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Unconventional spin-orbit torques from sputtered MoTe2 films

Physical Review B 2024年第2期110卷 024426-024426页

作者： Shuchen Li Jonathan Gibbons Stasiu Chyczewski Zetai Liu Hsu-Chih Ni Jiangchao Qian Jian-Min Zuo Jun-Fei Zheng Wenjuan Zhu Axel Hoffmann Department of Materials Science and Engineering and Materials Research Laboratory Department of Physics Department of Electrical and Computer Engineering Danbury Connecticut 06810 USA

Materials with strong spin-orbit coupling and low crystalline symmetry are promising for generating large unconventional spin-orbit torques (SOTs), such as in-plane fieldlike (FL) torques and out-of-plane dampinglike (DL) torques, which can effectively manipulate and deterministically switch an out-of-plane magnetization without the need for additional external in-plane magnetic fields. Here, we report SOTs generated by magnetron-sputtered 1T′MoTe2/Permalloy (Py; Ni80Fe20)/MgO heterostructures using both spin-torque ferromagnetic resonance (ST-FMR) and second harmonic Hall measurements. We observed unconventional FL and DL torques in our samples due to spins polarized normal to the interface of MoTe2 and Py layers, and studied the influence of crystallographic order and MoTe2 layer thickness on the SOTs. By comparing the Raman spectra of 1T′MoTe2 samples prepared in different ways, we found a tensile strain in sputtered MoTe2 films, which might further enhance the generation of unconventional torques by reducing the symmetry of 1T′MoTe2.

关键词： Spin injection Spin-orbit torque Spintronics Ferromagnetic resonance Raman spectroscopy

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Ferrite Shielding for Eddy Current Suppression on Inductors and Transformers Using Ribbon-Based Magnetic Cores

Ferrite Shielding for Eddy Current Suppression on Inductors ...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Gao, Zihan Wang, Fred The University of Tennessee Knoxville Min H. Kao Department of Electrical Engineering and Computer Science KnoxvilleTN United States The University of Tennessee Min H. Kao Department of Electrical Engineering and Computer Science KnoxvilleTN United States Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350376067

Ribbon-based magnetic cores, such as nanocrystalline and amorphous cores, have been widely used in inductors and transformers in high power converters. However, unwanted eddy current can be found on the surfaces of the core laminations due to fringing effect and leakage magnetic field. In this paper, a ferrite shielding structure is proposed to create bypass loops for lamination layers to avoid the stray field crossing the lamination layers. The mechanism of the proposed shielding is demonstrated. Simulations and tests have proved the effectiveness for the gapped inductor, as well as core and shell-type transformers. © 2024 IEEE.

关键词： Magnetic leakage

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Efficient and accurate numerical-projection of electromagnetic multipoles for scattering objects

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Frontiers of Optoelectronics 2023年第4期16卷 215-226页

作者： Wenfei Guo Zizhe Cai Zhongfei Xiong Weijin Chen Yuntian Chen School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117576Singapore Wuhan National Laboratory of Optoelectronics Huazhong University of Science and TechnologyWuhan 430074China Optics Valley Laboratory Wuhan 430074China

In this paper,we develop an efcient and accurate procedure of electromagnetic multipole decomposition by using the Lebedev and Gaussian quadrature methods to perform the numerical ***,we briefy review the principles of multipole decomposition,highlighting two numerical projection methods including surface and volume ***,we discuss the Lebedev and Gaussian quadrature methods,provide a detailed recipe to select the quadrature points and the corresponding weighting factor,and illustrate the integration accuracy and numerical efciency(that is,with very few sampling points)using a unit sphere surface and regular *** the demonstrations of an isotropic dielectric nanosphere,a symmetric scatterer,and an anisotropic nanosphere,we perform multipole decomposition and validate our numerical projection *** obtained results from our procedure are all consistent with those from Mie theory,symmetry constraints,and fnite element simulations.

关键词： Multipole decomposition Numerical quadrature Light scattering

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Multimodal Pain Assessment Βased on Physiological Biosignals: The Impact of Demographic Factors on Perception and Sensitivity 11

Multimodal Pain Assessment Βased on Physiological Biosignal...

