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Hierarchical structures in shell with transition metal underneath is a promising design for high-performance and low-cost heterogeneous nanocatalysts (NCs). Such a design enables the optimum extent of synergetic effects in NC surface. It facilitates intermediate reaction steps and, therefore, boosts activity of NC in oxygen reduction reaction (ORR). In this study, carbon nanotube (CNT)-supported ternary metallic NC comprising Cucluster-in-Pdcluster nanocrystal and surface decoration of atomic Pt clusters (14 wt %) is synthesized by using the wet chemical reduction method with sequence and reaction time controls. By annealing in H2 environment (H2/N2 = 9:1, 10 sccm) at 600 K for 2 h, specific activity of Cu@Pd/Pt is substantially improved by ∼2.0-fold as compared to that of the pristine sample and commercial Pt catalysts. By cross-referencing results of electron microscopic, X-ray spectroscopic, and electrochemical analyses, we demonstrated that reduction annealing turns ternary NC into complex of Cu3Pt al...

Surface tailoring as well as inner structure design at the atomic scale are of primary importance for the activity and durability of nanocatalysts (NCs) in electrochemical applications. In this study, a novel structural candidate containing a Cu core and Pt cluster decorated Pd shell with a balance struck between the performance and cost considerations for the oxygen reduction reaction (ORR) is proposed. The carbon nanotube supported NCs are synthesized using a wet chemical reduction method with different ratios of Pt from 5 to 14 wt%. Our results demonstrate a robust assessment for programming the ORR performance by Pt loading control in the NCs. For the optimum case (∼5.0 wt% of Pt), the mass activity (M.A.) is ∼639 mA mgPt−1. This value is improved by 9-folds compared to that of commercial Pt NC (J.M.-Pt/C) at 0.85 V vs. RHE and can be attributed to the formation of a high density of surface truncations in the NC surface. When the Pt loading is ∼9 wt%, the NC forms multi-faceted twin particles with low surface defects and thus has the highest stability (+/− 0.5% of current vibration) in an accelerated degradation test (ADT) among the experimental samples. Further increasing Pt to 14 wt%, restructures the NC into a local ordered crystal with certain amounts of Pt island clusters in the surface. Such a phenomenon results in a vibration of the current density by surface restructure upon oxidation and reduction of Pt oxides in a ADT test and possesses a residual current density of 92% compared to its original value after 40 k cycles. Most importantly, our observations bring fundamental and practical insights into the role of surface defects in electrocatalysis and present a new strategy to surmount a dilemma between the reliability and activity of ORR NCs.

Solar is an important energy resource at present, and thus how to generate power efficiently by using solar is the crucial research topics in next generation power system. Among these research topics, managing and maintaining the solar panels for avoiding the situation which cannot generate power due to damage is also an interesting issue. Because the cost of developing the solar plant is expensive and needing the extra-cost to maintain solar, how to maintain the solar panels effectively is another important issue. In this study, an anomaly detection mechanism with using the semi-supervision learning model is proposed to pre-identify whether the solar panel will occur the abnormal events or not. In the anomaly detection mechanism, this study uses the clustering algorithm to filter the normal events, and then adopts the neuron network model, Autoencoder, to develop the classificator. This study takes the data collected from a 500kW solar power plant to train models and verify the feasibility of the proposed anomaly detection mechanism.

Hierarchical structures in shell with transition metal underneath is a promising design for high-performance and low-cost heterogeneous nanocatalysts (NCs). Such a design enables the optimum extent of synergetic effects in NC surface. It facilitates intermediate reaction steps and, therefore, boosts activity of NC in oxygen reduction reaction (ORR). In this study, carbon nanotube (CNT)-supported ternary metallic NC comprising Cucluster-in-Pdcluster nanocrystal and surface decoration of atomic Pt clusters (14 wt %) is synthesized by using the wet chemical reduction method with sequence and reaction time controls. By annealing in H2 environment (H2/N2 = 9:1, 10 sccm) at 600 K for 2 h, specific activity of Cu@Pd/Pt is substantially improved by ∼2.0-fold as compared to that of the pristine sample and commercial Pt catalysts. By cross-referencing results of electron microscopic, X-ray spectroscopic, and electrochemical analyses, we demonstrated that reduction annealing turns ternary NC into complex of Cu3Pt alloy and CuxPd1–x alloy. Such a transition preserves Pt and Pd in metallic phases, therefore improving the activity by ∼29% and the stability of NC in an accelerated degradation test (ADT) as compared to those of pristine Cu@Pd/Pt in 36 000 cycles at 0.85 V (vs RHE). This study presents robust H2 annealing for structure stabilization of NC and systematic characterizations for rationalization of the corresponding mechanisms. These results provide promising scenarios for facilitation of heterogeneous NC in ORR applications.

A ternary metallic CuPdPt nanocatalyst (NC) is synthesized using a wet chemical reduction method, which is sequentially designed, in the presence of acid treated carbon nanotubes. This NC is a nanocrystal with a configuration of a Cu@Pd core and atomic Pt clusters (∼9 wt%) on the top (Cu@Pd/Pt). A residual current of 92.6%, 5.2 times higher than that of commercial Pt catalysts (at 0.85 V vs. RHE), is retained after 40 000 cycles of an accelerated degradation test (ADT). Atomic and electronic structure analyses show that such exclusive stability mainly results from electron localization at Pt clusters in heterogeneous interfaces of the Cu–Pd core. Most importantly, we develop a robust ternary NC, which shows outstanding MA, superior chemical durability, and ∼90 wt% lower Pt loading than commercial Pt NCs in the oxygen reduction reaction.

