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2022 Compound Semiconductor Week, CSW 2022

作者： Reddy, Pramod Loveless, James Quinones-Garcia, Cristyan Khachariya, Dolar Kirste, Ronny Pavlidis, Spyridon Mecouch, Will Mita, Seiji Moody, Baxter Tweedie, James Kohn, Erhard Collazo, Ramon Sitar, Zlatko Adroit Materials CaryNC27518 United States North Carolina State University Department of Materials Science and Engineering RaleighNC27695 United States North Carolina State University Department of Electrical and Computer Engineering RaleighNC27695-7919 United States

ISBN: (数字)9781665453400

ISBN: (纸本)9781665453400

In this work, we report on recent advances in UVC emitters and detectors based on AlGaN on single crystal AlN substrates. We perform point defect management via chemical potential control and extended defect management via growth on low threading dislocation density single crystal AlN substrates and demonstrate reliable UVC LEDs at high power densities (>40 Wcm-2) on transparent AlN substrates and high gain (>300000) solar blind avalanche photodiodes with high quantum efficiency (>70%) and near ideal breakdown fields. We also report a comparison with devices on foreign substrates (sapphire) with those on native AlN substrates revealing a general improvement in performance by orders of magnitude. © 2022 IEEE.

关键词： Aluminum gallium nitride

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Numerical Investigation of Optimal Buffer Layer and Performance Evaluation on CdTe Solar Cell

arXiv

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arXiv 2024年

作者： Ahamed, Tanzir Rahman, Arifa Rahaman, Imteaz Mamun, Ashraful Shiam, Istiaq Firoz Bappy, Md. Mehedi Hasan Ahammed, Tanvir Karmakar, Srabani Parash, Hasibul Hasan Ghosh, Sampad Department of Electrical and Electronic Engineering CCN University of Science and Technology Cumilla3503 Bangladesh Department of Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram4349 Bangladesh Department of Electrical and Computer Engineering University of Utah Salt Lake CityUT84112 United States Department of Electrical Engineering Texas State University San MarcosTX78666 United States Department of Materials Science and Engineering University of Rajshahi Rajshahi6205 Bangladesh Department of Materials Science and Engineering University of Utah Salt Lake CityUT84112 United States Department of Electrical and Electronic Engineering Rajshahi University of Engineering and Technology Rajshahi6204 Bangladesh

This study investigates the critical role of buffer layers in enhancing the efficiency of thin-film CdTe solar cells. We explore non-toxic buffer materials, specifically ZnSe, ZnMgO, 3C-SiC, and WS2, as potential replacements for the traditional Cd-based CdS buffer layer. Our analysis includes a thorough evaluation of the electrical and optical performance of these buffer materials in conjunction with CdTe absorbers. We optimize the thickness of both the buffer and absorber layers to achieve the best performance. Additionally, we examine the impact of defect density variations in the buffer materials and their corresponding temperature effects. Among the tested materials, ZnSe and ZnMgO demonstrate the highest potential, achieving power conversion efficiencies of 20.74% and 20.73%, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： II-VI semiconductors

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Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset

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Intelligent Automation & Soft Computing 2023年第3期35卷 2821-2835页

作者： Riaz Muhammad Ahmed Ali M.Abid Anwar Toufique Ahmed Soomro Omar AlShorman Adel Alshahrani Mahmoud Masadeh Ghulam Md Ashraf Naif H.Ali Muhammad Irfan Athanasios Alexiou Department of Electrical Engineering Sukkur IBA University65200SukkurPakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience and TechnologyLarkana77150Pakistan Faculty of Engineering and AlShrouk Trading Company Najran UniversityNajran61441Saudi Arabia Department of Medical Rehabilitation Sciences-Physiotherapy Program College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Computer Engineering Department Yarmouk UniversityIrbid21163Jordan Pre-Clinical Research Unit King Fahd Medical Research CenterKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Internal Medicine Medical CollegeNajran UniversityNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Novel Global Community Educational Foundation HebershamNSW 2770AustraliaAFNP Med AustriaWien2770Austria