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11th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Pavlidou, Elisavet Tsiknakis, Manolis Department of Electrical and Computer Engineering Hellenic Mediterranean University Estavromenos Heraklion71410 Greece Computational BioMedicine Laboratory Institute of Computer Science Foundation for Research & Technology-Hellas Vassilika Vouton Heraklion70013 Greece

ISBN: (纸本)9789897587436

Pain is a multidimensional and highly personalized sensation that affects individuals’ physical and emotional state. Visual analog scales, numeric rate indicators, and various questionnaires, all relying on patient-reported outcome measurements, are considered the "gold" standard methods for assessing the severity of pain. Nevertheless, self-report tools require cognitive, linguistic, and social abilities, which may manifest variations in certain populations such as neonates, individuals with intellectual disabilities, and those affected by dementia. The purpose of this study is to automate the process through multimodal physiological-data-driven machine-learning models in order to gain deeper insights into pain sensation. We developed a pipeline using electrocardiogram (ECG), galvanic skin response (GSR), and electromyogram (EMG), along with demographic information from the BioVid dataset. The Pan & Tompkins algorithm was applied for ECG signal processing, while statistical analysis was used for feature extraction across all signals. Our study achieved 82.83% accuracy in the SVM classification task of baseline (BL) vs the highest level of pain (PA4) for females aged 20-35. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Sensory perception

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Robust Synergetic Observer based Fault-Tolerant Control for Electric Vehicle Applications 50

Robust Synergetic Observer based Fault-Tolerant Control for ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Boumegouas, Mohammed Kabir Billa Kouzi, Katia Trabelsi, Mohamed Iqbal, Atif Birame, Mhamed Shadmand, Mohammad B. Laboratory of Semiconductors and Functional Materials Amar Telidji University of Laghouat Algeria Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait Department of Electrical Engineering Qatar University Doha Qatar Department of Electrical & Computer Engineering University of Illinois ChicagoIL United States

ISBN: (纸本)9781665464543

Speed sensor faults are very common in electric vehicle (EV) applications, often disrupting system performance due to the reliance on speed sensor data by the electric drives. Consequently, fault-tolerant control approaches require robust observer structures capable of functioning effectively during faults, swiftly identifying and reconfiguring failures. Thus, this paper presents a novel fault-tolerant control design leveraging a synergetic observer (SO) to substitute the speed sensor in the event of fault. Comparative analysis with a super-twisting sliding mode observer (ST-SMO) highlights the proposed observer's superior performance in terms of tracking accuracy and ripple reduction. The presented simulation results demonstrate promising performance of the proposed observer for fault-tolerant control in EV applications. © 2024 IEEE.

关键词： Permanent magnets

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An Immutable Framework for Smart Healthcare Using Blockchain Technology

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computer Systems science & engineering 2023年第7期46卷 165-179页

作者： Faneela Muazzam A.Khan Suliman A.Alsuhibany Walid El-Shafai Mujeeb Ur Rehman Jawad Ahmad Department of Computer Science Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia James Watt School of Engineering University of GlasgowG128QQUK School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

The advancements in sensing technologies,information processing,and communication schemes have revolutionized the healthcare *** Healthcare Records(EHR)facilitate the patients,doctors,hospitals,and other stakeholders to maintain valuable data and medical *** traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks.A single attempt of a successful Denial of Service(DoS)attack can compromise the complete healthcare *** article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things(IoMT)to address the stated *** proposed architecture is on the idea of a lightweight private blockchain-based network that facilitates the users and hospitals to perform multiple healthcare-related operations in a secure and trustworthy *** efficacy of the proposed framework is evaluated in the context of service execution time and *** experimental outcomes indicate that the proposed design attained lower service execution time and higher throughput under different control parameters.

关键词： Blockchain technology healthcare applications cybersecurity services IoMT DoS EHR

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A Surrogate-Assisted Evolutionary Algorithm for Expensive Dynamic Multimodal Optimzation 13

A Surrogate-Assisted Evolutionary Algorithm for Expensive Dy...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Wu, Xunfeng Liu, Songbai Ji, Junkai Ma, Lijia Leung, Victor C. M. Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China The University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9798350308365

