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In situ anchoring in carbon matrix of Bi2O2CO3 as a high-performance anode material for Li-ion batteries

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Rare Metals 2024年第08期43卷 3634-3646页

作者： Pu-Qiang He Jun Guo Hui Huang Zhong-Cheng Guo Faculty of Metallurgy and Energy Engineering Kunming University of Science and Technology Research Center of Metallurgical Electrode Materials Engineering technology Kunming Hendera Science and technology Co. Ltd.

Bismuth-based anode materials have been regarded as promising Li-ion batteries due to their high theoretical ***,their low conductivity and associated volume expansion inhabited their *** this work,Bi2O2CO3@C composites were successfully synthesized by in situ anchoring of flower-like Bi2O2CO3nanosheets on a carbon-based substrate via *** unique composited structure of Bi2O2-CO3@C leads to a stable specific capacity of 547 mAh·g-1after 100 cycles at a current density of 0.1 A·***,it demonstrates excellent rate capability with a specific capacity of 210 mAh·g-1at 5 A·*** 550 cycles at a current density of 0.5 A·g-1,a high reversible capacity of nearly 400 mAh·g-1was ***,in situ X-ray diffraction measurements clearly demonstrate the conversion between Bi and Li3Bi during alloying/dealloying,confirming the good electrochemical reversibility of the materials for Li *** reaction kinetics of Bi2O2CO3@C were further investigated using galvanostatic intermittent titration ***,Bi2O2-CO3@C exhibited excellent long-term stability,maintaining its high reversible capacity for over 200 cycles at a current density of 0.5 A·g-1in a full cell configuration using Li1.20Mn0.54Ni0.13Co0.13O2as the cathode *** result further underscores its promising potential for lithium-ion *** work may provide inspiration for the design of alloy-type negative electrode materials for high-performance rechargeable batteries.

关键词： Bi 2 O 2 CO 3 Composite materials Anode materials Full batteries

An optimization-oriented modeling approach using input convex neural networks and its application on optimal chiller loading

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Building Simulation 2024年第4期17卷 639-655页

作者： Shanshuo Xing Jili Zhang Song Mu Dalian University of technology Dalian116024China Guangdong Airport Baiyun Information technology Co. Ltd.Guangzhou510000China

Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller *** optima obtained by model-based optimization algorithms are dependent on precise and solvable objective *** classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based *** this paper,we leverage the input convex neural networks(ICNN)to identify the chiller model to construct a convex mapping between control variables and the objective function,which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model comparison based on an experimental data set,and the statistical results show that,on the premise of retaining prior convexities,the proposed model depicts excellent approximation power for the data set,especially the unseen ***,the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization *** with conventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.

关键词： chiller plant input convex neural network optimal load distribution convex optimization

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

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Defence technology（防务技术） 2024年第7期37卷 162-172页

作者： Pengyu Hu Jiangpeng Wu Zhengang Yan Meng He Chao Liang Hao Bai Xi'an Modern Control technology Research Institute Xi'an710065China Xi'an OET Science and technology Co. LtdXi'an710076China

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high ***,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment *** address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo ***,background difference algorithm is utilized to extract the center and area of each fragment in the image ***,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment *** reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial ***,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10~3fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

关键词： Warhead fragment measurement High speed photography Stereo vision Multi-object tracking Spatio-temporal reconstruction

An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 577-591页

作者： Qing Zhu Linlin Gu Huijie Lin Electricity technology Branch Nari Technology Co.Ltd.Nanjing211106China NARI-TECH Nanjing Control Systems Co. Ltd.Nanjing211106China

With the rapid development of electric power systems,load estimation plays an important role in system operation and ***,load estimation techniques contain traditional,time series,regression analysis-based,and machine learning-based *** the machine learning-based method can lead to better performance,in this paper,a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is ***,an image fingerprint construction is proposed for training *** the data preprocessing,the training data matrix is constructed by the cyclic shift and cubic spline ***,the linear mapping and the gray-color transformation method are proposed to form the color image ***,a convolutional neural network(CNN)combined with an attentionmechanism is proposed for training performance *** last,an experiment is carried out to evaluate the estimation *** with the support vector machine method,CNN method and long short-term memory method,the proposed algorithm has the best load estimation performance.

