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Mn-based MXene with high lithium-ion storage capacity

Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Estimation of Non-Convex Pareto Front in Collision Avoidance at Urban Intersections

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2024年第2期144卷 88-96页

作者： Tamura, Akinori Arai, Sachiyo Department of Global and Environmental Studies Graduate School of Science and Engineering Chiba University Urban Environment Systems Course 1-33 Yayoi-cho Inage-ku Chiba263-8522 Japan

Inexperienced drivers, such as the elderly and novice drivers, are prone to cause traffic accidents due to human error. Autonomous driving is expected to reduce traffic accidents by assisting their recognition, judgment, and operation. However, it is only effective in situations where drivers can easily make decisions, such as driving on highways, and is still challenging in urban areas. In this paper, we focus on safe and efficient autonomous driving in situations where multiple moving obstacles simultaneously exist, assuming an urban intersection. Since it is difficult to construct a driving model for such a situation, we introduced a reinforcement learning method that does not require a driving model. This paper proposes a collision-avoidance problem as a multi-objective sequential decision-making problem. We propose a method for learning a non-convex Pareto front concerning safety and speed using the multi-objective reinforcement learning algorithm, Pareto-DQN. The proposed method’s performance through computer experiments is verified in a T-intersection environment. We confirmed the acquisition of multiple Pareto-optimal driving policies that could not be achieved using conventional methods with linear scalarization. The proposed method is helpful for system designers because it provides a more detailed representation of the driver’s non-convex preferences. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Collision avoidance

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Relationship between X-Ray and Mechanical Elastic Constants of CoNiCrAlY Coating

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Zairyo/Journal of the Society of Materials science, Japan 2025年第4期74卷 238-244页

作者： Hayase, Tomoyuki Sasaya, Hiroto Hasunuma, Shota Waki, Hiroyuki Department of Mechanical Engineering Aoyama Gakuin University Fuchinobe Chuo-ku Kanagawa Sagamihara252-5258 Japan Graduate School of Science and Engineering Aoyama Gakuin University Fuchinobe Chuo-ku Kanagawa Sagamihara252-5258 Japan Department of Systems Innovation Engineering Iwate University Morioka Iwate Ueda020-8551 Japan

A thermally sprayed MCrAlY alloy coating in a thermal barrier coating system, called a "bond coat" (BC), is applied to the hot sections of gas turbines and jet engines. Residual stress in the BC is generated during spraying and after thermal exposure. Residual stress in sprayed coatings is an important characteristic that determines the development of high-performance materials and processes. X-ray diffraction is useful for evaluating the residual stress as well as the in situ stress change during thermal exposure. The X-ray elastic constants, which are necessary for evaluating the residual stress using this method, result in an accurate evaluation of the residual stress of a thin coating layer. However, systematic research on the effects of microstructural changes has yet to be conducted. In this study, the influence of high-temperature exposure on the X-ray elastic constants of an atmospheric-plasma-sprayed (APSed) BC was investigated by bending a two-layer specimen. Additionally, a dense high-velocity oxygen fuel (HVOF) BC was evaluated to elucidate the influence of sliding splat particles. Finally, the relationship between the X-rays and mechanical elastic constants of the BC was studied. It was found that the X-ray elastic constants of the as-sprayed APS BC were higher than the mechanical elastic constants due to the sliding deformation between the splat particles. Similarly, the X-ray elastic constants of HVOF BC were higher than the mechanical constants, as same as APS BC. However, the difference between the elastic constants was smaller than that of APS BC. The influence of sliding deformation of both coatings was suppressed by thermal exposure, and the X-ray elastic constants approached the mechanical constants. ©2025 The Society of Materials science, Japan.

关键词： Sprayed coatings

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A Non-Iterative LMI-Based Design of Static Output Feedback control with L2 Gain Performance for Linear systems 6

A Non-Iterative LMI-Based Design of Static Output Feedback C...

