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M_(4)X_(3) MXenes:Application in Energy Storage Devices

Nano-Micro Letters 2024年第10期16卷 522-542页

作者： Iftikhar Hussain Waqas Ul Arifeen Shahid Ali Khan Sikandar Aftab Muhammad Sufyan Javed Sajjad Hussain Muhammad Ahmad Xi Chen Jiyun Zhao PRosaiah Khaled Fahmi Fawy Adnan Younis Sumanta Sahoo Kaili Zhang Department of Mechanical Engineering City University of Hong Kong83 Tat Chee AvenueKowloon TongHong KongPeople's Republic of China School of Mechanical Engineering Yeungnam UniversityDaehak-roGyeongsan-siGyeongbuk-do 38541South Korea Department of Semiconductor Systems Engineering and Clean Energy Sejong UniversitySeoul 05006Republic of Korea School of Physical Science and Technology Lanzhou UniversityLanzhou 730000People's Republic of China Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea Department of Physics Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)ThandalamChennai 602105India Department of Chemistry Faculty of ScienceKing Khalid UniversityP.O.Box 900461413 AbhaSaudi Arabia Department of Physics College of ScienceUnited Arab Emirates UniversityP.O.Box 15551Al-AinUnited Arab Emirates School of Chemical Engineering Yeungnam UniversityGyeongsanGyeongbuk 38541South Korea

MXene has garnered widespread recognition in the scientific com-munity due to its remarkable properties,including excellent thermal stability,high conductivity,good hydrophilicity and dispersibility,easy processability,tunable surface properties,and admirable *** have been categorized into different families based on the number of M and X layers in M_(n+1)X_(n),such as M_(2)X,M_(3)X_(2),M_(4)X_(3),and,recently,M_(5)X_(4).Among these families,M_(2)X and M_(3)X_(2),par-ticularly Ti_(3)C_(2),have been greatly explored while limited studies have been given to M_(5)X_(4)MXene ***,studies on the M_(4)X_(3)MXene family have developed recently,hence,demanding a compilation of evaluated ***,this review provides a systematic overview of the latest advancements in M_(4)X_(3)MXenes,focusing on their properties and applications in energy storage *** objective of this review is to provide guidance to researchers on fostering M_(4)X_(3)MXene-based nanomaterials,not only for energy storage devices but also for broader applications.

关键词： MXene M_(4)X_(3)MXenes 2D materials Energy storage Properties

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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Layered niobium carbide enabling excellent kinetics and cycling stability of Li-Mg-B-H hydrogen storage material Layered niobium carbide enabling excellent kinetics

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Rare Metals 2024年第3期43卷 1153-1166页

作者： Li-Wen Lu Hui Luo Guang-Xu Li Yun Li Xin-Hua Wang Cun-Ke Huang Zhi-QiangLan Wen-Zheng Zhou Jin Guo Mohammad Ismail Hai-Zhen Liu Guangxi Novel Battery Materials Research Center of Engineering Technology Guangxi Colleges and Universities Key Laboratory of Blue Energy and Systems IntegrationSchool of Physical Science and TechnologyGuangxi UniversityNanning530004China State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures Nanning530004China School of Mechanical and Electrical Engineering Quzhou College of TechnologyQuzhou324000China Department of Materials Science and Engineering Zhejiang UniversityHangzhou310027China Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu21030Kuala NerusTerengganuMalaysia Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) Nankai UniversityTianjin300071China

The Li-Mg-B-H composite(2LiBH_(4)+MgH_(2))has a high capacity of 11.4 wt%as a hydrogen storage ***,the slow kinetics and poor cycling stability severely restrict its practical *** this work,a layered Nb_(2)C MXene was first synthesized and then introduced to tailor the kinetics and cycling stability of the Li-Mg-B-H *** milled 2LiH+MgB_(2)composites were initially hydrogenated to obtain the 2LiBH_(4)+MgH_(2)*** 2LiBH_(4)+MgH_(2)+5wt%Nb_(2)C can release 9.0 wt%H_(2)in 30 min at 400℃,while it is only 2.7 wt%for the undoped 2LiBH_(4)+MgH_(2).The dehydrogenation activation energies of MgH_(2)and LiBH_(4)are 123 and 154 kJ·mol^(-1)respectively for the 5 wt%Nb_(2)C-doped composite,lower than the undoped composite(164 and 165 kJ·mol^(-1)).The 2LiBH_(4)+MgH_(2)+5 wt%Nb_(2)C possesses excellent cycling stability,with the reversible capacity only slightly reduced from 9.4 wt%for the 1st cycle to 9.3 wt%for the 20th ***_(2)C keeps stable in the composite and acts as an efficient catalyst for the Li-Mg-B-H *** is believed that both the layered structure and the active Nb element contribu te to the enhanced hydrogen storage performances of the Li-Mg-B-H *** work confirms that the Nb_(2)C MXene with layered stru cture has a significant enhancing impact on the Li-Mg-B-H hydrogen storage materials,which is different from the bulk NbC.