关键词： Load estimation deep learning attention mechanism image fingerprint construction

A Blockchain-Based Proxy Re-Encryption Scheme with Conditional Privacy Protection and Auditability

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China Communications 2024年第7期21卷 267-277页

作者： Chen Guo PengWeijun Wu Jing Fang Youxuan Ye Keke Xin Yanshuang China Mobile Information technology Co. LtdBeijing 100037China China Mobile Information technology Co. LtdShenzhen 518048China

With the development of Internet of Things technology,intelligent door lock devices are widely used in the field of house *** the traditional housing leasing scenario,problems of door lock information disclosure,tenant privacy disclosure and rental contract disputes frequently occur,and the security,fairness and auditability of the housing leasing transaction cannot be *** solve the above problems,a blockchain-based proxy re-encryption scheme with conditional privacy protection and auditability is *** scheme implements fine-grained access control of door lock data based on attribute encryption technology with policy hiding,and uses proxy re-encryption technology to achieve auditable supervision of door lock information *** encryption technology and zero-knowledge proof technology are introduced to ensure the confidentiality of housing rent information and the fairness of rent *** construct a decentralized housing lease transaction architecture,the scheme realizes the efficient collaboration between the door lock data ciphertext stored under the chain and the key information ciphertext on the chain based on the blockchain and InterPlanetary File ***,the security proof and computing performance analysis of the proposed scheme are carried *** results show that the scheme can resist the chosen plaintext attack and has low computational cost.

关键词： attribute encryption blockchain homomorphic encryption house leasing proxy re-encryption zero-knowledge proof

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Method for rapid warning and activity concentration estimates in online waterγ-spectrometry systems

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Nuclear Science and Techniques 2024年第3期35卷 1-12页

作者： Meng Wang Yi Gu Mao-Lin Xiong Liang-Quan Ge Qing-Xian Zhang Guo-Qiang Zeng Heng Lu Sheng-Liang Guo College of Nuclear technology and Automation Engineering Chengdu University of TechnologyChengdu 610059China Applied Nuclear technology in Geosciences Key Laboratory of Sichuan Province (Chengdu University of Technology)Chengdu 610059China Chengdu New Ray technology Co.ltd Chengdu 610052China

Onlineγ-spectrometry systems for inland waters,most of which extract samples in situ and in real time,are able to produce reliable activity concentration measurements for waterborne radionuclides only when they are distributed relatively uniformly and enter into a steady-state diffusion regime in the measurement *** protect residents’health and ensure the safety of the living environment,better timeliness is required for this measurement *** address this issue,this study established a mathematical model of the online waterγ-spectrometry system so that rapid warning and activity estimates can be obtained for water under non-steady-state(NSS)*** addition,the detection efficiency of the detector for radionuclides during the NSS diffusion process was determined by applying the computational fluid dynamics technique in conjunction with Monte Carlo *** this basis,a method was developed that allowed the online waterγ-spectrometry system to provide rapid warning and activity concentration estimates for radionuclides in *** analysis of the NSS-mode measurements of^(40)K radioactive solutions with different activity concentrations determined the optimum warning threshold and measurement time for producing accurate activity concentration estimates for *** experimental results show that the proposed NSS measurement method is able to give warning and yield accurate activity concentration estimates for radionuclides 55.42 and 69.42 min after the entry of a 10 Bq/L^(40)K radioactive solution into the measurement chamber,*** times are much shorter than the 90 min required by the conventional measurement ***,the NSS measurement method allows the measurement system to give rapid(within approximately 15 min)warning when the activity concentrations of some radionuclides reach their respective limits stipulated in the Guidelines for Drinking-water Quality of the WHO,suggesting that this method con

关键词： Water radioactivity monitoring Dynamic detection efficiency Rapid warning Activity estimation

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Scenarios analysis and performance assessment of blockchain integrated in 6G scenarios

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Science China(Information Sciences) 2024年第7期67卷 5-26页

作者： Bo LI Guanjie CHENG Honghao GAO Xueqiang YAN Shuiguang DENG College of Computer Science and technology Zhejiang University College of Computer Science and technology Shanghai University 2012 Lab Huawei Technologies Co. Ltd.

