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Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Lizhu Ren Chenghang Zhou Liang Liu Jingsheng Chen Kie Leong Teo Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Materials Science and Engineering National University of Singapore Singapore School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350338362

ISBN: (纸本)9798350338379

electrically manipulating magnetic moment by spin-orbit torque (SOT) has great potential applications in magnetic memories and logic devices. Although there have been rich SOT studies on magnetic heterostructures, low interfacial thermal stability and high switching current density still remain an issue. Here, highly textured, polycrystalline Heusler alloy $\text{Mn}_{\mathrm{x}}\text{Pt}_{\mathrm{y}}\text{Ge}$ (MPG) films with various thicknesses are directly deposited on thermally oxidized silicon wafers. The perpendicular magnetization of the MPG single layer can be reversibly switched by electrical current pulses with a magnitude as low as $4.1\times 10^{10}\text{Am}^{-2}$ , as evidenced by both the electrical transport and the magnetic optical measurements. The switching is shown to arise from inversion symmetry breaking due to the vertical composition gradient of the films after sample annealing. The SOT effective fields of the samples are analysed systematically. It is found that the SOT efficiency increases with the film thickness, suggesting a robust bulk-like behaviour in the single magnetic layer. Moreover, a memristive characteristic has been observed due to multi-domain switching property in the single layer MPG device. This work proves that the MPG is a good candidate to be utilized in high-density and efficient MRAM devices and other novel spintronics.

关键词： Magnetic films Torque Optical switches Magnetization Metals Stability analysis Perpendicular magnetic anisotropy

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Development of a dual-spectroscopic system to rapidly measure diisopropyl methyl phosphonate (DIMP) decomposition and temperature in a reactive powder environment

arXiv

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arXiv 2024年

作者： Borah, Preetom Alemohammad, Milad Foster, Mark Weihs, Timothy P. Department of Materials Science and Engineering Johns Hopkins University BaltimoreMD21218 United States Hopkins Extreme Materials Institute Johns Hopkins University BaltimoreMD21218 United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD21218 United States

The development of systems to measure and optimize emerging energetic material performance is critical for Chemical Warfare Agent (CWA) defeat. In order to assess composite metal powder efficacy on CWA simulant defeat, this study documents a combination of two spectroscopic systems designed to monitor the decomposition of a CWA simulant and temperature rises due to combusting metal powders simultaneously. The first system is a custom benchtop Polygonal Rotating Mirror Infrared Spectrometer (PRiMIRS) incorporating a fully customizable sample cell to observe the decomposition of Diisopropyl Methyl Phosphonate (DIMP) as it interacts with combusting composite metal particles. The second is a tunable diode laser absorption spectroscopy (TDLAS) used to monitor increases in background gas temperatures as the composite metal powders combust. The PRiMIRS system demonstrates a very high signal to noise ratio (SNR) at slow timescales (Hz), reasonable SNR when operating at faster timescales (100 Hz), and capabilities of resolving spectral features with a FWHM resolution of 15 cm−1. TDLAS was able to monitor temperature rises between room temperature and 230 ± 5C while operating at 100 Hz. For testing, liquid DIMP was inserted in a preheated stainless steel (SS) cell to generate DIMP vapor and (Al–8Mg):Zr metal powders were ignited in a SS mount with a resistively heated nichrome wire at one end of the cell. The ignited particles propagated across the cell containing DIMP vapor. The path averaged gas temperature in the preheated SS cell rises rapidly (100 ms) and decays slowly ( © 2024, CC BY.

关键词： Zirconium compounds

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Deep learning-based channel estimation for RIS-assisted UAV-enabled wireless communications system

Deep learning-based channel estimation for RIS-assisted UAV-...

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International Conference on Innovation, Communication and engineering (ICICE 2023)

作者： Belayneh A Tesfaw Hsin-piao Lin Getaneh B Tarekegn Rong-Terng Juang Shiann-Shiun Jeng Department of International Graduate Program in Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Institute of Aerospace and System Engineering National Taipei University of Technology Taipei 10608 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu 30010 Taiwan Department of Electrical Engineering National Dong Hwa University Hualien Taiwan

ISBN: (数字)9781839539954

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. This problem can be effectively addressed by employing reconfigurable intelligent surfaces (RIS). To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communications system. Simulation results showed that LSTM can effectively improve the channel estimation performance of RIS-assisted UAV-enabled wireless communications.

