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Effect of preload forces on multidimensional signal dynamic behaviours for battery early safety warning

Journal of Energy Chemistry 2024年第5期92卷 484-498页

作者： Kuijie Li Jiahua Li Xinlei Gao Yao Lu Depeng Wang Weixin Zhang Weixiong Wu Xuebing Han yuan-cheng cao Languang Lu Jinyu Wen Shijie cheng Minggao Ouyang School of Electrical and Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074HubeiChina State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China Energy and Electricity Research Center Jinan UniversityZhuhai 519070GuangdongChina Department of Mechanical Engineering Imperial College LondonLondon.SW7:2AZ.UK

Providing early safety warning for batteries in real-world applications is *** this study,comprehensive thermal abuse experiments are conducted to clarify the multidimensional signal evolution of battery failure under various preload *** time-sequence relationship among expansion force,voltage,and temperature during thermal abuse under five categorised stages is *** characteristic peaks are identified for the expansion force,which correspond to venting,internal short-circuiting,and thermal *** particular,an abnormal expansion force signal can be detected at temperatures as low as 42.4°C,followed by battery thermal runaway in approximately 6.5 ***,reducing the preload force can improve the effectiveness of the early-warning method via the expansion ***,reducing the preload force from 6000 to 1000 N prolongs the warning time(i.e.,227 to 398 s)before thermal runaway is *** on the results,a notable expansion force early-warning method is proposed that can successfully enable early safety warning approximately 375 s ahead of battery thermal runaway and effectively prevent failure propagation with module *** study provides a practical reference for the development of timely and accurate early-warning strategies as well as guidance for the design of safer battery systems.

关键词： Lithium-ion battery Thermal runaway Preload force Expansionforce Early warning Multidimensional signal

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EXTRACTION OF ANTHRAQUINONE DERIVATIVES FROM RHUBARB RHIZOMES AND THEIR ANTIBACTERIAL TESTS

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Journal of Innovative Optical Health Sciences 2011年第2期4卷 127-132页

作者： yuan-cheng cao yuan-DI ZHAO College of Life Science and Technology Huazhong University of Science and Technology Wuhan HuBeiP.R.China430074

Photometry was employed to study the optimum extraction conditions of anthraquinone derivatives from rhizomes of Rheum officinale Baill in this *** influences of extraction solvents(chloroform,benzene,ethanol,methanol,and glycerol),acid,and extraction time on the extraction yield were *** results indicate that,to the Rhubarb rhizomes powder with the average particle size 0.18 mm,the conditions of the extraction solvent composed by chloroform,glycerol,and sulfuric acid(20%)in the ratio of 4:1:1(v:v),the weight of dried Rhubarb to the solvent volume in the ratio of 1:12 ew:vT,extraction time of 110 min,the anthraquinone derivatives extraction could achieve the best *** the antibacterial tests showed the raw extraction products had the MIC(minimal inhibitory concentration)of 20μg=mL and 30μg=mL to Staphylococcus aureus and Escherichia coli,respectively.

关键词： Anthraquinone derivatives photometry optimum extraction conditions Rheum officinale Baill antibacterial

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AtomGAN:unsupervised deep learning for fast and accurate defect detection of 2D materials at the atomic scale

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Science China(Information Sciences) 2023年第6期66卷 102-114页

作者： Danpeng cheng Wuxin SHA Zuo XU Shide LI Zhigao YIN Yuling LANG Shun TANG yuan-cheng cao State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and Technology School of Computer Science and Technology Huazhong University of Science and Technology CITIC Dicastal Co. Ltd.

