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A plastic iron-based nanocrystalline alloy with high saturation magnetic flux density and low coercivity via flexible-annealing

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Journal of Materials Science & Technology 2024年第23期190卷 229-235页

作者： Xuesong Li Rongce Sun Dongyang Li Chengyue Song Jing Zhou Zhiyong Xue Chuntao Chang Baoan Sun Bo Zhang Haibo Ke Weihua Wang Haiyang Bai School of Energy Power and Mechanical Engineering North China Electric Power UniversityBeijing 102206China Songshan Lake Materials Laboratory Dongguan 523808China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808China Institute of Physics Chinese Academy of SciencesBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences100049 BeijingChina

The traditional high-temperature annealing process is difficult to control the morphology and size of the crystallization phases in amorphous alloy systems with high ferromagnetic element content,lead-ing to mechanical brittleness and soft magnetic properties ***,we developed a flexible-annealing technique and successfully achieved a fine nanocrystalline structure in a high-ferromagnetic-content system of(Fe_(0.8)Co_(0.2))_(85)Si_(2)B_(12)Cu_(0.8)Mo_(0.2).It is exciting that the(Fe_(0.8)Co_(0.2))_(85)Si_(2)B_(12)Cu_(0.8)Mo_(0.2) nanocrystalline alloy exhibits high Bs up to 1.88 T,low coercivity of 6.3 A m-1,as well as good *** excellent comprehensive properties are attributed to the controllable construction of di-luted amorphous-nanocrystalline structure,the rapid release of internal stress,and the suppression of relaxation-induced uniformity achieved by the flexible annealing *** results provide a fast and new paradigm for the development of next-generation high-Bs soft magnetic materials.

关键词： Nanocrystalline alloy Flexible annealing High saturation magnetic flux density Low,coercivity Plastic

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Machine learning accelerated DFT research on platinum-modified amorphous alloy surface catalysts

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Chinese Chemical Letters 2023年第5期34卷 645-649页

作者： Xi Zhang Kangpu Li Bo Wen Jiang Ma Dongfeng Diao Institute of Nanosurface Science and Engineering Guangdong Provincial Key Laboratory of Micro/NanoShenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Research Center of Medical Plasma Technology Shenzhen UniversityShenzhen 518060China

Pt-modified amorphous alloy(Pt@PdNiCuP)catalyst exhibits excellent electro-catalytic activity and high experimental durability for hydrogen evolution reaction(HER).However,the physical origin of the catalytically active remains *** this paper,we constructed a distance contribution descriptor(DCD)for the feature engineering of machine learning(ML)potential,and calculated the Gibbs free energies(ΔGH)of 46,000*H binding sites on the Pt@Pd Ni Cu P surface by ML-accelerated density functional theory(DFT).The relationship betweenΔGHand DCD revealed that in the H-Pt distance region of 2.0-2.5 A where the parabolic tail and disordered scatters coexist,the H-metal bonding configuration is mainly the bridge-or hollow-bonding *** contribution analysis of DCD indicates that the joint effect of Pt,Pd and Ni atoms determines the catalytical behavior of amorphous alloy,which agrees well with experimental *** counting atomic percentages in different energy intervals,we obtained the atomic ratio for the best catalytic performance(Pt:Pd:Ni:Cu:P=0.33:0.17:0.155:0.16:0.185).Projected density of states(PDOS)show that H 1s orbital,Pt 5d orbital,and Pd 4d orbital form a bonding state at-2 e *** results provide new ideas for designing more active amorphous alloy catalysts.

关键词： Hydrogen evolution reaction Amorphous alloy Density functional theory Machine learning

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Adaptive backstepping sliding mode control of lower limb exoskele-ton robot based on combined double power reaching law 12

Adaptive backstepping sliding mode control of lower limb exo...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2022

作者： Xu, Wen-Xin Cao, Guang-Zhong Zhang, Yue-Peng Chen, Jiang-Cheng Tan, Dong-Po Ling, Zi-Qin Shenzhen University Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen Key Laboratory of Electromagnetic Control College of Mechatronics and Control Engineering Shenzhen518060 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

This paper presents an adaptive backstepping sliding mode control (ABSM) method based on the combined double power reaching law (CDPRL) for a lower limb exoskeleton robot (LLER) system. Considering the influence of robot nonlinearity, strong coupling and unknown external disturbance, the ABSM controller is designed, and the CDPRL is employed to achieve fast convergence and reducing chattering phenomenon of the sliding mode control. The experiment results show that the pro-posed method can availably weaken the chattering phenomenon, and improve the accuracy of trajectory tracking and anti-inter- ference ability in comparison with advanced and classical meth- ods. © 2022 IEEE.