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6th International Conference on Electrical, control and Instrumentation engineering, ICECIE 2024

作者： Oya, Hidetoshi Asada, Daiki Nagai, Shunya Nakano, Kazushi Tokyo City University Department of Computer Science Tokyo Japan Graduate School of Integrative Science and Engineering Tokyo City University Tokyo Japan Niihama College Department of Electronics and Control Engineering Ehime Japan Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

ISBN: (纸本)9798350380040

In this paper, we present a new LMI-based non-iterative design strategy for static output feedback controllers with L2 Gain Performance for linear systems. In our approach, on the basis of the well-known necessary and sufficient condition for the existence of the static output feedback control for linear systems, the non-iterative LMI-based design procedure for the proposed static output feedback controller is derived. In this paper, we show the LMI-based non-iterative design procedure for static output feedback controllers with L2 Gain Performance and the effectiveness of the proposed static output feedback control is presented through a simple illustrative example. © 2024 IEEE.

关键词： Feedback control

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Context-aware Inductive Graph Matrix Completion with Sentence BERT

Context-aware Inductive Graph Matrix Completion with Sentenc...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Han, Donghee Kim, Daehee Han, Keejun Yi, Mun Yong Korea Advanced Institute of Science and Technology Graduate School of Data Science Daejeon Korea Republic of Hansung University School of Computer Engineering Seoul Korea Republic of Korea Advanced Institute of Science and Technology Department of Industrial and Systems Engineering Daejeon Korea Republic of

ISBN: (纸本)9798350304855

Existing graph neural network (GNN) based recommendation models depend highly on initial node features and graph structures. Most prior studies do not support the use of additional information on user-item interactions and adopt a transductive method, which has limitations for actual web service. To overcome these problems, we propose Context-aware Inductive Graph Matrix Completion (CGMC), which utilizes context vectors that represent user-item interactions and user-item bipartite graph structures in an inductive manner. Our method constructs context vectors from the review, timestamp, and rating and uses them as edge features of the user-item bipartite graph. Relations between homogeneous nodes are also constructed based on common neighbors. Our model combines context vectors and relational information using Context-aware Graph Attention Networks and Edge Fusion Graph Convolutional Networks. We conducted extensive experiments using six real-world datasets, and the results show that the proposed model achieves superior performances over other competing models. Furthermore, we analyzed the inductive characteristics of CGMC through the cross-domain transferability. The source code is available in the repository at [https://***/venzino-han/CGMC_SBERT]. © 2023 IEEE.

关键词： Recommender systems

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Enhanced Growth Optimizer and Its Application to Multispectral Image Fusion

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Computers, Materials & Continua 2024年第11期81卷 3033-3062页

作者： Jeng-Shyang Pan Wenda Li Shu-Chuan Chu Xiao Sui Junzo Watada College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Management Chaoyang University of TechnologyTaichung413310Taiwan Graduate School of Information Production and SystemsWaseda UniversityKitakyushu808-0135Japan

The growth optimizer(GO)is an innovative and robust metaheuristic optimization algorithm designed to simulate the learning and reflective processes experienced by individuals as they mature within the social ***,the original GO algorithm is constrained by two significant limitations:slow convergence and high mem-ory *** restricts its application to large-scale and complex *** address these problems,this paper proposes an innovative enhanced growth optimizer(eGO).In contrast to conventional population-based optimization algorithms,the eGO algorithm utilizes a probabilistic model,designated as the virtual population,which is capable of accurately replicating the behavior of actual populations while simultaneously reducing memory ***,this paper introduces the Lévy flight mechanism,which enhances the diversity and flexibility of the search process,thus further improving the algorithm’s global search capability and convergence *** verify the effectiveness of the eGO algorithm,a series of experiments were conducted using the CEC2014 and CEC2017 test *** results demonstrate that the eGO algorithm outperforms the original GO algorithm and other compact algorithms regarding memory usage and convergence speed,thus exhibiting powerful optimization ***,the eGO algorithm was applied to image *** a comparative analysis with the existing PSO and GO algorithms and other compact algorithms,the eGO algorithm demonstrates superior performance in image fusion.