关键词： Hydrogen storage Lithium borohydride Magnesium hydride Nb_(2)C MXene

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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MXene@c-MWCNT Adhesive Silica Nanofiber Membranes Enhancing Electromagnetic Interference Shielding and Thermal Insulation Performance in Extreme Environments

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Nano-Micro Letters 2024年第10期16卷 82-98页

作者： Ziyuan Han Yutao Niu Xuetao Shi Duo Pan Hu Liu Hua Qiu Weihua Chen Ben Bin Xu Zeinhom MEl-Bahy Hua Hou Eman Ramadan Elsharkawy Mohammed AAmin Chuntai Liu Zhanhu Guo Key Laboratory of Materials Processing and Mold(Zhengzhou University) Ministry of EducationNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002People's Republic of China School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaHefei 230026People's Republic of China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Advanced Materials DivisionSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123People's Republic of China Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi'an 710072People's Republic of China College of Chemistry&Green Catalysis Center Zhengzhou UniversityZhengzhou 450001People's Republic of China Mechanical and Construction Engineering Faculty of Engineering and EnvironmentNorthumbria UniversityNewcastle Upon Tyne NE18UK Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City 11884CairoEgypt Department of Chemistry Faculty of ScienceNorthern Border UniversityArarSaudi Arabia Department of Chemistry College of ScienceTaif UniversityP.O.Box 1109921944 TaifSaudi Arabia

A lightweight flexible thermally stable composite is fabricated by com-bining silica nanofiber membranes(SNM)with MXene@c-MWCNT hybrid *** flexible SNM with outstanding thermal insulation are prepared from tetraethyl orthosilicate hydrolysis and condensation by electrospinning and high-temperature calcination;the MXene@c-MWCNT_(x:y)films are prepared by vacuum filtration *** particular,the SNM and MXene@c-MWCNT_(6:4)as one unit layer(SMC_(1))are bonded together with 5 wt%polyvinyl alcohol(PVA)solution,which exhibits low thermal conductivity(0.066 W m^(-1)K^(-1))and good electromagnetic interference(EMI)shielding performance(average EMI SE_(T),37.8 dB).With the increase in func-tional unit layer,the overall thermal insulation performance of the whole composite film(SMC_(x))remains stable,and EMI shielding performance is greatly improved,especially for SMC_(3)with three unit layers,the average EMI SET is as high as 55.4 *** addition,the organic combination of rigid SNM and tough MXene@c-MWCNT_(6:4)makes SMC_(x)exhibit good mechanical tensile ***,SMC_(x)exhibit stable EMI shielding and excellent thermal insulation even in extreme heat and cold ***,this work provides a novel design idea and important reference value for EMI shielding and thermal insulation components used in extreme environmental protection equipment in the future.

关键词： SiO_(2)nanofiber membranes MXene@c-MWCNT Composite film Thermal insulation Electromagnetic interference shielding

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Neural-Network-Based control for Discrete-Time Nonlinear systems with Input Saturation Under Stochastic Communication Protocol

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 766-778页

作者： Xueli Wang Derui Ding Hongli Dong Xian-Ming Zhang Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Software and Electrical Engineering Swinburne University of TechnologyMelbourne 3122VictoriaAustralia Institute of Complex Systems and Advanced Control Northeast Petroleum UniversityDaqing 163318China

