High energy storage and ultrafast discharge in NaNbO3-based lead-free dielectric capacitors via a relaxor strategy

Dielectric capacitors with decent energy storage and fast charge-discharge performances are essential in advanced pulsed power systems. In this study, novel ceramics (1-x)NaNbO₃-xBi(Ni_2/3Nb_1/3)O₃(xBNN, x = 0.05, 0.1, 0.15 and 0.20) with high energy storage capability, large power density and ultrafast discharge speed were designed and prepared. The impedance analysis proves that the introducing an appropriate amount of Bi(Ni_0·5Nb_0.5)O₃ boosts the insulation ability, thus obtaining a high breakdown strength (E_b) of 440 kV/cm in xBNN ceramics. A high energy storage density (W_total) of 4.09 J/cm³, recoverable energy storage density (W_rec) of 3.31 J/cm³, and efficiency (η) of 80.9% were attained in the 0.15BNN ceramics. Furthermore, frequency and temperature stability (fluctuations of W_rec ≤ 0.4% over 5–100 Hz and W_rec ≤ 12.3% over 20–120 °C) were also observed. The 0.15BNN ceramics exhibited a large power density (19 MW/cm³) and ultrafast discharge time (~37 ns) over the range of ambient temperature to 120 °C. These enhanced performances may be attributed to the improved breakdown strength and relaxor behavior through the incorporation of BNN. In conclusion, these findings indicate that 0.15BNN ceramics may serve as promising materials for pulsed power systems.     

Ensemble relation network with multi-level measure

Fine-grained few-shot learning is a difficult task in image classification. The reason is that the discriminative features of fine-grained images are often located in local areas of the image, while most of the existing few-shotlearning image classification methods only use top-level features and adopt a single measure. In that way, the localfeatures of the sample cannot be learned well. In response to this problem, ensemble relation network with multi-level measure (ERN-MM) is proposed in this paper. It adds the relation modules in the shallow feature space tocompare the similarity between the samples in the local features, and finally integrates the similarity scores from thefeature spaces to assign the label of the query samples. So the proposed method ERN-MM can use local details andglobal information of different grains. Experimental results on different fine-grained datasets show that the proposedmethod achieves good classification performance and also proves its rationality.     

Epidemic Models of Malicious-Code Propagation and Control in Wireless Sensor Networks: An Indepth Review

Wireless Personal Communications - Besides anti-malware usage for the eradication of malicious attacks, researchers have developed epidemic models in order to gain more insights into the spread...     

Analysis of energy saving in user equipment in LTE-A using stochastic modelling

Telecommunication Systems - Energy saving in User Equipment (UE) is one of the important issues for limited sources of power in the device. It is critical for the UE to maximize its energy...     

On the Growth of Thin-Film AlGaN/GaN Epitaxial Heterostructures on Hybrid Substrates Containing Layers of Silicon Carbide and Porous Silicon

Semiconductors - Abstract—In our work, we carry out a structural-spectroscopic study of AlGaN/GaN epitaxial layers grown by molecular-beam epitaxy with nitrogen-plasma activation on a hybrid...     

New Design of Wavelets Based on the Convolution of Compactly Supported Functions with a Rectangular Pulse

Journal of Communications Technology and Electronics - A new design of wavelets based on the convolution of a compactly supported function with a rectangular pulse is proposed and theoretically...     

Influence of Continuous Wave Interference on the Efficiency of the Non-Threshold Search Procedure for a Noise-Like Signal by Delay Time with Transition to the Frequency Domain

Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is...     

Modern Photodetector IR-Modules

Journal of Communications Technology and Electronics - In recent years, there has been a rapid improvement in photonics products due to the use of multilayer heterostructures grown on the basis of...     

Measuring Creative Experience from Visitors’ Paths and Abstract Multi-sensory Artefacts

Mobile Networks and Applications - Project MindCatcher is an art/research project which has the intention to explore the potential of interactive artistic environments for measuring and a better...     

Effect of PyC interface phase on the cyclic ablation resistance and flexural properties of two-dimensional Cf/HfC composites

Composites based on hafnium carbide and reinforced with continuous naked carbon fiber with and without PyC interface were prepared at low temperature by precursor infiltration and pyrolysis and chemical vapor deposition method. The microstructure, mechanical property, cyclic ablation and fiber bundle push-in tests of the composites were investigated. The results show that after three times ablation cycles, the bending strength of samples without PyC interface decreased by 63.6 %; the bending strength of samples with PyC interface only decreased by 37.8 %. The force displacement curve of the samples with PyC interface presented a well pseudoplastic deformation state. The mechanical behavior difference of two kinds of composites was due to crucial function of PyC interface phase including protection of fiber and weakening of fiber/matrix interface.