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Fiber swelling to improve cycle performance of paper-based separator for lithium-ion batteries application

Journal of Energy Chemistry 2023年第4期79卷 92-100页

作者： Zhenghao Li Wei Wang Xinmiao Liang Jianlin Wang Yonglin Xu Wei Li College of Light Industry and Food Engineering Guangxi UniversityNanning 530004GuangxiChina Guangxi Key Laboratory of Clean Pulp&Papermaking and Pollution Control Nanning 530004GuangxiChina State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in WuhanWuhan Institute of Physics and MathematicsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430071HubeiChina

It is well established that paper-based separators display short-circuit risk in lithium-ion batteries due to their intrinsic micron-sized *** this research,we have adjusted pore structure of paper by fiber swelling in liquid ***,the paper-based separator is prepared by propionylated sisal fibers through a wet papermaking *** electron microscope(SEM)and multi-range X-ray nano-computed tomography(CT)images display strong swelling of modified fibers after electrolyte absorption,which can effectively decrease the pore size of *** to the high electrolyte uptake(817 wt%),paper-based separator exhibits ionic conductivity of 2.93 mS cm^(-1).^(7)Li solid-state NMR spectroscopy and Gaussian simulation reveal that the formation of local high Li^(+)ion concentration in the separator and its low absorption energy with Li^(+) ion(62.2 kcal mol^(-1))is conducive to the ionic *** particular,the assembled Li/separator/LiFePO_(4) cell displays wide electrochemical stability window(5.2 V)and excellent cycle performance(capacity retention of 96.6%after 100 cycles at 0.5C)due to the reduced side reactions as well as enhanced electrolyte absorption and retention capacity by *** proposed strategy will provide a novel perspective to design high-performance biobased separators to boost the development of clean and sustainable energy economy.

关键词： Paper-based separators Lithium-ion batteries Electrochemical properties Propionylation

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Distributed Forward Stimulated Brillouin Scattering measurement on Polarization-Maintaining fiber with 80cm Spatial Resolution 21

Distributed Forward Stimulated Brillouin Scattering Measurem...

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21st International Conference on Optical Communications and Networks, ICOCN 2023

作者： Xie, Wenping Liang, Qiwen Liang, Yongchun Li, Tianfu Zhang, Hongying Dong, Yongkang Electric Power Research Institute of Guangdong Power Grid Co. Ltd. Guangzhou510080 China Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin150080 China Harbin Institute of Technology National Key Laboratory of Science and Technology on Tunable Laser Harbin150001 China

ISBN: (纸本)9798350343502

This article presents a novel distributed forward stimulated Brillouin scattering measurement scheme on polarization maintaining fiber (PM fiber) with a spatial resolution of 0.8 m named polarization separation assisted opto-mechanical time-domain analysis (PS-OMTDA). The activation pulse is injected into the fast axis and the probe pulse and probe wave is injected into the slow one, therefore, the acoustic wave is excited upon the fast axis but affected the probe wave on the slow axis. The backward Brillouin scattering of an activation pulse is effectively suppressed by isolating the acoustic activation and probing process. A spatial resolution of 80 cm is experimentally demonstrated over a PM fiber with a length of 34 m. © 2023 IEEE.

关键词： Probes

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Image Fusion Algorithm Based on Laplacian Pyramid and Principal Component Analysis Transforms 5

Image Fusion Algorithm Based on Laplacian Pyramid and Princi...

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5th International Conference on Computer Network, Electronic and Automation, ICCNEA 2022

作者： Li, Dangjuan Dong, Xiaoyu Wang, Kexuan Zhou, Mi Chen, Hang Su, Junhong Xi'an Technological University School of Optoelectronics Engineering Xi'an China Shaanxi Institute of Applied Physical Chemistry Science and Technology on Applied Physical Chemistry Laboratory Xi'an China Harbin Institute of Technology Department of Automation Measurement and Control Harbin China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

Herein, a novel image fusion algorithm based on Laplacian pyramid transform and principal component analysis (PCA) is proposed. In this algorithm, a multi-resolution transform called Laplacian pyramid transform is used to decompose the original image into sub-images. In the transform domain, the coefficients of the various sub-images are combined using a novel fusion rule that utilizes the PCA technique. Finally, the new coefficients are used in the reconstruction of the fused image. Numerical simulations are performed to test the validity and capability of the proposed fusion algorithm. The average gradient values of PCA fusion, Laplacian pyramid fusion, and the proposed fusion method, are tested, respectively. The average gradient values of the proposed method are larger than the other two methods, especially for the spectral bands over 600nm. The three methods performed a bit inferior between the 500nm and 600nm bands compared to the other spectral bands. The Laplacian pyramid transform fusion algorithm seems relatively stable, but it is obvious that the proposed fusion algorithm has a superior performance in the visible range. Moreover, the principal component of the original image was utilized, thus, preserving the spectral information of the hyperspectral image. © 2022 IEEE.