Electroencephalogram(EEG)is a method of capturing the electrophy-siological signal of the *** EEG headset is a wearable device that records electrophysiological data from the *** paper presents the design and fab-rication of a customized low-cost Electroencephalogram(EEG)headset based on the open-source OpenBCI Ultracortex Mark IV *** electrode placement locations are modiﬁed under a 10–20 standard *** fabricated headset is then compared to commercially available headsets based on the following para-meters:affordability,accessibility,noise,signal quality,and ***,the data is recorded from 20 subjects who used the EEG Headset,and signals were ***,the participants marked the accuracy,set up time,participant comfort,and participant perceived ease of set-up on a scale of 1 to 7(7 being excellent).Thirdly,the self-designed EEG headband is used by 5 participants for slide *** raw EEG signal is decomposed into a series of band sig-nals using discrete wavelet transform(DWT).Lastly,theseﬁndings have been compared to previously reported *** concluded that when used for slide-changing control,our self-designed EEG headband had an accuracy of 82.0 *** also concluded from the results that our headset performed well on the cost-effectiveness scale,had a reduced setup time of 2±0.5 min(the short-est among all being compared),and demonstrated greater ease of use.

关键词： Brain-computer interface EEG consumer-grade accessibility headset

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Radiation Anomaly Detection Using an Adversarial Autoencoder

Radiation Anomaly Detection Using an Adversarial Autoencoder

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Asilomar Conference on Signals, Systems & computers

作者： Charles Sayre Eric C. Larson Gabs DiLiegro Joseph Camp Bruce Gnade Department of Computer Science Southern Methodist University Dallas Texas Department of Electrical and Computer Engineering Southern Methodist University Dallas Texas Department of Materials Science and Engineering Univertsity of Texas Dallas Texas

Scintillators are the primary devices used for radiation detection., especially at national borders and other ports of entry. Reducing the size of these detectors for placement on mobile devices such as drones can allow for better detection and localization of radiation sources. Detection of radiation with supervised machine learning can be a challenge when looking for previously unobserved radiation sources. Therefore, anomaly detection methods are investigated. In this work we employ adversarial autoencoders trained to classify spectra from radioactive sources as either background or anomalous. This allows the model to detect anomalies regardless of radiation source and outperform supervised methods on newly encountered sources.

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Near-half-metallic state in the half-Heusler PtMnSb film on a III-V substrate

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Physical Review materials 2025年第4期9卷 044403-044403页

作者： Shinichi Nishihaya Malcolm J. A. Jardine Hadass S. Inbar Aranya Goswami Jason T. Dong Aaron N. Engel Yu-Hao Chang Connor P. Dempsey Makoto Hashimoto Department of Electrical and Computer Engineering University of California Santa Barbara Santa Barbara California 93106 USA Present Address: Department of Physics Institute of Science Tokyo Tokyo 152-8551 Japan. Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 USA Materials Department University of California Santa Barbara Santa Barbara California 93106 USA Present Address: Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA. Stanford Synchrotron Radiation Lightsource SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park California 94025 USA

The interplay between half-metallic ferromagnetism and spin-orbit coupling within the inversion-symmetry-broken structure of half-Heuslers provides an ideal platform for various spintronics functionalities. Taking advantage of good lattice matching, it is highly desired to epitaxially integrate promising Heuslers into III-V semiconductor-based devices. PtMnSb is one of the first half-Heuslers predicted to be an above-room-temperature half-metal with large spin orbit coupling, however, its half-metallicity and potential as a spintronics material has remained elusive due to lack of high quality samples. Here we demonstrate epitaxial growth of single crystal PtMnSb(001) film on GaSb(001) substrates using molecular beam epitaxy. Direct observation of the band structure via angle-resolved photoemission spectroscopy and many-body perturbation theory within the quasi-particle self-consistent GW approximation (QPGW) reveals that PtMnSb hosts rather a near-half-metallic state with both spin bands crossing the Fermi level and with high spin polarization over 90%. Temperature dependence of magnetization also shows an anomalous enhancement below 60 K, which can be associated with the development of such a near-half-metallic state at low temperatures. Epitaxial growth of high-crystalline PtMnSb on a III-V paves the way for systematic clarification of its spin transport properties with fine-tuning of strain in heterostructure devices.