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Shubnikov-de Haas oscillations in coherently strained AlN/GaN/AlN quantum wells on bulk AlN substrates

arXiv

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arXiv 2025年

作者： Chen, Yu-Hsin Encomendero, Jimy Xing, Huili Grace Jena, Debdeep Department of Materials Science and Engineering Cornell University IthacaNY14853 United States School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States Kavli Institute Cornell for Nanoscale Science Cornell University IthacaNY14853 United States

We report the observation of Shubnikov-de Haas (SdH) oscillations in coherently strained, low-dislocation AlN/GaN/AlN quantum wells (QWs), including both undoped and δ-doped structures. SdH measurements reveal a single subband occupation in the undoped GaN QW and two subband occupation in the δ-doped GaN QW. More importantly, SdH oscillations enable direct measurement of critical two-dimensional electron gas (2DEG) parameters at the Fermi level: carrier density and ground state energy level, electron effective mass (m∗ ≈ 0.289 me for undoped GaN QW and m∗ ≈ 0.298 me for δ-doped GaN QW), and quantum scattering time (τq ≈ 83.4 fs for undoped GaN QW and τq ≈ 130.6 fs for δ-doped GaN QW). These findings provide important insights into the fundamental properties of 2DEGs that are strongly quantum confined in the thin GaN QWs, essential for designing nitride heterostructures for high-performance electronic applications. © 2025, CC BY-NC-ND.

关键词： Gallium nitride

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Controllable Multi-Level Switching of Optical Phase Change materials via Microheater Temperature Profile engineering

Controllable Multi-Level Switching of Optical Phase Change M...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Hongyi Sun Chuanyu Lian Francis Vásquez-Aza Yi-Siou Huang Steven A. Vitale Ichiro Takeuchi Juejun Hu Nathan Youngblood Georges Pavlidis Carlos A. Ríos Ocampo Department-of Materials Science & Engineering University of Maryland College Park MD USA Institute for Research in Electronics and Applied Physics University of Maryland College Park MD USA Department of Mechanical Engineering University of Connecticut Storrs CT USA Advanced Materials and Microsystems Group MIT Lincoln Laboratory Lexington MA USA Department of Physics Quantum Materials Center University of Maryland College Park MD USA Department of Materials Science & Engineering MIT Cambridge MA USA Electrical & Computer Engineering Department The University of Pittsburgh Pittsburgh PA USA

We demonstrate doped-silicon-on-insulator microheaters with triangle-like temperature profiles. Such devices control the hotspot size and temperature and, thus, the area that undergoes amorphization or crystallization... 详细信息

ISBN: (纸本)9798350369311

关键词： Phase change materials Temperature Optical switches Optical device fabrication Control systems Metasurfaces Optical materials Tuning Optical pulses Switching circuits

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Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics

arXiv

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arXiv 2023年

作者： Murali, Nihal Puli, Aahlad Yu, Ke Ranganath, Rajesh Batmanghelich, Kayhan Intelligent Systems Program University of Pittsburgh United States Department of Computer Science New York University United States Department of Electrical and Computer Engineering Boston University United States

Deep Neural Networks (DNNs) are prone to learning spurious features that correlate with the label during training but are irrelevant to the learning problem. This hurts model generalization and poses problems when deploying them in safety-critical applications. This paper aims to better understand the effects of spurious features through the lens of the learning dynamics of the internal neurons during the training process. We make the following observations: (1) While previous works highlight the harmful effects of spurious features on the generalization ability of DNNs, we emphasize that not all spurious features are harmful. Spurious features can be "benign" or "harmful" depending on whether they are "harder" or "easier" to learn than the core features for a given model. This definition is model and dataset dependent. (2) We build upon this premise and use instance difficulty methods (like Prediction Depth (Baldock et al., 2021)) to quantify "easiness" for a given model and to identify this behavior during the training phase. (3) We empirically show that the harmful spurious features can be detected by observing the learning dynamics of the DNN’s early layers. In other words, easy features learned by the initial layers of a DNN early during the training can (potentially) hurt model generalization. We verify our claims on medical and vision datasets, both simulated and real, and justify the empirical success of our hypothesis by showing the theoretical connections between Prediction Depth and information-theoretic concepts like V-usable information (Ethayarajh et al., 2021). Lastly, our experiments show that monitoring only accuracy during training (as is common in machine learning pipelines) is insufficient to detect spurious features. We, therefore, highlight the need for monitoring early training dynamics using suitable instance difficulty metrics. © 2023, CC BY.

关键词： Deep neural networks

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A Pseudo-CMOS Bootstrap DIGOTA in a 600nm Flexible IGZO Technology

A Pseudo-CMOS Bootstrap DIGOTA in a 600nm Flexible IGZO Tech...