Electrochemical carburization (ECC) of pure iron in a 1 M Na2SO4 bath containing supercritical CO2 (sc-CO2) fluids was investigated. The experimental results showed that the carbon-bearing films electrodeposited on iron substrate could be successfully produced under either galvanostatic or potentiostatic modes. The formation of carbon film on metal substrate and the subsequent carburization of iron substrate were analyzed by X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and scanning transmission electron microscopy (STEM) coupled with energy dispersive X-ray spectroscopy (EDS), with the aid of a focused ion beam (FIB). Keywords: Electrochemical carburization, Supercritical CO2, Aqueous carburization, Carbidic carbon

The co-deposition of Ni and Al2O3 by electrodeposition in supercritical CO2 (sc-CO2) baths with and without emulsification was studied. The material characteristics of the Ni-Al2O3 composite coatings, including its crystal structure, surface morphology, chemical composition, micro-hardness, wear resistance, and corrosion resistance, were all examined and compared with those of pure deposited Ni. Although a reduction in electrodeposition rate and a lower solid Al2O3 particle content in the composite coatings were obtained incorporating sc-CO2 bath, substantial increases in the micro-hardness and wear resistance of the coatings were observed comparing with those formed in conventional bath. The advantages of sc-CO2 electrodeposition, with and without surfactant addition, over the conventional electrodeposition of composite coatings, are addressed.

This research proposes a novel opinion mining approach, which combines domain concepts and ranking systems from word of mouth documents to build an adaptive sentiment lexicon for sentiment classification. The main task of opinion mining is to detect subjective information in the text such as reviews, preferences, attitudes, etc., which extract the useful information for users to make a strategic decision. Some wide-scaled sentiment lexicons, such as SentiWordNet and SenticNet, are helpful to define sentiment scores for words, which are often used for mining opinions or sentiment analysis. However, the traditional sentiment lexicons are pre-defined and static so they cannot adapt to time and various domains. In this research, we build a contextual sentiment lexicon based on an integration of domain concepts and ranking systems. As related words are able to form some specific concepts from documents, we use a well-known common sense database, ConceptNet, for extraction of significant words from word of mouth documents. The traditional opinion mining model, which extracts sentiments from SentiWordNet 3.0, is treated as the benchmark in this research. We compare our proposed model, which extracts sentiments from the contextual sentiment lexicon and selects significant words from ConceptNet. According to the experiments, our model achieves higher classification accuracy than the traditional opinion model.

Numerical calculation based on first-principles is applied to study the structural characteristics and the band-energy properties of wurtzite AlxGa1-xN. The lattice constants obtained from the equilibrium energy are larger than those obtained from the Vegard’s law. The deviation parameter is 0.040±0.005 A for the a lattice constant and 0.125±0.009 A for the c lattice constant. The band gap energy is overestimated with the Vegard’s law. The bowing parameter of direct (indirect) band gap energy of 0.752±0.069 eV (0.889±0.057 eV) is obtained with the equilibrium lattice constants, and 0.352±0.046 eV (0.271±0.056 eV) is obtained with the lattice constants derived from the Vegard’s law.

The characteristics of the violet–blue InGaN quantum-well lasers with an emission wavelength of 400–480 nm when the band-offset ratio of the In x Ga 1− x N/In y Ga 1− y N heterojunction is 3/7, which was most frequently used before, and 7/3, which is accepted recently by most researchers, are studied numerically. Specifically, the characteristics of the electronic current overflow, stimulated recombination rate, and laser performance are discussed. Meanwhile, the relationship between the threshold current and the number of quantum wells in the InGaN quantum-well laser is investigated. Simulation results suggest that, when the band-offset ratio is 7/3, the lowest threshold current of the violet–blue InGaN quantum-well lasers is obtained when the number of InGaN well layers is two if the emission wavelength is shorter than 450 nm, and one if the emission wavelength is longer than 450 nm.

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior.

The fabrication and characterization of a radio frequency (RF) micromachined switch with annealing were presented. The structure of the RF switch consists of a membrane, coplanar waveguide (CPW) lines, and eight springs. The RF switch is manufactured using the complementary metal oxide semiconductor (CMOS) process. The switch requires a post-process to release the membrane and springs. The post-process uses a wet etching to remove the sacrificial silicon dioxide layer, and to obtain the suspended structures of the switch. In order to improve the residual stress of the switch, an annealing process is applied to the switch, and the membrane obtains an excellent flatness. The finite element method (FEM) software CoventorWare is utilized to simulate the stress and displacement of the RF switch. Experimental results show that the RF switch has an insertion loss of 0.9 dB at 35 GHz and an isolation of 21 dB at 39 GHz. The actuation voltage of the switch is 14 V.

Images/videos of outdoor scenes are usually degraded by the turbid medium in the atmosphere. In this paper, a novel single image-based dehazing framework is proposed to remove haze effects from image/video, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze imaging model, we propose to accurately estimate the atmospheric light via haze density analysis. We can then accurately estimate the transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free image can be recovered with lower computational complexity, which can be naturally extended to video dehazing.