ZnO Nanorods Grown Directly on Copper Foil Substrate as a Binder-Free Anode for High Performance Lithium-Ion Batteries

ZnO nanorods directly grown on copper foil substrate were obtained via hydrothermal method without using templates. Structure and morphology of the as-prepared ZnO nanorods were characterized by X-ray diffraction, scanning electron microscopy and high-resolution transmission electron microscopy. The ZnO nanorods on copper foil (ZnO@CF) exhibited remarkably enhanced performance as anode for lithium batteries with the initial discharge capacity of 1236 mAh g-1 and a capacity of 402 mAh g-1 retained over 100 cycles at a current density of 200 mA g-1. The ZnO@CF anode demonstrated an excellent rate capability, delivering a reversible capacity of 390 mAh g-1 at 1500 mA g-1. This superior performance of the ZnO@CF anode is believed to be due to the unique structure of this binder-free anode, favoring mass and charge transfer at its interface with the electrolyte, effectively reducing the Li-ions diffusion paths and providing conditions to accommodate the anode volume variations upon charge-discharge cycling

A New Cooperative Anomaly Detection Method for Stacker Running Track of Automated Storage and Retrieval System in Industrial Environment

Considering the complexity and the criticality of the stacker equipment, in order to solve the problem that the stop accuracy of the stacker reduces or even fails to work due to abrasion of the running rail, this paper proposes a cooperative detection method based on Pulse Coupling Neural Network (PCNN) and wavelet transform theory to detect the abnormal points of the stacker running rail in industrial environment by analyzing the variation signals. First of all, considering the fact that the data is mixed up with noises because of the environment at the site and the possibility of the data acquisition equipment breaking down, a noise reduction method for the vibration signal data of stacker is constructed based on PCNN. Then, the basic theory of wavelet transform is introduced and then the rules of judging anomaly points on stackers’ running tracks are discussed based on wavelet transform. In addition, a cooperative detection method based on PCNN and wavelet transform theory is carried out based on the space-time distribution feature of the vibration of the stacker orbits in the industrial environment. Then the rationality of the proposed algorithm is verified by simulation through data provided by State Grid Measuring Center of China. This paper constructs a model of the abnormal point detection of the stackers in an industrial environment. The experimental simulation and example simulation show that the cooperative detection method based on PCNN and wavelet transform theory can effectively detect and locate the anomaly points of the stacker running tracks. The expansibility in engineering applications is promising. Lastly, some conclusions are discussed

Research on the optimization and improvement of business environment based on the customer satisfaction model of ‘Access to Electricity’

In order to further promote the reform of “deregulation and service” and continuously optimize the business environment, the power industry as the important part of national economic development, optimizing the business environment is urgent. Based on the customer satisfaction survey of ‘Access to electricity’, this paper constructs a set of targeted, complete and practical multiple regression model of electricity consumption satisfaction, and puts forward relevant strategies to help optimize and improve the business environment of the power industry

A Cooperative Denoising Algorithm with Interactive Dynamic Adjustment Function for Security of Stacker in Industrial Internet of Things

In order to more effectively eliminate the disturbance of vibration signal to ensure the security monitoring of stacker be more accurate in Industrial Internet of Things (IIoT), a cooperative denoising algorithm with interactive dynamic adjustment function was constructed and proposed. First, some basic theories such as EMD, EEMD, LMS, and VSLMS were introduced in detail according the characteristics of stacker in IIoT. Meanwhile, the advantages and disadvantages of varieties of algorithms have been analyzed. Secondly, based on the traditional VSLMS-EEMD, an improved VSLMS-EEMD was proposed. Thirdly, to guarantee the denoising effect of security monitoring in IIoT, a cooperative denosing model and framework named as IDVSLMS-EEMD was designed and constructed based on the advantages of LMS, VSLMS, and improved VSLMS-EEMD. In addition, the assignment rules and models of the corresponding weight coefficients were also set up according to the features of the error signal of denoising process in IIoT. At the same time, we have designed a cooperative denoising algorithm with interactive dynamic adjustment function. And some evaluated indexes such as NSR and SDR were selected and introduced to evaluate the effectiveness of the different algorithms. Thirdly, some simulation examples and real experiment examples of stacker running signals under abnormal condition, which has been developed and applied in Power Grid of China, was used to verify and simulate the effectiveness of our presented algorithm. The experiment comparison results have shown that our algorithm can improve the denosing effect. Finally, some conclusions were discussed and the directions for future engineering application were also pointed out

The incipient fault feature enhancement method of the gear box based on the wavelet packet and the minimum entropy deconvolution