The extraction of atomic-level material features from electron microscope images is crucial for studying structure-property relationships and discovering new materials. However, traditional electron microscope analyses rely on time-consuming and complex human operations; thus, they are only applicable to images with a small number of atoms. In addition, the analysis results vary due to observers’ individual deviations. Although efforts to introduce automated methods have been performed previously, many of these methods lack sufficient labeled data or require various conditions in the detection process that can only be applied to the target material. Thus, in this study, we developed AtomGAN, which is a robust, unsupervised learning method, that segments defects in classical 2D material systems and the heterostructures of MoS2/WS2automatically. To solve the data scarcity problem, the proposed model is trained on unpaired simulated data that contain point and line defects for MoS2/WS2. The proposed AtomGAN was evaluated on both simulated and real electron microscope images. The results demonstrate that the segmented point defects and line defects are presented perfectly in the resulting figures, with a measurement precision of 96.9%. In addition, the cycled structure of AtomGAN can quickly generate a large number of simulated electron microscope images.

关键词： deep learning generative adversarial network defect detection atomic resolution 2D materials

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Degradation mechanism analysis of LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) single crystal cathode materials through machine learning

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npj Computational Materials 2022年第1期8卷 2119-2127页

作者： Wuxin Sha Yaqing Guo Danpeng cheng Qigao Han Ping Lou Minyuan Guan Shun Tang Xinfang Zhang Songfeng Lu Shijie cheng yuan-cheng cao School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China State Grid Huzhou Electric Power Supply Company Huzhou313000China School of Cyber Science&Engineering Huazhong University of Science and TechnologyWuhan430074China

LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2)(NCM523)has become one of the most popular cathode materials for current lithium-ion batteries due to its high-energy density and cost ***,the rapid capacity fading of NCM severely hinders its development and ***,the single crystal NCM523 materials under different degradation states are characterized using scanning transmission electron microscopy(STEM).Then we developed a neural network model with a two-sequential attention block to recognize the crystal structure and locate defects in STEM *** number of point defects in NCM523 is observed to experience a trend of increasing first and then decreasing in the degradation *** space between the transition metal columns shrinks obviously,inducing dramatic capacity *** analysis sheds light on the defect evolution and chemical transformation correlated with layered material *** also provides interesting hints for researchers to regenerate the electrochemical capacity and design better battery materials with longer life.

关键词： battery crystal analysis

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Scalable fabrication and active site identification of MOF shell-derived nitrogen-doped carbon hollow frameworks for oxygen reduction

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Journal of Materials Science & Technology 2021年第7期66卷 186-192页

作者： Jiashen Meng Ziang Liu Xiong Liu Wei Yang Lianzhou Wang Yan Li yuan-cheng cao Xingcai Zhang Liqiang Mai State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan430070China Nanomaterials Centre School of Chemical Engineering and Australian Institute for Bioengineering and NanotechnologyThe University of QueenslandSt LuciaQLD4072Australia Shenzhen Power Supply Col.Ltd. Shenzhen CityChina State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan430074China John A.Paulson School of Engineering and Applied Sciences Harvard UniversityCambridgeMA02138United States

Nitrogen-doped carbon materials as promising oxygen reduction reaction(ORR) electrocatalysts attract great interest in fuel cells and metal-air batteries because of their relatively high activity, high surface area, high conductivity and low cost. To maximize their catalytic efficiency, rational design of efficient electrocatalysts with rich exposed active sites is highly desired. Besides, due to the complexity of nitrogen species, the identification of active nitrogen sites for ORR remains challenging. Herein, we develop a facile and scalable template method to construct high-concentration nitrogen-doped carbon hollow frameworks(NC), and reveal the effect of different nitrogen species on theirORRactivity on basis of experimental analysis and theoretical calculations. The formation mechanism is clearly revealed, including low-pressure vapor superassembly of thin zeolitic imidazolate framework(ZIF-8) shell on ZnO templates,in situ carbonization and template removal. The obtained NC-800 displays better ORR activity compared with other NC-700 and NC-900 samples. Our results indicate that the superior ORR activity of NC-800 is mainly attributed to its content balance of three nitrogen species. The graphitic N and pyrrolic N sites are responsible for lowering the working function, while the pyridinic N and pyrrolic N sites as possible active sites are beneficial for increasing the density of states.