Surrogate-assisted evolutionary algorithms (SAEAs) have demonstrated promising optimization performance in addressing expensive dynamic optimization problems or expensive multimodal optimization problems. However, none of existing SAEAs are designed specifically for tackling expensive dynamic multimodal optimization problems (EDMMOPs). Therefore, in this paper, a first SAEA for tackling EDMMOPs is proposed. First, a nearest density clustering is designed to divide the population into a number of subpopulations, enhancing the diversity of the population. Then, a surrogate-assisted evolutionary optimizer is developed to construct surrogate models for each subpopulation and evolve all solutions in subpopulations by means of the built surrogate models, accelerating the population's converge towards several optimal solutions rapidly. Finally, a transfer learning-based prediction is devised to generate initial samples for next environment by leveraging the stored training samples in the previous environments. To assess the performance of our proposed algorithm, a set of complex benchmark problems is adopted, and the experimental results confirm its superior performance over several competitive algorithms on most test cases. © 2024 IEEE.

关键词： Digital elevation model

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Predictive modeling of MXene-based solar absorbers using a deep neural network

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Journal of the Optical Society of America B: Optical Physics 2025年第4期42卷 763-772页

作者： Waseer, Waleed Iqbal Baqir, Muhammad Abuzar Saqlain, Muhammad Mughal, Muhammad Junaid Khan, Shujaat School of Physics State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of China Chengdu China Department of Electrical Engineering COMSATS University Islamabad Sahiwal57000 Pakistan Department of Electrical and Computer Engineering COMSATS University Islamabad Islamabad45550 Pakistan Department of Computer Engineering College of Computing and Mathematics King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia SDAIA-KFUPM Joint Research Center for Artificial Intelligence King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia

Nanophotonic structures, such as photonic crystals, plasmonic nanostructures, and metamaterials, present transformative potential in advancing optical devices through innovative design capabilities. Among these, metamaterials—specifically metal–insulator–metal (MIM)-based absorbers—stand out for their ability to achieve high electromagnetic wave absorption across designated frequencies, proving valuable in applications ranging from solar cells to sensors. This study focuses on designing a high-efficiency MXene–SiO2–silver MIM metasurface absorber, leveraging deep learning techniques to streamline and enhance the simulation process traditionally reliant on finite-difference time-domain (FDTD) or finite-element methods (FEMs). By utilizing a deformable convolutional neural network (CNN), the proposed model predicts absorption spectra from metasurface geometries with superior accuracy and reduced computational demand while achieving dynamic spatial transformation handling. The model’s accuracy is further elucidated through Gradient-weighted Class Activation Mapping (Grad-CAM), which provides insights into the absorber’s most influential regions, supporting targeted optimization for specific applications. This deep learning approach demonstrates significant advantages over conventional methods in efficiency and adaptability, advancing the development of high-performance nanophotonic devices. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Time domain analysis

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Approximating parameters of photovoltaic models using an amended reptile search algorithm

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Journal of Ambient Intelligence and Humanized Computing 2023年第7期14卷 9073-9088页

作者： Chauhan, Sumika Vashishtha, Govind Kumar, Anil Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology Longowal148 106 India Precision Metrology Laboratory Department of Mechanical Engineering Sant Longowal Institute of Engineering and Technology Longowal148 106 India College of Mechanical and Electrical Engineering Wenzhou University Wenzhou325 035 China Department of Computer Science and Engineering National Institute of Technology Delhi New Delhi110036 India

The appropriate selection of parameters of photovoltaic models is necessary for an accurate evaluation, control, and optimization of photovoltaic systems. Even though various strategies have been developed to address this issue, but, a precise and reliable scheme for identifying the model parameters remains a challenge. To improve parameter identification of different photovoltaic models, an opposition-based learning reptile search algorithm with Cauchy mutation strategy (OBL-RSACM) is introduced in this research. In OBL-RSACM, the individuals in search space get doubled by generating their opposite guess of the solution which overcomes the issue of strucking of solution in local minima and also enhances the convergence speed. Cauchy mutation strategy is also incorporated in the basic reptile search algorithm (RSA) which enhances the search mechanism, modifies the control parameter, mutation-driven scheme, and greedy approach of selection during the search process of the RSA. Thus, improves the exploration process and maintains the proper balance between exploration and exploitation. The proposed OBL-RSACM is applied to estimate the parameters of different photovoltaic models, i.e., single diode, double diode, and photovoltaic module. A comprehensive comparison of experimental results and analysis demonstrated that OBL-RSACM outperformed other state-of-the-art algorithms in terms of accuracy, reliability, and computational efficacy. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Learning algorithms

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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