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International Flexible Electronics Technology Conference (IFETC)

作者： Diogo Sousa João Marcelino Angelo Santos Hugo Viana João Xavier Pedro Barquinha Pedro Toledo Paolo Crovetti Department of Materials Science Nova School of Science and Technology Lisbon Portugal Department of Electrical and Computer Engineering Nova School of Science and Technology Lisbon Portugal Synopsis Lisbon Portugal Dipartimento di Elettronica Politecnico di Torino Turin Italy

ISBN: (数字)9798331529468

ISBN: (纸本)9798331529475

A bstract- The design of a Digital-Based Operational Transconductance Amplifier (DIGOTA) featuring pseudo-CM OS bootstrap inverters integrated is a 600 nm Indium-Gallium-Zinc-Oxide (IGZO) Thin-Film Transistors (TFT) Flexible Integrated Circuits (FlexICs) technology is presented in this paper. Based on post-layout simulations, the proposed DIGOTA operates at 3 V power supply and achieves a DC gain of 33.8 dB and a GBW of 64.9 kHz at 22111W power. Despite maintaining performance comparable to the previous Flexible DIGOTA, this new design occupies 26% less area, requires less logical gates, and enhances the slew rate whilst maintaining reasonable energy efficiency and large signal figures of merit of 14.5 ***/mW and 50.2 ***/***, respectively.

关键词： Power supplies Simulation Logic gates Inverters Thin film transistors Topology Transistors Integrated circuit modeling Transconductance Gain

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Design of high-entropy films as ultra-violet light reflector

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Applied materials Today 2024年 36卷

作者： Yeh, Cheng-Hsien You, Hau-Shiang Chang, Yuan-Chun Kuan, Chen-Yun Wu, Hsuan-Ta Hsu, Wen-Dung Shih, Chuan-Feng Department of Electrical Engineering National Cheng Kung University Tainan70101 Taiwan Department of Materials Science and Engineering National Cheng Kung University Tainan70101 Taiwan Department and Institute of Electrical Engineering Minghsin University of Science and Technology Hsinchu30401 Taiwan Program on Semiconductor Packaging and Testing Academy of Innovative semiconductor and Sustainable Manufacture National Cheng Kung University Tainan70101 Taiwan Center National Cheng Kung University Tainan70101 Taiwan

This study proposes the design and implementation of high-entropy alloy (HEA) thin films as materials for the reflector of deep ultraviolet light-emitting devices and marks the first application of HEA in optical field. In the material design phase, an Al-Co-Zn-Ni alloy is designed by considering the reflectivity, phase stability and binary formation energy. Reverse Monte Carlo calculation is employed to establish stable atomic structure. Frequency-dependent dielectric equations are derived from first principles calculations, with dielectric constants incorporating contributions from ions and electrons and combining classical Drude and Lorentz models. The dielectric equations yield optical constants that are used to calculate the reflectance. In the experimental phase, we systematically vary the aluminum content and prepare Al-Co-Zn-Ni thin films ranging from pure aluminum to equimolar compositions. In the deep ultraviolet region, the reflectance of thermally treated Al65Zn12Co12Ni11 and Al50Zn16Co17Ni17 thin films is found superior to that of gold by three times. Structural and crystalline changes with varying aluminum content are found, as well as intriguing phase separation and superlattice formation that persist until equimolar compositions. This unique nanoscale structural variation causes the Young's modulus and hardness of Al-Co-Zn-Ni thin films to initially increase and then decrease with decreasing aluminum content. There is a significant increase in the corrosion potential difference when reducing Al contents in Al-Co-Zn-Ni, indicating improved passivation effects as the equimolar composition is approached. By modulating the aluminum content, the nanoscale structure of Al-Co-Zn-Ni can be adjusted, thereby improving its optical, mechanical, corrosion resistance, and thermal stability properties. This demonstrates the high versatility of this material for practical optical applications. © 2023

关键词： Zinc alloys

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An Empirical Generation Technique on Background Music Using Gated Recurrent Neural Networks

An Empirical Generation Technique on Background Music Using ...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Varinya Phanichraksaphong Wei-Ho Tsai International Graduate Program of Electrical Engineering and Computer Science (IEECS) National Taipei University of Technology Taipei Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan

The implementation of Gated Recurrent Neural Networks (GRU) to generate background music (BGM) combines deep learning technology with music that is used for the visual content of a commercial or educational. Indeed, this BGM is necessary to enhance the intended message expressed to the other audience. This work aimed to provide the model network of GRU which is based on RNN to generate multi-label genres of music by using the open source of GTZAN to evaluate the new BGM. Our GRU networks can solve the vanishing gradient problem by utilizing both the reset gate and the update gate on the network. In the results, we achieved a new BGM that synchronized with the human mood which made more variety of sounds.

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Special Issue on Advanced materials and Sensing Technologies on IoT Applications: Part 4-3 Preface

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Sensors and materials 2022年第7期34卷

作者： Meen, Teen-Hang Zhao, Wenbing Yang, Cheng-Fu Department of Electronic Engineering National Formosa University Taiwan Department of Electrical Engineering and Computer Science Cleveland State University United States Department of Chemical and Materials Engineering National University of Kaohsiung Taiwan

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