关键词： MOF shell Nitrogen-doped carbon Hollow framework Oxygen reduction Active nitrogen sites

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Preparation of nitrogen doped clews-like carbon materials and their application as the electrode in supercapacitor

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Chinese Chemical Letters 2019年第3期30卷 787-791页

作者： Shengrui Chen Jiyuan Liang Jinxing Zhao Haifeng Li Yan Liu Heming Deng Chang Liu Shun Tang yuan-cheng cao Key Laboratory of Optoelectronic Chemical Materials and Devices Ministry of Education Jianghan University State Grid Electric Power Research Institute State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology

In this work, nitrogen doped clews-like carbon materials were successfully fabricated through hydrothermal polymerization method, followed by post treatment that integrated the carbonization,activation and post-nitrogen doping into one process. This preparation method can form particular hierarchical porous structure without using any sacrificial templates. The experimental results show that the nitrogen doped clews-like hierarchical porous carbon materials possess a relatively high specific surface area of 815 m^2/g with the nitrogen content of 10.58 at%. The electrochemical properties show that the resulting sample delivers 258 F/g at a 0.5 A/g and excellent capacity retention of 79% at 20 A/g. After conducting 10,000 charge-discharge cycles at 10 A/g, the capacitance retention of 98.3% is *** intriguing results demonstrate that the obtained nitrogen doped clews-like carbon materials will be promising electrode materials for supercapacitor and other energy storage devices.

关键词： Porous carbon material Nitrogen doped Clews-like Hierarchical Electrode

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Machine learning in polymer informatics

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InfoMat 2021年第4期3卷 353-361页

作者： Wuxin Sha Yan Li Shun Tang Jie Tian Yuming Zhao Yaqing Guo Weixin Zhang Xinfang Zhang Songfeng Lu yuan-cheng cao Shijie cheng State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhanChina Shenzhen Power Supply Col.Ltd. ShenzhenChina School of Computer Science and Technology Huazhong University of Science and TechnologyWuhanChina

Polymers have been widely used in energy storage,construction,medicine,aerospace,and so ***,the complexity of chemical composition and morphology of polymers has brought challenges to their *** to the integration of machine leaming algorithms and large data resources,the data-driven methods have opened up a new road for the development of poly-mer science and *** emerging polymer informatics attempts to accelerate the performance prediction and process optimization of new poly-mers by using machine learning models based on reliable *** the grad-ual supplement of currently available databases,the emergence of new databases and the continuous improvement of machine learning algorithms,the research paradigm of polymer informatics will be more efficient and widely *** on these points,this paper reviews the development trends of machine learning assisted polymer informatics and provides a simple introduc-tion for researchers in materials,artificial intelligence,and other fields.

关键词： polymer learning artificial

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A multi-mechanism numerical simulation model for CO_(2)-EOR and storage in fractured shale oil reservoirs

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Petroleum Science 2024年第3期21卷 1814-1828页

作者： yuan-Zheng Wang Ren-Yi cao Zhi-Hao Jia Bin-Yu Wang Ming Ma Lin-Song cheng College of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China John&Willie Leone Department of Energy&Mineral Engineering The Pennsylvania State UniversityUniversity Park16802PA.USA

