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Ammonia pyrolysis oxidation excited by nanosecond pulsed discharge:Global/fluid models hybrid solution

Journal of Energy Chemistry 2025年第1期100卷 385-396页

作者： Mingming Zhang Hanyu Wu Qi Chen Jiaxin Yang Bonan Liu school of Mechanical Electronic and Control Engineering Beijing Jiaotong University China University of Petroleum

The kinetic characteristics of plasma-assisted oxidative pyrolysis of ammonia are studied by using the global/fluid models hybrid solution ***,the stable products of plasma-assisted oxidative pyrolysis of ammonia are *** results show that the consumption of NH3/O2and the production of N2/H2change linearly with the increase of voltage,which indicates the decoupling of nonequilibrium molecular excitation and oxidative pyrolysis of ammonia at low ***,the detailed reaction kinetics mechanism of ammonia oxidative pyrolysis stimulated by a nanosecond pulse voltage at low pressure and room temperature is *** on the reaction path analysis,the simplified mechanism is *** detailed and simplified mechanism simulation results are compared with experimental data to verify the accuracy of the simplified ***,based on the simplified mechanism,the fluid model of ammonia oxidative pyrolysis stimulated by the nanosecond pulse plasma is established to study the pre-sheath/sheath behavior and the resultant consumption and formation of key *** results show that the generation,development,and propagation of the pre-sheath have a great influence on the formation and consumption of *** consumption of NH3by the cathode pre-sheath is greater than that by the anode pre-sheath,but the opposite is true for OH and O（1S）.However,within the sheath,almost all reactions do not ***,by changing the parameters of nanosecond pulse power supply voltage,it is found that the electron number density,electron current density,and applied peak voltages are not the direct reasons for the structural changes of the sheath and ***,the discharge interval has little effect on the sheath structure and gas mixture *** research results of this paper not only help to understand the kinetic promotion of non-equilibrium excitation in the process of oxidative pyrolysis but also help to explore th

关键词： Nanosecond pulsed discharge Ammonia Oxidative pyrolysis Fluid model Global model

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Recent development in electrode design for wide-temperature supercapacitors

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Science China Chemistry 2025年第1期68卷 96-117页

作者： Jianhong Liu Qiang Zhou Yuxiao Lin Xinsheng Zhao Guangmin Zhou Xiaoxiao Li school of Physics and electronic engineering Jiangsu Normal University Tsinghua-Berkeley Shenzhen Institute & Tsinghua Shenzhen International Graduate school Tsinghua University

An ever-increasing market demand has stimulated the soaring enthusiasm of researchers to develop wide-temperature supercapacitors(SCs). The active electrode is one of the most important parts of SC, which is directly related to the energy density,power transmission and long-term cyclability of the device in the wide-temperature environment. Compared with the SC electrodes aimed for room-temperature application, the SC electrodes for operating at wide-temperature scene often face greater challenges. In this review, the main challenges of SC electrodes under various temperature conditions, including low, high and cross-fade temperatures, are summarized. The relevant performance decay and failure mechanisms of wide-temperature SC electrodes are analyzed. In addition, this review deals with the recent studies and developments in robust wide-temperature SC electrodes with respect to the rational design of electrode structures and the exploitation of advanced active materials. Finally, the future directions for exploring reliable wide-temperature SCs are also proposed.

关键词： supercapacitor wide-temperature electrode design active materials

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Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

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Energy engineering 2025年第1期122卷 203-220页

作者： Yu Zhang Daoyu Zhang TiezhouWu school of Electrical and electronic engineering Hubei University of TechnologyWuhan430068China

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery ***,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity ***,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model *** address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural ***,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity ***,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network *** validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging *** experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

关键词： Lithium-ion battery state of health differential thermal voltammetry Sparrow Search Algorithm

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Situation-adaptive neural network for fast pre-computing image enhancement

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Science China(Information Sciences) 2025年

作者： Xinyue LI Huiyu DUAN Jia WANG Xiaohong LIU Yitong CHEN Guangtao ZHAI Institute of Image communication and Network engineering Department of Electronic EngineeringShanghai Jiao Tong University

As intelligent vision tasks become more widespread, enhancing image quality before further computational analysis is crucial. Recently, deep learning has shown potential for automated pre-computing enhancement, but it typically requires substantial computational resources and is hard to adapt to in multiple situations without *** practice, image enhancement often demands flexible adjustments based on different situations and subsequent computation devices, such as optical computing. Therefore,we propose SAEnhancer, a situation-adaptive neural network for fast pre-computing image enhancement. It learns from a small sample set to achieve personalized and adaptive enhancements for various situations without re-training,using semantic-aware embedding for precise color adjustments, surpassing traditional 3D lookup tables (LUTs), and enhancing computational effectiveness in intelligent vision applications.

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Distributed fiber optic sensing system for vibration monitoring of 3D printed bridges

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Optoelectronics Letters 2025年第1期21卷 28-34页

作者： ZHAO Shuai ZHOU Ran LUO Mingming LIU Jianfei LIU Xiongfei ZHOU Tao school of electronic Information engineering Hebei University of Technology Tianjin Key Laboratory of electronic Materials and Devices school of Civil engineering and Transportation Hebei University of Technology Tianjin Jinhang Institute of Technical Physics

The fiber optic sensing technology provides data support in structural health monitoring of the macro facilities, including design, construction, and maintenance of bridges, tunnels, ports and other infrastructures. In this paper, a distributed vibration sensing system is proved to be responsive to a single touch over a 1.8-m-long equivalent fiber segment, covering a vibration frequency from 5 Hz to 25 kHz. The sensing fiber was arranged as an S type layout on the bridge to recognize the standing state, windblown disturbance, and walking vibration. Moreover, the knocking and climbing events are recognized fiber laying spinning lines and hanging on the fences, respectively. The demonstration shows an accurate positioning and sensitive vibration monitoring applied on the automated three-dimensional(3D) printed bridge, which is applicable to all kinds of 3D printed facilities as intelligent sensory neuro-networks.