In this paper,an adaptive dynamic programming(ADP)strategy is investigated for discrete-time nonlinear systems with unknown nonlinear dynamics subject to input *** save the communication resources between the controller and the actuators,stochastic communication protocols(SCPs)are adopted to schedule the control signal,and therefore the closed-loop system is essentially a protocol-induced switching system.A neural network(NN)-based identifier with a robust term is exploited for approximating the unknown nonlinear system,and a set of switch-based updating rules with an additional tunable parameter of NN weights are developed with the help of the gradient *** virtue of a novel Lyapunov function,a sufficient condition is proposed to achieve the stability of both system identification errors and the update dynamics of NN ***,a value iterative ADP algorithm in an offline way is proposed to solve the optimal control of protocol-induced switching systems with saturation constraints,and the convergence is profoundly discussed in light of mathematical ***,an actor-critic NN scheme is developed to approximate the control law and the proposed performance index function in the framework of ADP,and the stability of the closed-loop system is analyzed in view of the Lyapunov ***,the numerical simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Adaptive dynamic programming(ADP) constrained inputs neural network(NN) stochastic communication protocols(SCPs) suboptimal control

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Synchronous control of H-type Linear Motor System via Super-Twisting Sliding Mode

Synchronous Control of H-type Linear Motor System via Super-...

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Chinese Automation Congress (CAC)

作者： Jiawei Liu Xiaolei Li Feilong Tang Qixin Kui Miodrag D. Spasic Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Control Systems Faculty of Electronic Engineering University of Niš Niš Serbia

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In this paper, a synchronous control strategy based on super-twisting sliding mode algorithm is proposed to enhance the tracking accuracy and robustness of H-type linear motor systems. Such systems are widely utilized in precision manufacturing owing to their high precision and fast response. Firstly, the dynamic model is established based on the coupling dynamics analysis of the H-type system. Secondly, a supertwisting sliding mode controller (STSMC) with linear terms is designed, which effectively reduces the chattering associated with conventional sliding mode control, while maintaining good robustness. Thirdly, a super-twisting extended state observer (STESO) is introduced to handle large fluctuations in the early estimation process of linear extended state observer (LESO), so as to effectively observe and compensate the uncertainties and external disturbances. Finally, experimental results demonstrate that the STESO-based STSMC greatly improves the anti-disturbance ability and tracking accuracy of the H-type system.

关键词： Robust control Analytical models Accuracy Uncertainty Motors Robustness PD control State estimation Sliding mode control Time-varying systems

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Design of unbiased reduced order filter for stochastic systems with sampled measurements 12

Design of unbiased reduced order filter for stochastic syste...

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12th International Conference on Mathematical Modeling in Physical sciences, IC-MSQUARE 2023

作者： Kamenshchikov, Mikhail Lomonosov Moscow State University Faculty of Computational Mathematics and Cybernetics Department of Nonlinear Dynamical Systems and Control Processes Moscow119991 Russia V. A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences Laboratory of Terminal Control Systems Moscow117997 Russia National University of Science and Technology "MISiS" Department of Engineering Cybernetics Moscow119049 Russia

The problem of synthesizing reduced order filter, that forms an unbiased estimate of linear functional from an unknown phase vector of a continuous time stochastic system with sampled measurements and additive noises, is considered in this work. The H2 norm of the weighted transfer function from input noises to estimation error is used as a performance criterion. The method for reduced order filter design is based on the expression of the explicit dependence of performance criterion on unknown parameters in the canonical basis and the application of the non-convex optimization technique. Numerical simulations are performed to illustrate the proposed approach. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Stochastic systems

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Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic

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Computers, Materials & Continua 2023年第4期75卷 427-442页

作者： Reem Alkanhel El-Sayed M.El-kenawy D.L.Elsheweikh Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia

Traffic prediction of wireless networks attracted many researchersand practitioners during the past decades. However, wireless traffic frequentlyexhibits strong nonlinearities and complicated patterns, which makes it challengingto be predicted accurately. Many of the existing approaches forpredicting wireless network traffic are unable to produce accurate predictionsbecause they lack the ability to describe the dynamic spatial-temporalcorrelations of wireless network traffic data. In this paper, we proposed anovel meta-heuristic optimization approach based on fitness grey wolf anddipper throated optimization algorithms for boosting the prediction accuracyof traffic volume. The proposed algorithm is employed to optimize the hyperparametersof long short-term memory (LSTM) network as an efficient timeseries modeling approach which is widely used in sequence prediction *** prove the superiority of the proposed algorithm, four other optimizationalgorithms were employed to optimize LSTM, and the results were *** evaluation results confirmed the effectiveness of the proposed approachin predicting the traffic of wireless networks accurately. On the other hand,a statistical analysis is performed to emphasize the stability of the proposedapproach.

关键词： Network traffic soft computing LSTM metaheuristic optimization

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