关键词： Sliding mode control

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Geometric Programming for Nonlinear Satellite Buffer Networks With Time Delays under L_(1)-Gain Performance

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 554-556页

作者： Yukang Cui Yihui Huang Michael V.Basin Zongze Wu College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Shenzhen University Shenzhen 518060China Peng Cheng Laboratory Shenzhen 518060China Robotics Institute Ningbo University of TechnologyNingbo 315211China Autonomous University of Nuevo Leon Nuevo Leon 66455Mexico

Dear Editor,This letter concerns the parameter tuning problem for nonlinear satellite buffer networks with communication delays, aiming to optimize their stability properties under L_(1)-gain. We first model the satellite buffer networks by a nonlinear time-delay positive system and propose a novel characterization under which the nonlinear system is asymptotically stable with a prescribed L_(1)-induced performance.

关键词： nonlinear system prescribed

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Exploring the range of optical memory effect by deep learning 8

Exploring the range of optical memory effect by deep learnin...

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8th International Conference on Speckle Metrology, Speckle 2023

作者： Chen, Juncheng Lu, Dajiang Cai, Jiapeng Chen, Zaoxin Peng, Xiang He, Wenqi Key Laboratory of Optoelectronic Devices Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China

ISBN: (数字)9781510674592

ISBN: (纸本)9781510674585

Among the various methods for imaging through scattering media, the speckle autocorrelation imaging method based on optical memory effect (OME) has gained significant attention for its non-invasive single-shot imaging capability through scatter media. However, the imaging range of this method is limited by OME. This paper presents a physics-informed deep learning strategy that establishes relationships among different linearly-shift-invariant subsystems based on OME to explore the range of OME range. By leveraging the feature extraction capabilities of deep learning, the proposed approach recovers sidelobes from the speckle autocorrelation patterns of objects in several OME regions. Then, a phase retrieval algorithm is employed to achieve object reconstruction. In the future, the approach can be extended to integrate different small regions of the object plane into a big one which can be linear shift invariant. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Autocorrelation

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Drivers’ EEG Responses to Different Distraction Tasks

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Automotive Innovation 2023年第1期6卷 20-31页

作者： Guofa Li Xiaojian Wu Arno Eichberger Paul Green Cristina Olaverri‑Monreal Weiquan Yan Yechen Qin Yuezhi Li College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400044China Institute of Human Factors and Ergonomics College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China Institute of Automotive Engineering Graz University of Technology8010 GrazAustria University of Michigan Transportation Research Institute and Department of Industrial and Operations Engineering University of MichiganAnn ArborMI 48109USA Chair ITS‑Sustainable Transport Logistics 4.0 Johannes Kepler University4040 LinzAustria Department of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Laboratory of Neural Engineering College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China

Driver distraction has been deemed a major cause of traffic ***,drivers’brain response activities to different distraction types have not been well *** purpose of this study is to investigate the response of electroencephalography(EEG)activities to different distraction *** the conducted simulation tests,three secondary tasks(i.e.,a clock task,a 2-back task,and a navigation task)are designed to induce different types of driver ***-four participants are recruited for the designed tests,and differences in drivers’brain response activities concerning distraction types are *** results show that the differences in comprehensive distraction are more significant than that in single cognitive *** test and post hoc two-tailed Nemenyi test are conducted to further identify the differences in band activities among brain *** results show that the theta energy in the frontal lobe is significantly higher than that in other brain regions in distracted driving,whereas the alpha energy in the temporal lobe significantly decreases compared to other brain *** results provide theoretical references for the development of distraction detection systems based on EEG signals.

关键词： Driving safety Driver distraction EEG Autonomous vehicle

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Low Overlapping Plant Point Cloud Registration and Splicing Method Based on FPFH 17th

Low Overlapping Plant Point Cloud Registration and Splicing ...

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17th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2022

作者： Lin, Shengdong Peng, Yeping Cao, Guangzhong Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9789811950957

Three-dimensional point clouds captured by sensors can quantify plant phenotype, which plays an important role in agricultural intelligence. Many scanned objects in agriculture and forestry are tall and obscured by leaves, so point clouds captured by either terrestrial or airborne methods may be incomplete. In order to obtain a more complete point cloud, this paper proposes a point cloud registration method based on the fast point feature histogram (FPFH), which aligns point clouds collected from different viewpoints. This method calculates the FPFH feature of each point and the Bhattacharyya distance between point pairs. Effective strategies pick out reliable sets of point pairs. Singular value decomposition is used to obtain the transformation relationship between point clouds. Experimental results show that the proposed method has high accuracy for plant point cloud registration in real scenes, and the root-mean-square error is smaller than that of common registration methods of SAC-IA and NDT. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forestry