Under the policy background and advocacy of carbon capture,utilization,and storage(CCUS),CO_(2)-EOR has become a promising direction in the shale oil reservoir *** multi-scale pore structure distribution and fracture structure lead to complex multiphase flow,comprehensively considering multiple mechanisms is crucial for development and CO_(2) storage in fractured shale *** this paper,a multi-mechanism coupled model is developed by *** to the traditional Eclipse300 and MATLAB Reservoir Simulation Toolbox(MRST),this model considers the impact of pore structure on fluid phase behavior by the modified Peng—Robinson equation of state(PR-EOS),and the effect simultaneously radiate to Maxwell—Stefan(M—S)diffusion,stress sensitivity,the nano-confinement(NC)***,a modified embedded discrete fracture model(EDFM)is used to model the complex fractures,which optimizes connection types and half-transmissibility calculation approaches between non-neighboring connections(NNCs).The full implicit equation adopts the finite volume method(FVM)and Newton—Raphson iteration for discretization and *** model verification with the Eclipse300 and MRST is *** results show that the interaction between the mechanisms significantly affects the production performance and storage *** effect of molecular diffusion may be overestimated in oil-dominated(liquid-dominated)shale *** well spacing and injection gas rate are the most crucial factors affecting the production by sensitivity ***,the potential gas invasion risk is *** model provides a reliable theoretical basis for CO_(2)-EOR and sequestration in shale oil reservoirs.

关键词： CO_(2)-EOR CO_(2)storage Shale oil reservoir Complex fracture model Multiple mechanisms

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Oxygen reduction electrocatalysis:From conventional to single-atomic platinum-based catalysts for proton exchange membrane fuel cells

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Frontiers in Energy 2024年第2期18卷 206-222页

作者： cheng yuan Shiming ZHANG Jiujun ZHANG Institute for Sustainable Energy/College of Sciences Shanghai UniversityShanghai 200444China

Platinum(Pt)-based materials are still the most efficient and practical catalysts to drive the sluggish kinetics of cathodic oxygen reduction reaction(ORR)in proton exchange membrane fuel cells(PEMFCs).However,their catalysis and stability performance still need to be further improved in terms of corrosion of both carbon support and Pt catalyst particles as well as Pt loading *** on the developed synthetic strategies of alloying/nanostructuring Pt particles and modifying/innovating supports in developing conventional Pt-based catalysts,Pt single-atom catalysts(Pt SACs)as the recently burgeoning hot materials with a potential to achieve the maximum utilization of Pt are comprehensively reviewed in this *** design thoughts and synthesis of various isolated,alloyed,and nanoparticlecontained Pt SACs are *** single-atomic Pt coordinating with non-metals and alloying with metals as well as the metal-support interactions of Pt single-atoms with carbon/non-carbon supports are emphasized in terms of the ORR activity and stability of the *** advance further research and development of Pt SACs for viable implementation in PEMFCs,various technical challenges and several potential research directions are outlined.

关键词： oxygen reduction electrocatalysis Pt singleatom catalysts conventional Pt-based catalysts design thoughts and synthesis metal-support interactions

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The Investigation of Data Voting Algorithm for Train Air-Braking System Based on Multi-Classification SVM and ANFIS

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Chinese Journal of Electronics 2024年第1期33卷 274-281页

作者： Juhan WANG Ying GAO yuan cao Tao TANG School of Electronics and Information Engineering Beijing Jiaotong University Graduate Department China Academy of Railway Science National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University

The pressure data of the train air braking system is of great significance to accurately evaluate its operation state. In order to overcome the influence of sensor fault on the pressure data of train air braking system, it is necessary to design a set of sensor fault-tolerant voting mechanism to ensure that in the case of a pressure sensor fault, the system can accurately identify and locate the position of the faulty sensor, and estimate the fault data according to other normal data. A fault-tolerant mechanism based on multi-classification support vector machine(SVM) and adaptive network-based fuzzy inference system(ANFIS) is introduced. Multi-classification SVM is used to identify and locate the system fault state, and ANFIS is used to estimate the real data of the fault sensor. After estimation, the system will compare the real data of the fault sensor with the ANFIS estimated data. If it is similar,the system will recognize that there is a false alarm and record it. Then the paper tests the whole mechanism based on the real data. The test shows that the system can identify the fault samples and reduce the occurrence of false alarms.

关键词： Support vector machines Fault diagnosis Pressure sensors Fuzzy logic Fault tolerance Adaptive systems Fault tolerant systems

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