关键词： Principal component analysis

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Effect of Dy2O3 on the phase formation and electrical properties of Tl-1223 HTS

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Fizika Nizkikh Temperatur 2025年第1期51卷 59-63页

作者： Metskhvarishvili, I.R. Menelaou, Melita Lobzhanidze, T.E. Dgebuadze, G.N. Surmanidze, D.L. Bendeliani, B.G. Gabunia, V.M. Metskhvarishvili, M.R. Jishiashvili, D.A. Ilia Vekua Sukhumi Institute of Physics and Technology Laboratory of Cryogenic Technique and Technologies Georgia Tbilisi0186 Georgia Georgian Technical University Faculty of Informatics and Control Systems Department of Microprocessor and Measurement Systems Tbilisi0175 Georgia Department of Mechanical Engineering and Materials Science and Engineering Cyprus University of Technology Limassol3036 Cyprus Ivane Javakhishvili Tbilisi State University Faculty of Exact and Natural Sciences Department of Chemistry Tbilisi0179 Georgia Petre Melikishvili Institute of Physical and Organic Chemistry the Iv. Javakhishvili Tbilisi State University Tbilisi0186 Georgia "Talga" Institute of Georgian Technical University Tbilisi0186 Georgia V. Chavchanidze Institute of Cybernetics the Georgian Technical University Tbilisi0186 Georgia

TlBa2Ca2Cu3DyxO8+δ superconductor samples (x = 0–0.075) were prepared by a two-step solid-state reaction technique to investigate the impact of Dy2O3 (dysprosium sesquioxide) addition on the formation and the transport properties of the Tl-1223 phase. The samples were analyzed using X-ray powder diffraction, ac susceptibility, and high-harmonics temperature dependence to study the effects of Dy2O3 on phase formation, superconducting transition temperature Tc, and the intergrain critical current density Jc. XRD results revealed that the prepared samples are nearly single-phases Tl-1223 with a tetragonal structure. Tc is not suppressed as Dy content increased, while Jc increased up to x = 0.025, then decreased with a further increase in x. Our findings show that the presence of dysprosium sesquioxide promotes the high-Tc phase and enhances the transport critical current densities. © I. R. Metskhvarishvili, Melita Menelaou, T. E. Lobzhanidze, G. N. Dgebuadze, D. L. Surmanidze, B. G. Bendeliani, V. M. Gabunia, M. R. Metskhvarishvili, and D. A. Jishiashvili, 2025.

关键词： X ray powder diffraction

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A Lightweight Object Detection Network for Industrial Robot Based YOLOv5

A Lightweight Object Detection Network for Industrial Robot ...

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2023 China Automation Congress, CAC 2023

作者： Zhong, Tao Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

With the rapid development of deep learning, it has been widely applied in fields such as computer vision, natural language processing, and robotics. Despite the superior performance of deep learning in object detection, most industrial vision robots still rely on traditional object detection methods due to computational constraints of robot controllers. In order to improve the performance of object detection for vision robots, a lightweight 3D object detection network based on You Only Look Once version 5 (YOLOv5) is proposed for satisfying industrial production. YOLOv5 work to efficiently object detection using deep convolutional networks. In terms of model deployment, we adopt a novel OpenVINO-based model deployment approach. The OpenVINO framework significantly enhances the inference speed of models by model optimization and compression. Our model achieves a 70% reduction in inference time compared to the baseline model on CPU. The effectiveness of the proposed method is demonstrated through experiments. © 2023 IEEE.

关键词： Object detection

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An Improved YOLOv5 Detection Algorithm with Pruning and OpenVINO Quantization

An Improved YOLOv5 Detection Algorithm with Pruning and Open...

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2023 China Automation Congress, CAC 2023

作者： Chen, Cheng Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

In order to address the problem of current object detection models being too large to be deployed on robot controllers, this paper proposes improvements to YOLOv5 for real-time detection. The YOLOv5s model is pruned at the Batch Normalization (BN) layer, and further optimized using the OpenVINO tool for quantization. The results demonstrate that our improvements effectively improve the model's inference speed while maintaining its accuracy. Compared to the original YOLOv5 model, the pruned model achieves the same accuracy without degradation, with a 36.6% reduction in parameter count and a 35% reduction in weight storage file size. Furthermore, after optimization with OpenVINO, the final model achieves a FPS of 56. © 2023 IEEE.

