Zinc ion batteries (ZIBs) have been gradually developed in recent years due to their abundant resources, low cost, and environmental friendliness. Therefore, ZIBs have received a great deal of attention from researchers, which are considered as the next generation of portable energy storage systems. However, poor overall performance of ZIBs restricts their development, which is attributed to zinc dendrites and a series of side reactions. Constructing 3D zinc anodes has proven to be an effective way to significantly improve their electrochemical performance. In this review, the challenges of zinc anodes in ZIBs, including zinc dendrites, hydrogen evolution and corrosion, as well as passivation, are comprehensively summarized and the energy storage mechanisms of the zinc anodes and 3D zinc anodes are discussed. 3D zinc anodes with different structures including fiberous, porous, ridge‐like structures, plated zinc anodes on different substrates and other 3D zinc anodes, are subsequently discussed in detail. Finally, emerging opportunities and perspectives on the material design of 3D zinc anodes are highlighted and challenges that need to be solved in future practical applications are discussed, hopefully illuminating the way forward for the development of ZIBs.
With the advent of the era of Internet of Everything, the amount of data generated by edge devices in the distribution network has increased rapidly, bringing higher data transmission bandwidth requirements. At the same time, new applications have placed higher demands on the real-time nature of data processing, and traditional computing models have been unable to cope effectively. This paper proposes distributed power distribution fault detection based on edge computing, which can realize timely sensing and real-time response to distribution network faults, speed up distribution fault processing speed, shorten power outage time, improve power supply reliability and user satisfaction. Secondly, the basic principle of wavelet transform application in signal singularity detection is introduced, and a power signal fault signal analysis method based on wavelet transform is proposed. It not only makes full use of the advantages of wavelet transform in fault signal analysis, but also overcomes the shortcomings of traditional Fourier transform method, and verifies it through examples. Finally, based on the critical requirements of edge computing, such as agile connection, business real-time, data optimization, application intelligence, security and privacy protection, an evaluation system based on edge computing CROSS index fault detection model is proposed.
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