The amplitude of the vibration signal in the gearbox of the motor driving system is low, resulting in disturbance and vibration noise effect, especially in the early stage of failure. So, it is difficult to extract the characterization of gearbox fault correctly. A method of incipient fault feature enhancement based on the wavelet packet and the minimum entropy deconvolution (MED) is proposed. Firstly, the vibration signal of the gear box containing the incipient fault is decomposed by the wavelet packet, and the decomposed band is reconstructed to eliminate the noise component which is the initial enhancement of the fault feature. After that theMED is used to filter the reconstructed band blind deconvolution to eliminate the influence of the transmission path, so that the feature components of the fault are enhanced again. The combination of WP and MED weakens the influence of the normal components in the original signal, highlights the impact component of the fault, and fully excavates the hidden fault information in the frequency band after the wavelet packet decomposition. Finally, the experimental results are compared and analysed. The experimental results show that the incipient fault feature extracted by this method improves the accuracy of fault diagnosis

ZnO Nanorods Grown Directly on Copper Foil Substrate as a Binder-Free Anode for High Performance Lithium-Ion Batteries

ZnO nanorods directly grown on copper foil substrate were obtained via hydrothermal method without using templates. Structure and morphology of the as-prepared ZnO nanorods were characterized by X-ray diffraction, scanning electron microscopy and high-resolution transmission electron microscopy. The ZnO nanorods on copper foil (ZnO@CF) exhibited remarkably enhanced performance as anode for lithium batteries with the initial discharge capacity of 1236 mAh g-1 and a capacity of 402 mAh g-1 retained over 100 cycles at a current density of 200 mA g-1. The ZnO@CF anode demonstrated an excellent rate capability, delivering a reversible capacity of 390 mAh g-1 at 1500 mA g-1. This superior performance of the ZnO@CF anode is believed to be due to the unique structure of this binder-free anode, favoring mass and charge transfer at its interface with the electrolyte, effectively reducing the Li-ions diffusion paths and providing conditions to accommodate the anode volume variations upon charge-discharge cycling

ZnS nanotubes/carbon cloth as a reversible and high-capacity anode material for lithium-ion batteries

Metal sulfides have been considered as one of the most promising class of anode materials for lithium-ion batteries. However, large volume change and low intrinsic electrical conductivity significantly restrict the performance. Herein, flexible electrode materials comprising ZnS nanotubes/carbon cloth are prepared by combined solvothermal and ion-exchange sulfidation technique. The ZnS nanotube array/carbon cloth electrode is assessed for application in lithium-ion batteries and remarkable improvement towards reversible capacity was observed. A notable capacity of 1053 mAh g(-1) at 0.2 C and a maintained reversible capacity of 608 mAh g(-1) after 100 cycles are observed, which are both comparable to similar materials in previously published reports. The ZnS nanotubes with small dimension and uniform dispersion grown directly on carbon cloth can effectively shorten the path of the lithium-ions, facilitating the charge transfer of the electrode. The carbon cloth and the three-dimensional (3D) structured carbon fiber exhibit a large surface area and can thus efficiently reduce the volume change during the discharge/charge cycles

Synthesis and Investigation of CuGeO3 Nanowires as Anode Materials for Advanced Sodium-Ion Batteries

Abstract Germanium is considered as a potential anode material for sodium-ion batteries due to its fascinating theoretical specific capacity. However, its poor cyclability resulted from the sluggish kinetics and large volume change during repeated charge/discharge poses major threats for its further development. One solution is using its ternary compound as an alternative to improve the cycling stability. Here, high-purity CuGeO3 nanowires were prepared via a facile hydrothermal method, and their sodium storage performances were firstly explored. The as-obtained CuGeO3 delivered an initial charge capacity of 306.7 mAh g−1 along with favorable cycling performance, displaying great promise as a potential anode material for sodium ion batteries

Biomass-Derived Oxygen and Nitrogen Co-Doped Porous Carbon with Hierarchical Architecture as Sulfur Hosts for High-Performance Lithium/Sulfur Batteries

In this work, a facile strategy to synthesize oxygen and nitrogen co-doped porous carbon (ONPC) is reported by one-step pyrolysis of waste coffee grounds. As-prepared ONPC possesses highly rich micro/mesopores as well as abundant oxygen and nitrogen co-doping, which is applied to sulfur hosts as lithium/sulfur batteries’ appropriate cathodes. In battery testing, the sulfur/oxygen and nitrogen co-doped porous carbon (S/ONPC) composite materials reveal a high initial capacity of 1150 mAh·g−1 as well as a reversible capacity of 613 mAh·g−1 after the 100th cycle at 0.2 C. Furthermore, when current density increases to 1 C, a discharge capacity of 331 mAh·g−1 is still attainable. Due to the hierarchical porous framework and oxygen/nitrogen co-doping, the S/ONPC composite exhibits a high utilization of sulfur and good electrochemical performance via the immobilization of the polysulfides through strong chemical binding