关键词： Growth optimizer probabilistic model Lévy flight image fusion

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Rectification and converter control of the FPSLGs for energy storage applications

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IET Renewable Power Generation 2024年第9-10期18卷 1611-1625页

作者： Ali, Murad Haitao, Yu Mobayen, Saleh Zhang, Jiahui Zhilenkov, Anton Din, Zakiud School of Electrical Engineering Southeast University Nanjing China Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Department of Cyber-Physical Systems St. Petersburg State Marine Technical University Saint-Petersburg Russia Department of Mechatronics Engineering College of Electrical and Mechanical Engineering National University of Sciences and Technology Islamabad Pakistan

This article presents two power converters with controllers attached to the Free-Piston Stirling Linear Generator (FPSLG) and energy storage system (ESS). The rectifier uses hysteresis-SVPWM current regulation and CB-SPWM, while the buck-boost converter utilizes the dual-loop PI control method. The storage battery receives energy from a linear-generator with a rectifier and converter. The FPSE and linear motors in the FPSLG convert thermal to electrical energy. A two-level electrical energy conversion technique using a three-phase AC signal to DC and DC-DC converter has been devised to reduce output electrical energy oscillation as well as stabilize the generating system's DC power. Initially, the FPSE's nonlinear model and the three-phase permanent magnet linear-motor's linear mathematical model were created and followed by the ESS and control mechanism simulation. The simulation shows that the ESS system and control approach can give stable power to the storage battery using linear-generator power. The PR controller replaces the PI controller in the position loop to improve frequency and displacement tracing. The control system design was simulated in MATLAB and the topology's feasibility and correctness were confirmed. Comparative analysis shows that, rectifier uses the H-SVPWM's unity power factor of AC and stability controllability of the DC-side voltage is better than the CB-SPWM approach. © 2024 The Author(s). IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： controllers

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Frontiers in high entropy alloys and high entropy functional materials

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Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao Zhang Xue-Qian Wang Feng-Qi Zhang Xiao-Ya Cui Bing-Bing Fan Jia-Ming Guo Zhi-Min Guo Rui Huang Wen Huang Xu-Bo Li Meng-Ru Li Yan Ma Zhi-Hua Shen Yong-Gang Sun De-Zhuang Wang Fei-Yang Wang Li-Qiang Wang Nan Wang Tian-Li Wang Wei Wang Xiao-Yang Wang Yi-Han Wang Fu-Jie Yu Yu-Zhen Yin Ling-Kun Zhang Yi Zhang Jian-Yang Zhang Qi Zhao Yu-Ping Zhao Xin-Dong Zhu Yasir Sohail Ya-Nan Chen Tao Feng Qi-Long Gao Hai-Yan He Yong-Jiang Huang Zeng-Bao Jiao Hua Ji Yao Jiang Qiang Li Xiao-Ming Li Wei-Bing Liao Huai-Jun Lin Hui Liu Qi Liu Qing-Feng Liu Wei-Di Liu Xiong-Jun Liu Yang Lu Yi-Ping Lu Wen Ma Xue-Fei Miao Jie Pan Qing Wang Hong-Hui Wu Yuan Wu Tao Yang Wei-Ming Yang Qian Yu Jin-Yu Zhang Zhi-Gang Chen Liang Mao Yang Ren Bao-Long Shen Xun-Li Wang Zhe Jia He Zhu Zhen-Duo Wu Si Lan School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and EngineeringSoutheast UniversityNanjing 211189China Department of Physics City University of Hong KongHongKong 999077China School of Materials Science and Engineering Tianjin UniversityTianjin 300072China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China Department of Mechanical Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 100872China Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Institute of Advanced Wear&Corrosion Resistance and Functional Materials Jinan UniversityGuangzhou 510632China School of Mechanics and Civil Engineering China University of Mining and TechnologyXuzhou 221116China School of Physical Sciences Great Bay UniversityDongguan 523000China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical EngineeringNanjing Tech UniversityNanjing 211816China Beijing Advanced Innovation Center for Materials Genome Engineering Research Institute for Carbon NeutralityUniversity of Science and Technology BeijingBeijing 100083China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China School of Computing Macquarie UniversitySydney 2113Australia Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laborato