关键词： Object detection

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Parallel Graph Attention Network Model Based on Pixel and Superpixel Feature Fusion for Hyperspectral Image Classification

Parallel Graph Attention Network Model Based on Pixel and Su...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Lisong Ma Qingyan Wang Junping Zhang Yujing Wang School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

With the development of hyperspectral sensors, there is an increasing amount of accessible hyperspectral data, and the classification task for land cover categories has gained significant attention. Existing classification methods typically extract features from either the pixel or superpixel perspective. However, using a single-scale feature extraction approach fails to simultaneously consider both local and global features of land cover, leading to suboptimal classification results. To address this issue, this paper proposes a parallel graph attention network model based on pixel and superpixel feature fusion (SSPGAT) for hyperspectral image classification, which leverages the fusion of pixel-level and superpixel-level features. The proposed approach first employs spectral convolutional layers to reduce the redundant spectral dimension. Then, it utilizes graph attention network (GAT) to extract local and global features of land cover separately from the pixel and superpixel perspectives. Finally, a fully connected network is employed to classify the fused features from both branches. Experimental results on two different datasets demonstrate the effectiveness of the proposed approach.

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engineering Vehicle Recognition and Multi-Object Tracking System based on YOLOv5 and DeepSort Algorithm 23

Engineering Vehicle Recognition and Multi-Object Tracking Sy...

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Proceedings of the 2023 5th International Conference on Video, Signal and Image Processing

作者： Yanbo Wu Xintao Liang Quan Cui Qingyan Wang Heilongjiang Government Affairs Big Data Center China School of Measurement-Control and Communication Engineering Harbin University of Science and Technology China School of Electronics and Information Engineering Harbin Institute of Technology China

ISBN: (纸本)9798400709272

This study explores traditional object detection algorithms and deep neural network-based engineering vehicle detection algorithms. We applied preprocessing algorithms such as image denoising, enhancement, and edge detection to process the images and constructed our own trainable dataset through labeling. Next, we used the YOLOv5 algorithm, which has high detection accuracy and real-time capability, for engineering vehicle detection. To address the issues of missed targets and predicted bounding box misalignment, we introduced the DeepSORT algorithm for target prediction and tracking. This algorithm utilizes Kalman filtering for estimation and updates and employs the Hungarian algorithm to associate data between consecutive frames, thereby achieving engineering vehicle tracking. To tackle the problem of frequent identity switching due to camera motion and non-uniform vehicle movements, we adopted the modified GIoU to calculate the intersection over union between trajectories and detected target bounding boxes, reducing identity jumps during the tracking process. Finally, we designed an engineering vehicle detection and tracking system and applied this algorithm to practical production.

关键词： DeepSORT algorithm YOLOv5 algorithm engineering vehicle detection multi-object tracking real-time detection

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Interface Modification of TiO_(2)Electron Transport Layer with PbCl_(2)for Perovskiote Solar Cells with Carbon Electrode

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Tsinghua Science and technology 2022年第4期27卷 741-750页

作者： Abolfazl Amraeinia Yuhua Zuo Jun Zheng Zhi Liu Guangze Zhang Liping Luo Buwen Cheng Xiaoping Zou Chunbo Li Key Laboratory on Integrated Optoelectronics Institute of SemiconductorChinese Academy of SciencesBeijing 100083China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory for SensorMOE Key Laboratory for Modern Measurement and Control TechnologyBeijing Information Science and Technology UniversityBeijing 100101China School of Science Minzu University of ChinaBeijing 100081China

Perovskite Solar Cells(PSCs)have attracted considerable attention because of their unique features and high ***,the stability of perovskite solar cells remains to be *** this study,we modified the TiO_(2)Electron Transport Layer(ETL)interface with PbCl_(2).The efficiency of the perovskite solar cells with carbon electrodes increased from 11.28%to 13.34%,and their stability obviously *** addition of PbCl_(2)had no effect on the morphology,crystal structure,and absorption property of the perovskite absorber ***,it affected the band energy level alignment of the solar cells and accelerated the electron extraction and transfer at the interface between the perovskite layer and the ETL,thus enhancing the overall photovoltaic *** interfacial modification of ETL with PbCl_(2)is a promising way for the potential commercialization of low-cost carbon electrode-based perovskite solar cells.

关键词： Perovskite Solar Cell(PSC) Electron Transport Layer(ETL) electron and hole recombination modification stability

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control of distributed-parameter systems using normal forms: An introduction

arXiv

引用

arXiv 2023年

作者： Gehring, Nicole Irscheid, Abdurrahman Deutscher, Joachim Woittennek, Frank Rudolph, Joachim Institute of Automatic Control and Control Systems Technology Johannes Kepler University Linz Austria Systems Theory and Control Engineering Saarland University Germany Institute of Measurement Control and Microtechnology Ulm University Germany Institute of Automation and Control Engineering UMIT TIROL Private University for Health Sciences and Health Technology Austria

This paper gives an overview of the control of distributed-parameter systems using normal forms. Considering linear controllable PDE-ODE systems of hyperbolic type, two methods derive tracking controllers by mapping the system into a form that is advantageous for the control design, analogous to the finite-dimensional case. A flatness-based controller makes use of the hyperbolic controller canonical form that follows from a parametrization of the system’s solutions. A backstepping design exploits the strict-feedback form of the system to recursively stabilize and transform the subsystems. © 2023, CC BY-NC-SA.

关键词： State feedback

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