different preparation methods on the luminescence properties and microstructures were studied using X-ray diffraction, fluorescence spectra analysis, decay curves, scanning electron microscopy, transmission electron microscopy and laser particle size analysis. Results indicate that the average size of the phosphors via sol–gel methods and hydrothermal coprecipitation methods were 0.711 and 0.389 µm, respectively, and their luminous intensities increased by 20 and 80% as compared to phosphors of the solid state methods, respectively.

Long afterglow phosphors of Sr1.956MgSi2O7: 0.004Eu2+, 0.04Dy3+ and Sr1.94MgSi2O7: 0.004Eu2+, 0.04Dy3+, 0.016Er3+ were successfully synthesized via the sol–gel method. The phase compositions and luminescent properties of the phosphors were analyzed by X-ray diffraction (XRD), fluorescence spectra and decay curves. Compared with the undoped phosphor, the crystallinity of Er3+ co-doping phosphors is decreased. Luminescence spectra show the main peak of excitation was 274, 356 nm and the main emission peak was 467 nm. Furthermore, Sr1.94MgSi2O7: 0.004Eu2+, 0.04Dy3+, 0.016Er3+ show excellent luminescent properties, and its initial luminous intensity increased by 1.4 times than Sr1.956MgSi2O7: 0.004Eu2+, 0.04Dy3+. The mechanism of Sr1.94MgSi2O7: 0.004Eu2+, 0.04Dy3+, 0.016Er3+ enhancement has been discussed.

Li4Ti5O12 (LTO) anode materials have attracted attention owing to its structural stability and negligible volume change. However, its application is still restricted due to the low conductivity and Li+ diffusion coefficient. To address these disadvantages, herein, Y3+ doped Li4Ti5-xYxO12 (LYTO) with Y2Ti2O7 surface modification anode materials have been synthesized by an easy solid-state reaction with ball milling activating method using Y(NO3)3 as the dopant. The structural analysis shows that Y3+ doping does not change the crystal structure of LTO and exhibits a uniform particle size distribution. When applied to the anodes of lithium ion batteries, Li4Ti4.8Y0.2O12 possess outstanding long-cycle stability and excellent rate performance. The discharge specific capacity achieves 173 mAh g−1 after 300 cycles at a current density of 1 A g−1 and the voltage range of 1–3 V and 92 mAh g−1 after 1000 cycles at the current density of 7 A g−1 (40C), respectively. In addition, full cells are assembled using Li4Ti4.8Y0.2O12 as anodes and LiCoO2 as cathodes. The specific capacity of coin full cell remains 150 mAh g−1 after 100 cycles at 0.2C, while the pouch full cell exhibits 149 mAh g−1 under the same conditions. These results clearly confirm that LYTO can be considered as a promising electrode material for high performance lithium-ion batteries.

Li4Ti5O12/NiO (LTO/NiO) composites with various NiO contents were prepared successfully as anode materials for high-performance lithium-ion battery. The preparation procedure consisted of high-energy ball milling, high-temperature calcination, and solution coating in succession. Several techniques such as X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area analysis, scanning electron microscopy (SEM), transmission electron microscopy (TEM), galvanostatic charge-discharge, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) were applied to fully investigate the micromorphology, composition structure, and electrochemical performances of the LTO/NiO composites. It was found that all the LTO/NiO composites showed higher discharge capacity than the pure LTO anode within the representative 20 cycles. The LTO/5 wt.% NiO, which had the largest specific surface area of 2.1229 m(2) g(-1) among all the LTO/NiO composites, delivered a capacity of 203 mAh g(-1) in a voltage window of 0.5-3.0 V at 1 C rate and retained a capacity of 176 mAh g(-1) after 100 cycles. The CV and EIS analysis indicated that the charge/discharge processes of LTO/NiO composites included the Li+ diffusion into or out of LTO phase and the redox reaction of NiO phase. The results demonstrate that the surface modification of LTO with small amounts of NiO nanoparticles can decrease the overall charge transfer resistance by forming in situ the electron-conductive Ni, leading to the improved electrochemical behavior of the composites.

Magnetic nanoparticle clusters (MNCs) are a class of secondary structural materials that comprise chemically defined nanoparticles assembled into clusters of defined size. Herein, MNCs are fabricated through a one-pot solvothermal reaction featuring self-limiting assembly of building blocks and the controlled reorganization process. Such growth-dissolution-regrowth fabrication mechanism overcomes some limitations of conventional solvothermal fabrication methods with regard to restricted available feature size and structural complexity, which can be extended to other oxides (as long as one can be chelated by EDTA-2Na). Based on this method, the nanoparticle size of MNCs is tuned between 6.8 and 31.2 nm at a fixed cluster diameter of 120 nm, wherein the critical size for superparamagnetic-ferromagnetic transition is estimated from 13.5 to 15.7 nm. Control over the nature and secondary structure of MNCs gives an excellent model system to understand the nanoparticle size-dependent magnetic properties of MNCs. MNCs have potential applications in many different areas, while this work evaluates their cytotoxicity and Pb(2+) adsorption capacity as initial application study.

Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources, semantic context has been exploited in AIA and brings promising results. However, previous works either casted the problem into structural classification or adopted multi-layer modeling, which suffer from the problems of scalability or model efficiency. In this paper, we propose a novel discriminative Conditional Random Field (CRF) model for semantic context modeling in AIA, which is built over semantic concepts and treats an image as a whole observation without segmentation. Our model captures the interactions between semantic concepts from both semantic level and visual level in an integrated manner. Specifically, we employ graph structure to model contextual relationships between semantic concepts. The potential functions are designed based on linear discriminative models, which enables us to propose a novel decoupled hinge loss function for maximal margin parameter estimation. We train the model by solving a set of independent quadratic programming problems with our derived contextual kernel. The experiments are conducted on commonly used benchmarks: Corel and TRECVID data sets for evaluation. The experimental results show that compared with the state-of-the-art methods, our method achieves significant improvement on annotation performance.

The semantic contextual information is shown to be an important resource for improving the scene and image recognition, but is seldom explored in the literature of previous distance metric learning (DML) for images. In this work, we present a novel Contextual Metric Learning (CML) method for learning a set of contextual distance metrics for real world multi-label images. The relationships between classes are formulated as contextual constraints for the optimization framework to leverage the learning performance. In the experiment, we apply the proposed method for automatic image annotation task. The experimental results show that our approach outperforms the start-of-the-art DML algorithms.

A simple solution-liquid-solid method under hydrothermal conditions has been developed for the one-pot synthesis of Ga-doped/self-supported aligned ZnO 1-D nanostructures, which exhibits enhanced activity for the photocatalytic degradation of rhodamine B.