Improvement of dielectric breakdown strength and energy storage performance in Er2O3–modified 0.95Sr0.7Ba0.3Nb2O6-0.05CaTiO3 lead-free ceramics

In this study, 0.95?Sr_0.7Ba_0.3Nb₂O₆-0.05CaTiO₃-x wt% Er₂O₃ ceramics (SBNCTEx; x?=?0–5) were synthesized using traditional solid-state method, and we investigated the microstructure, energy storage properties as well as the relationship between dielectric breakdown strength and interfacial polarization. As compared with pure 0.95?Sr_0.7Ba_0.3Nb₂O₆-0.05CaTiO₃ ceramics, the Er₂O₃ dopants suppressed the grain growth of SBNCTEx, and the doped ones showed the dense microstructure. The secondary phase was found for x?≥?1 according to the EDS results, and the influence of the secondary phase on relative dielectric breakdown strength has also been studied. The dielectric breakdown strength increased from 18.1?kV/mm to 34.4?kV/mm, which is good for energy storage. The energy storage density of 0.28?J/cm³ and the energy storage efficiency of 91.4% were obtained in the SBNCTE5 ceramics. The results indicate that SBNCTE ceramics can be used as energy storage capacitors.     

A new perspective of co-doping and Nd segregation effect on proton stability and transportation in Y and Nd co-doped BaCeO3

Bulk and surface properties of proton stability and transportation in Y and Nd co-doped BaCeO₃ (BCYN), especially the effect of Nd segregation, were investigated by first-principles calculations. Since the structure of doped BaCeO₃ at the operating temperature of proton-conducting has been unclear for a long time, we have summarized the latest experimental results and calculated the structure of the asymmetric BCYN for the first time. The results show that compared with Y, Nd doping promotes oxygen vacancy formation, however reduces proton stability. Our calculation can also provide a possible explanation for the formation of space charge layer at the grain boundary of doped BaCeO₃ in experiment. Unlike the stable Y in BCYN, Nd is calculated to be easily segregated, which can facilitate both proton hydration and proton transportation near the surface. Moreover, Nd segregation at the grain boundary is predicted to be beneficial for proton transportation between grains.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Performance investigation on a novel 3D wave flow channel design for PEMFC

Flow field structure can largely determine the output performance of Polymer electrolyte membrane fuel cell. Excellent channel configuration accelerates electrochemical reactions in the catalytic layer, effectively avoiding flooding on the cathode side. In present study, a three-dimensional, multi-phase model of PEMFC with a 3D wave flow channel is established. CFD method is applied to optimize the geometry constructions of three-dimensional wave flow channels. The results reveal that 3D wave flow channel is overall better than straight channel in promoting reactant gases transport, removing liquid water accumulated in microporous layer and avoiding thermal stress concentration in the membrane. Moreover, results show the optimal flow channel minimum depth and wave length of the 3D wave flow channel are 0.45 mm and 2 mm, respectively. Due to the periodic geometric characteristics of the wave channel, the convective mass transfer is introduced, improving gas flow rate in through-plane direction. Furthermore, when the cell output voltage is 0.4 V, the current density in the novel channel is 23.8% higher than that of conventional channel.     

Use of heat-moisture treated maize starch to modify the properties of wheat flour and the quality of noodles

Waxy, normal and high-amylose maize starches were subjected to heat-moisture treatment (HMT) and then added to wheat flour (WF) in different ratios (1%, 5% and 10%). The properties of blends and their cooked noodles were studied to investigate the effects of HMT starches. The incorporation of HMT starch in WF led to an increase in swelling power, peak viscosity and breakdown and to a decrease in setback, thus inhibiting retrogradation, hence enhancing resultant noodle softness. Compared to the same addition ratio of native starch to WF, HMT starch led to higher tensile strength and extensibility in resultant noodles. WF with added HMT starch had higher resistant starch than with native starch. This study showed that addition of HMT maize starch has potential to bring nutritional benefits. However, it is necessary to select the proper blending ratio and amylose content of starch to add, in consideration of its effect on noodle quality.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Low-temperature synthesis of SiC nanowires with Ni catalyst

SiC nano wires were fabricated on the silicon substrate dipped with a layer of Ni catalyst at 900 ℃ by gas pressure annealing processing. The morphologies and crystal structures were determined by scanning electron microscopy(SEM), transmission electron microscopy(TEM)and X-ray diffraction(XRD). The results show that the assynthesized nanowires are β-SiC single crystalline with diameter range of 50-100 nm, and length of tens of micron by directly annealing at 900 ℃. The SiC nano wires grow along the [111] direction with highly uniform morphology. And the possible growth mechanism of SiC nano wires is proposed.The present work provides an efficient strategy for the production of high-quality SiC nano wires.