关键词： Molecular beam epitaxy

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Perovskite Nickelate Thin Film Devices as Adaptive Weights for Photonic Computing Networks

Perovskite Nickelate Thin Film Devices as Adaptive Weights f...

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Tae Joon Park Mohamad Hossein Idjadi Farshid Ashtiani Chenghao Wan Mikhail A. Kats Shriram Ramanathan School of Materials Engineering Purdue University West Lafayette IN USA Nokia Bell Labs Murray Hill NJ USA Department of Electrical and Computer Engineering University of Wisconsin-Madison Madison Wisconsin USA Department of Materials Science and Engineering University of Wisconsin-Madison Madison Wisconsin USA Department of Electrical and Computer Engineering Rutgers The State University of New Jersey Piscataway NJ USA

Atomic layer deposition (ALD) and sputtering of strongly correlated perovskite nickelate thin films are emerging fields for wafer-scale demonstration of quantum technologies. Functional properties of such oxide quantu... 详细信息

ISBN: (纸本)9798350369311

关键词： Adaptive systems Atomic layer deposition Thin film devices Quantum materials Perovskites Sputtering Electro-optical waveguides Photonics

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Observation of double hysteresis in CoFe2O4/MnFe2O4 core/shell nanoparticles and its contribution to AC heat induction

arXiv

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arXiv 2025年

作者： Wang, Jie Kim, Hyungsub Kim, Ji-Wook Seo, HyeongJoo Ota, Satoshi You, Chun-Yeol Takemura, Yasushi Bae, Seongtae Department of Electrical Engineering University of South Carolina ColumbiaSC29208 United States Department of Emerging Materials Science Daegu Gyeongbuk Institute of Science & Technology Daegu42988 Korea Republic of Department of Electrical and Electronic Engineering Shizuoka University Hamamatsu432-8561 Japan Department of Electrical and Computer Engineering Yokohama National University Yokohama240-8501 Japan

Magnetic core/shell nanoparticles are promising candidates for magnetic hyperthermia due to its high AC magnetic heat induction (specific loss power (SLP)). It’s widely accepted that magnetic exchange-coupling between core and shell plays the crucial role in enhancing SLP of magnetic core/shell nanoparticles. However, the physical contribution of exchange coupling to SLP has not been systematically investigated, and the underlying mechanism remains unclear. In this study, magnetic hard/soft CoFe2O4/MnFe2O4 and inverted soft/hard MnFe2O4/CoFe2O4 core/shell nanoparticles were synthesized, systematically varying the number of shell layers, to investigate the physical contribution of internal bias coupling at the core/shell interface to AC heat induction (SLP). Our results show that a unique magnetic property, double-hysteresis loop, was present and clearly observed, which was never reported in previous core/shell research literature. According to the experimentally and theoretically analyzed results, the double-hysteresis behavior in core/shell nanoparticles was caused by the difference of magnetic anisotropy between core and shell materials, separated by a non-magnetic interface. The enhanced SLP and and maximum temperature rise (TAC,max) of core/shell nanoparticles are attributed to the optimized magnetic anositropy, AC magnetic softness and double hysteresis behavior due to the internal bias coupling. These results demonstrate that the rational design capabilities to separately control the magnetic anisotropy, AC/DC magnetic properties by varying the volume ration between core and shell and by switching hard or soft phase materials between core and shell are effective modalities to enhance the AC heat induction of core/shell nanoparticles for magnetic nanoparticle hyperthermia. Copyright © 2025, The Authors. All rights reserved.