Emerging applications such as smart city infrastructures and virtual reality landscapes are setting rigorous benchmarks for 6G mobile networks, requiring elevated levels of confidentiality, integrity, nonrepudiation, authentication, and stringent access controls. Blockchain technology is heralded as a transformative enabler for meeting 6G standards, owing to its intrinsic attributes. However, a gap exists in the holistic investigation of blockchain's applicability in 6G realms, particularly addressing the “whether”, “when”, and“how” of its deployment. Present research trails in developing robust methodologies to gauge blockchain's efficacy within 6G use cases. Addressing this, our study introduces a novel confluence of blockchain with 6G networks, where data resides in distributed Hash tables(DHTs) while their hashes are secured in distributed ledger technology(DLT), harnessing blockchain's core strengths-immutability, traceability, and fortified security. We delineate seven specific 6G use cases poised for enhancement through blockchain integration,and scrutinize the rationale, nature, and timing of this convergence. Furthermore, we devise a comprehensive methodology for assessing blockchain's performance metrics and scalability in 6G environments. Our extensive experimental analyses evaluate the synergistic performance of this integration, revealing that the Quorum blockchain satisfactorily supports 80% of 6G scenarios. The findings suggest that, with appropriate configurations, consortium blockchains are well-equipped to fulfill the demanding performance and scalability requisites of 6G networks.

关键词： blockchain distributed ledger technology (DLT) 6G performance assessment 6G scenarios analysis transaction arrival rate

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3D printed silicon-based micro-lattices with ultrahigh areal/gravimetric capacities and robust structural stability for lithium-ion batteries

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Nano Research 2024年第4期17卷 2693-2703页

作者： Jie Fu Dong Wang Yan Li Xianzheng Liu Rui Zhang Zhiyuan Liu Pengdong Liu Lijuan Zhang Xuefei Li Guangwu Wen School of Materials Science and Engineering Shandong University of TechnologyZibo 255000China Shandong Si-Nano Materials technology Co. Ltd.Zibo 255000China

Nanostructured silicon anodes have shown extraordinary lithium storage properties for lithium-ion batteries(LIBs)but are usually achieved at low areal loadings(<1.5 mg·cm^(-2))with low areal *** sound electrochemical performance at high loading requires proportionally higher ion/electron currents and robust structural stability in the thicker ***,we report a three-dimensional(3D)printed silicon-graphene-carbon nanotube(3D-Si/G/C)electrode for simultaneously achieving ultrahigh areal/gravimetric capacities at high mass *** periodically arranged vertical channels and hierarchically porous filaments facilitate sufficient electrolyte infiltration and rapid ion diffusion,and the carbonaceous network provides excellent electron transport properties and mechanical integrity,thus endowing the printed 3D-Si/G/C electrode with fast electrochemical reaction kinetics and reversibility at high mass ***,the 3D-Si/G/C with high areal mass loading of 12.9 mg·cm^(-2) exhibits excellent areal capacity of 12.8 mAh·cm^(-2) and specific capacity of 1007 mAh·g^(-1),***-situ optical microscope and ex-situ scanning electron microscope(SEM)confirm that the hierarchically porous filaments with interconnected carbon skeletons effectively suppress the volume change of silicon and maintain stable micro-lattice architecture.A 3D printed 3D-Si/G/C-1||3D-LiFePO_(4)/G full cell holds excellent cyclic stability(capacity retention rate of 78%after 50 cycles)with an initial Coulombic efficiency(ICE)of 96%.This work validates the feasibility of 3D printing on constructing high mass loading silicon anode for practical high energy-density LIBs.

关键词： silicon anode areal capacity three-dimensional(3D)printing lithium-ion batteries

Small object detection on highways via balance feature fusion and task-specific encoding network

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Optoelectronics Letters 2024年第7期20卷 424-429页

作者： YU Minming CHAN Sixian ZHOU Xiaolong LAI Zhounian College of Computer Science and technology Zhejiang University of Technology Hangzhou Xsuan technology Co. Ltd. Quzhou University Huzhou Institute of Zhejiang University

Detecting small objects on highways is a novel research topic. Due to the small pixel of objects on highways, traditional detectors have difficulty in capturing discriminative features. Additionally, the imbalance of feature fusion methods and the inconsistency between classification and regression tasks lead to poor detection performance on highways. In this paper, we propose a balance feature fusion and task-specific encoding network to address these issues. Specifically, we design a balance feature pyramid network(FPN) to integrate the importance of each layer of feature maps and construct long-range dependencies among them, thereby making the features more discriminative. In addition, we present task-specific decoupled head, which utilizes task-specific encoding to moderate the imbalance between the classification and regression tasks. As demonstrated by extensive experiments and visualizations, our method obtains outstanding detection performance on small object detection on highways(HSOD) dataset and AI-TOD dataset.

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