Owing to their exceptional properties,high-entropy alloys(HEAs)and high-entropy materials have emerged as promising research areas and shown diverse ***,the recent advances in the field are comprehensively reviewed,organized into five *** first section introduces the background of HEAs,covering their definition,significance,application prospects,basic properties,design principles,and *** subsequent section focuses on cutting-edge high-entropy structural materials,highlighting developments such as nanostructured alloys,grain boundary engineering,eutectic systems,cryogenic alloys,thin films,micro-nano-lattice structures,additive manufacturing,high entropy metallic glasses,nano-precipitate strengthened alloys,composition modulation,alloy fibers,and refractory *** the following section,the emphasis shifts to functional materials,exploring HEAs as catalysts,magneto-caloric materials,corrosion-resistant alloys,radiation-resistant alloys,hydrogen storage systems,and materials for ***,the review encompasses functional high-entropy materials outside the realm of alloys,including thermoelectric,quantum dots,nanooxide catalysts,energy storage materials,negative thermal expansion ceramics,and high-entropy wave absorption *** paper concludes with an outlook,discussing future directions and potential growth areas in the *** this comprehensive review,researchers,engineers,and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： High entropy alloys Cutting-edge structural materials Cutting-edgefunctional materials

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Adaptive FRIT-Based Recursive Robust controller Design Using Forgetting Factors 32

Adaptive FRIT-Based Recursive Robust Controller Design Using...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Tsuruhara, Satoshi Ito, Kazuhisa Graduate School of Engineering and Science Functional Control Systems Shibaura Institute of Technology Minuma Saitama3378570 Japan Japan Society for the Promotion of Science Tokyo1020083 Japan Shibaura Institute of Technology Department of Machinery and Control Systems Minuma Saitama3378570 Japan

ISBN: (纸本)9798350395440

Adaptive FRIT (A-FRIT) with exponential for-getting (EF) has been proposed for time-varying systems to improve the data dependence of FRIT, which is a direct data-driven tuning method. However, the EF -based method is not a reliable controller because it can cause significant degradation of the control performance and instability unless the persistent excitation (PE) condition is satisfied. To solve this problem, we propose a new A-FRIT method based on directional forgetting (DF) and exponential resetting that can forget old data without instability regardless of the PE condition. To confirm the effectiveness of the proposed method, we applied it to artificial muscle control with strong asymmetric hysteresis characteristics and evaluated its robust performance against load changes during the experiment. The experimental results show that the proposed method based on DF achieves high control performance and is robust against changes in the characteristics and/or target trajectory. The proposed method is also practical because it does not require system identification, model structure, or prior experimentation. © 2024 IEEE.

关键词： Time varying systems

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A Study on Purchasing Behavior Analysis Method by Comparing Difference in Latent Class Distributions between Membership Stages

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Journal of Japan Industrial Management Association 2022年第2期73卷 54-69页

作者： Yang, Tianxiang Yamashita, Haruka Goto, Masayuki Major of Industrial and Management Systems Engineering Graduate School of Creative Science and Engineering Waseda University Japan Department of Information and Communication Sciences Faculty of Science and Technology Sophia University Japan Department of Industrial and Management Systems Engineering School of Creative Science and Engineering Waseda University Japan

A marketing policy called the"Membership Stage System" is widely used in retail business. A membership stage provides benefits to customers such as shopping points when a customer's annual cumulative purchase amount exceeds a certain threshold and the customer's stage is raised a level. As a result, the company is not only able to promote the customer's willingness to purchase, but it can also obtain the purchasing history data, thereby enabling high-quality customer analysis. The most fundamental analysis is to infer the difference of purchasing characteristics between member stages and to construct different clustering models for each member stage. However, when the clustering models are learned independently for each membership stage, it is not possible to compare the obtained clusters between membership stages. In this study, we propose a new analytical method and its learning algorithm to analyze differences in cluster distribution between membership stages. Through demonstrating the proposed model applied to an actual data set of purchasing history data on a membership stage system, the effectiveness of our proposal is clarified. © 2022 Japan Industrial Management Association. All rights reserved.

关键词： Sales

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