关键词： Magnetic anisotropy

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Stretchable Textile Bands for Ambulatory Electrocardiogram and Oximetry

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2022年第4期1卷 214-222页

作者： Liu, Jiaxi Le, Thy Sadatian, Ellie Yao, Lulu Garudadri, Harinath Dunphy, Stephen A. McClung, Christian Ng, Tse Nga University of California at San Diego Department of Electrical and Computer Engineering La Jolla CA92093 United States University of California at San Diego Materials Science and Engineering Program La Jolla CA92093 United States Qualcomm Institute University of California at San Diego La Jolla CA92093 United States Cb Innovations Llc Rancho Santa FeCA92067 United States

This work presents a vital sign monitoring interface combining electrocardiogram (ECG) and reflective photoplethysmography (PPG) acquisition on stretchable kinesiology tapes (KTs). The integrated textile bands are less prone to electrode misplacement and deliver high-quality diagnostic ECG signals with dry electrodes. The reflective PPG measured over the subclavian artery is used to track blood oxygen saturation, and in combination with ECG, enables the determination of pulse transit time and inference of blood pressure. This multimodal interface improves clinical workflows because it is easy to don, reduces motion artifacts, and facilitates more efficient and accurate diagnosis in emergency settings. © 2022 IEEE.

关键词： Electrocardiograms

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Utilizing Machine Learning Algorithms in Conjunction with Terahertz Spectra for Enhanced Plastic Sorting Efficiency

Utilizing Machine Learning Algorithms in Conjunction with Te...

引用

International Conference on Infrared and Millimeter Waves

作者： Nan Zhang Lim Zi Xi Josie Phua Wei Ji Anor Technologies Pte Ltd Singapore Institute of Materials Research and Engineering Agency for Science Technology and Research Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798350370324

ISBN: (纸本)9798350370331

The imperative of addressing climate change is clear, compounded by inadequate waste management intensifying plastic pollution. Challenges in waste management, such as manual sorting and recycling contamination, contribute to ongoing plastic accumulation. To surmount these hurdles, advanced technologies like terahertz (THz) technology integrated with machine learning algorithms such as Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA), and Support Vector Machine (SVM) are being investigated. This integration demonstrates considerable potential in improving plastic separation and sorting processes, achieving an impressive accuracy of 100%. Such advancements represent a significant stride towards more effective and sustainable solutions in combating plastic pollution and revolutionizing waste management practices.

关键词： Waste management Support vector machines Machine learning algorithms Manuals Recycling Linear discriminant analysis Contamination Sorting Principal component analysis Plastic waste

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Deep Reinforcement Learning-Based LSTM Model for Traffic Flow Forecasting in Internet of Vehicles

Deep Reinforcement Learning-Based LSTM Model for Traffic Flo...

引用

Chinese Intelligent Automation Conference, CIAC 2021

作者： Chen, Zekuan Luo, Xiong Wang, Ting Wang, Weiping Zhao, Wenbing School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China Shunde Graduate School University of Science and Technology Beijing Foshan528399 China Department of Electrical Engineering and Computer Science Cleveland State University ClevelandOH44115 United States

ISBN: (纸本)9789811663710

Nowadays many large cities often suffer from road congestion. Then, it is necessary to improve the working efficiency of urban road network with the help of computational intelligence technologies, within the Internet of vehicles (IoV) environment. We are committed to designing traffic flow prediction methods through the use of machine learning models. In this paper, we predict the traffic flow and traffic situation of the selected road segment. Specifically, we propose a deep reinforcement learning (DRL)-based long short-term memory (LSTM) model to predict the traffic flow. On the basis of it, we characterize the traffic situation with fuzzy comprehensive evaluation (FCE)-based model. The experimental results show that the constructed DRL-based LSTM model can accurately predict the traffic flow data. Meanwhile, the traffic situation characterization model can represent the road traffic situation well. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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