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A Novel Motor Imagery EEG Classification Model Using Frequency-Temporal-Spatial Convolutional Neural Network with Channel Attention 12

A Novel Motor Imagery EEG Classification Model Using Frequen...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2022

作者： Liang, Hong-Jie Li, Ling-Long Cao, Guang-Zhong Chen, Jiang-Cheng College of Mechatronics and Control Engineering Shenzhen University Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen518060 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Motor imagery (MI) EEG classification is a crucial component for brain-computer interface (BCI) system, the quality of features extracted from EEG signals greatly affects the MI classification performance. Nevertheless, most researches caused information loss while performing EEG feature extraction. To extract multilevel recognizable EEG features and improve classification performance of MI tasks, this paper proposes a novel MI EEG classification model of frequency-temporal-spatial multi-layer CNN with channel attention. In this model, multiple convolution kernels with different size are used to extract features at relevant frequency bands, the squeeze-and-excitation block based channel attention mechanism is added to learn distinct frequency characteristics, then via layer-by-layer convolutional operation, EEG features from frequency-temporal-spatial can be excavated. The model can learn EEG features of three domain and classify MI tasks simultaneously. Finally, the proposed method is evaluated on two BCI datasets. For dataset BCI-C IV-2a, the average classification accuracy and kappa value are 89.14%, 0.85, respectively;for dataset BCI-C IV-2b, the average classification accuracy and kappa value are 89.19%, 0.78, respectively. Additionally, when comparing to other MI classification methods on the same EEG datasets, the classification performance is superior to state-of-the-art methods, the effectiveness and superiority of the proposed method is validated. © 2022 IEEE.

关键词： Brain computer interface

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Multiscale frictional behaviors of sp^(2) nanocrystallited carbon films with different ion irradiation densities

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Friction 2021年第5期9卷 1025-1037页

作者： Zelong HU Xue FAN Cheng CHEN Institute of Nanosurface Science and Engineering Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics EngineeringCollege of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China

sp^(2) nanocrystallited carbon films with large nanocrystallite sizes,smooth surfaces,and relative high hardness were prepared with different ion irradiation densities regulated with the substrate magnetic coil current in an electron cyclotron resonance plasma sputtering *** multiscale frictional behaviors were investigated with macro pin‐on‐disk tribo‐tests and micro nanoscratch *** results revealed that,at an ion irradiation density of 16 mA/cm^(2),sp^(2) nanocrystallited carbon film exhibits the lowest friction coefficient and good wear resistant properties at both the macroscale and *** film sliding against a Si_(3)N_(4) ball under a contact pressure of 0.57 GPa exhibited a low friction coefficient of 0.09 and a long wear life at the ***,the film sliding against a diamond tip under a contact pressure of 4.9 GPa exhibited a stable low friction coefficient of 0.08 with a shallow scratch depth at the *** is suggested that sp^(2) nanocrystallites affect the frictional behaviors in the cases described *** the macroscale,the contact interface via the small real contact area and the sp^(2) nanocrystallited transfer layer dominated the frictional behavior,while the sp^(2) nanocrystallited structure in the film with low shear strength and high plastic resistivity,as well as the smooth surface morphology,decided the steady low nanoscratch properties at the *** findings expand multiscale tribological applications of sp^(2) nanocrystallited carbon films.

关键词： macro‐tribology micro‐tribology sp^(2)nanocrystallite carbon film ion irradiation density

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A Novel Hand Gesture Recognition Method Using sEMG-Based PSODE-BPNN 12

A Novel Hand Gesture Recognition Method Using sEMG-Based PSO...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2022

作者： Li, Ling-Long Cao, Guang-Zhong Zhang, Yue-Peng Chen, Jiang-Cheng College of Mechatronics and Control Engineering Shenzhen University Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen518060 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aim to improve the deficiencies of slow convergence speed and prone to trapped into local minimum for back propagation neural network (BPNN) in sEMG-based hand gesture, a novel hand gesture recognition method associating particle swarm optimization (PSO) with differential evolution (DE) is proposed to optimize BPNN, namely PSODE-BPNN. Firstly, initial parameters of weights and biases are adjusted and updated to yield optimal values, via PSO and DE incorporation with the gradient descent method of BPNN. Secondly, the optimal values are utilized as the initial parameters to train the BPNN. Then the proposed method is evaluated on sEMG-based hand gesture dataset Ninapro DB4. The performance for the PSODE-BPNN is compared with the PSO-BPNN, the BPNN, and other related competing methods in literatures. The experimental results show that the PSODE-BPNN improves the inadequacy of slow convergence rate and local minimum of BPNN, and achieves higher gesture recognition accuracy than other comparison listed methods. The effectiveness and superiority of the proposed method is significantly validated. © 2022 IEEE.

关键词： Optimal systems

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