关键词： Spinning (fibers)

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Conversion-type cathode materials for high energy density solid-state lithium batteries

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Journal of Energy Chemistry 2025年第1期100卷 409-425页

作者： Yuhao Ma Shihong Qing Hongyu Liu Chuntao Ma Yuan Yu Chuang Yu Liping Wang school of Materials and Energy University of Electronic Science and Technology of China Zhejiang Provincial Key Laboratory of Fiber Materials and Manufacturing Technology Zhejiang Sci-Tech University State Key Laboratory of Advanced Electromagnetic engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology

Solid-state lithium batteries （SSLBs） are regarded as an essential growth path in energy storage systems due to their excellent safety and high energy *** particular,SSLBs using conversion-type cathode materials have received widespread attention because of their high theoretical energy densities,low cost,and *** the great progress in research and development of SSLBs based on conversiontype cathodes,their practical applications still face challenges such as blocked ionic-electronic migration pathways,huge volume change,interfacial incompatibility,and expensive processing *** review focuses on the advantages and critical issues of coupling conversion-type cathodes with solid-state electrolytes （SSEs）,as well as state-of-the-art progress in various promising cathodes （e.g.,FeS2,CuS,FeF3,FeF2,and S） in ***,representative research on conversion-type solid-state full cells is discussed to offer enlightenment for their practical ***,the energy density exhibited by the S cathode stands out impressively,while sulfide SSEs and halide SSEs have demonstrated immense potential for coupling with conversion-type ***,perspectives on conversion-type cathodes are provided at the material,interface,composite electrode,and battery levels,with a view to accelerating the development of conversion-type cathodes for high-energy–density SSLBs.

关键词： Sulfur compounds

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Future development research of 5G positioning in 3GPP standards

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The Journal of China Universities of Posts and Telecommunications 2025年

作者： Liu Wen Ren Hailong Deng Zhongliang school of electronic engineering， Beijing University of Posts and Telecommunications

Since the release of the first version of the 5th Generation Mobile Networks (5G) standard， Release-15 (Rel-15)， in June 2018， the 3rd Generation Partnership Project (3GPP) made significant efforts in the field of indoor and outdoor wireless positioning. Notably， Release-16 augmented support for enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (uRLLC)， particularly within complex indoor settings. To further meet the diverse application needs of positioning scenarios， the 3GPP standards for Release-17 and Release-18 propose new enhancement measures to continuously provide more accurate positioning services. In this paper， the scholarly discourse on 5G positioning was critically examined， providing a systematic review of the 5G positioning standards as delineated in 3GPP's Release-16 and Release-17， and was extended the discussion to the anticipated enhancements in 5G Release-18， along with their underlying motivations. Through these discussions， this article not only a comprehensive perspective on the current development of 5G positioning technology was provided but also was offered forward-looking analysis and predictions for the evolution of positioning technology in the upcoming 3GPP Release-19 phase. Additionally， it serves as a reference for researchers interested in understanding the development of positioning within the standard framework in the field of 5G indoor positioning， which holds significant meaning for promoting research and application of 5G positioning technology.

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Crosstalk-free multichannel sensor based on a dual-Sagnac interferometer interrogated by microwave photonic filter

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Optoelectronics Letters 2025年

作者： ZHANG Ailing WANG Bo ZHANG Yongfu CHANG Pengxiang WANG Minghe LIN Rui engineering Research Center of Optoelectronic Devices & communication Technology， Ministry of Education， Tianjin Key Laboratory of Film electronic and communication Devices， school of Electrical and electronic engineering， Tianjin University of Technology

A crosstalk-free multichannel sensor based on a dual-Sagnac interferometer interrogated by microwave photonic filter (MPF) is demonstrated theoretically and experimentally in this paper. The dual-Sagnac interferometer is taken as the sensing element as well as an optical spectrum slicer to implement a dual-passband MPF. Experimental results show that the proposed multichannel sensor is crosstalk-free， and the temperature sensitivity of each channel is -0.9884 MHz/℃ and -1.9302 MHz/℃， respectively. The sensing interrogation system has good linearity and stability and it is suitable for application scenarios where multiple points of temperature are required to monitor simultaneously.

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Sensitivity improvement by Vernier effect in microwave photonic filter based on F-P fiber ring

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Optoelectronics Letters 2025年

作者： LIN Rui ZHANG Ailing CHANG Pengxiang PAN Honggang WANG Minghe WANG Bo engineering Research Center of Optoelectronic Devices & communication Technology， Ministry of Education， Tianjin Key Laboratory of Film electronic and communication Devices， school of Electrical and electronic engineering， Tianjin University of Technology

A high sensitivity fiber optic temperature sensor based on Vernier effect in microwave photonic filter based on two paralleled F-P (Fabry-Perot) fiber ring is proposed and experimentally verified. Sensitivity is improved through the Vernier effect， which is caused by two parallel F-P fiber rings with approximate lengths. Temperature interrogation is achieved by monitoring the notch frequency of the superimposed frequency response curve. The temperature sensitivity of -484.514kHz/℃ is achieved in experiment， which is 57 times of the sensor without Vernier effect. The improved sensitivity and simple structure make it have wide potential applications in temperature monitoring of power systems.

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A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen school of electronic and Information engineering University of Science and Technology LiaoningAnshan114051China school of Computer Science and Software engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction

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