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High-performance UV polarization sensitive photodetector for a graphene(2D)/GaN(3D) junction with a non-centrosymmetric electric field

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Photonics Research 2025年第6期13卷 1544-1553页

作者： Zou, Can Liu, Qing Zhang, Lu Tang, Xiao Li, Xiaohang Li, Shuti Gao, Fangliang Guangdong Engineering Research Center of Optoelectronic Functional Materials and Devices School of Electronic Science and Engineering School of Microelectronics South China Normal University Guangzhou510631 China Advanced Semiconductor Laboratory Electrical and Computer Engineering Program CEMSE Division King Abdullah University of Science and Technology Thuwal239556900 Saudi Arabia

This study pioneers a high-performance UV polarization-sensitive photodetector by ingeniously integrating non-centrosymmetric metal nanostructures into a graphene (Gr)∕Al2O3∕GaN heterojunction. Unlike conventional approaches constrained by graphene’s intrinsic isotropy or complex nanoscale patterning, our design introduces asymmetric metal architectures (E-/T-type) to artificially create directional anisotropy. These structures generate plasmon-enhanced localized electric fields that selectively amplify photogenerated carrier momentum under polarized UV light (325 nm), synergized with Fowler-Nordheim tunneling (FNT) across an atomically thin Al2O3 barrier. The result is a breakthrough in performance: a record anisotropy ratio of 115.5 (E-type, −2 V) and exceptional responsivity (97.7 A/W), surpassing existing graphene-based detectors by over an order of magnitude. Crucially, by systematically modulating metal geometry and density, we demonstrate a universal platform adaptable to diverse 2D/3D systems. This study provides a valuable reference for developing and practically applying photodetectors with higher anisotropy than ultraviolet polarization sensitivity. © 2025 Chinese Laser Press.

关键词： Nanoparticles

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Brain Tumor Detection and Segmentation Using Deep Learning Models 6

Brain Tumor Detection and Segmentation Using Deep Learning M...

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6th World Symposium on Artificial Intelligence, WSAI 2024

作者： Abiodun, Moses Kazeem Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Aworinde, Halleluyah Tinuoye, George Imoize, Agbotiname Lucky Li, Chun-Ta Lee, Cheng-Chi Landmark University Department of Computer Science Kwara State Omu-Aran Nigeria Bowen University Department of Computer Science Osun State Iwo Nigeria University of Ilorin Department of Computer Science Kwara State Ilorin Nigeria University of Lagos Faculty of Engineering Department of Electrical and Electronics Engineering Akoka Nigeria Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City Taiwan Fu Jen Catholic University Department of Library and Information Science New Taipei City Taiwan

ISBN: (纸本)9798350374162

This study focuses on brain tumor detection and segmentation using Convolutional Neural Networks (CNN) with architectures of Fully Convolutional Net-work (FCN) and VGG16. The dataset imported for this study consists of brain MRI images, which were preprocessed to improve the overall image resolution. Data augmentation techniques were applied to heighten the variability and volume of the training data. For feature extraction, CNN models were utilized, specifically the VGG16 architectures. This model was trained on a preprocessed dataset to learn the important features associated with the presence of brain tumor. Image segmentation was performed to precisely outline and identify the tumor region within the brain images. FCN architecture was employed for this task, which allowed pixel-level classification of tumor regions. Finally, image classification was carried out to group brain images based on the absence or presence of a tumor. The trained models were evaluated using accuracy, precision, recall and F1score as the performance metrics. The results of the study demonstrated promising outcomes, achieving an accuracy score of 93% and a precision, recall and f1score ranging from 75% to 100% based on the specific type of tumor enlisted. This indicates that the developed CNN models, with the FCN and VGG16 architectures, effectively detect and segment brain tumors from MRI images. The findings of this study contribute to the field of medical image analysis and gives a foundation for further research and development in brain tumor diagnosis and treatment. The study recommends the use of more deep learning algorithms for the process of detecting brain tumors. © 2024 IEEE.

关键词： Convolutional neural networks

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First write pulse-induced interface damage in ferroelectric field-effect transistors

First write pulse-induced interface damage in ferroelectric ...

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2024 IEEE International Integrated Reliability Workshop, IIRW 2024

作者： Ravikumar, Priyankka Gundlapudi Park, Chinsung Ravindran, Prasanna Venkatesan Afroze, Nashrah Tian, Mengkun Chern, Winston Datta, Suman Yu, Shimeng Mahapatra, Souvik Khan, Asif Institute of Materials GA United States Georgia Institute of Technology School of Electrical and Computer Engineering GA United States Georgia Institute of Technology School of Material Science and Engineering GA United States Indian Institute of Technology Bombay Department of Electrical Engineering Mumbai India

ISBN: (纸本)9798331517168

We report the first direct experimental evidence that the first write pulse (cycle 1) generates more than half of the total traps generated until the complete collapse of the memory window at cycle 10⁴-10⁵, in ferroelectric field effect transistors (FEFETs). This conclusion is reached by tracking the generated traps by a combination of subthreshold slope and charge pumping measurements in a Ferroelectric field-effect transistor and an equivalent standard MOSFET of same effective oxide thickness (EOT). We also find that with continued cycling, traps get generated more toward the bulk of the stack away from the Si/SiO₂ interface. We show that: (1) the first switch effect leads to nearly 50% of the total trap density (N_it) near the Si/SiO₂ interface until memory window closure (2) with further bipolar cycling, damage happens both at and away from Si/SiO₂ interface. © 2024 IEEE.

关键词： Charge pumping Endurance FEFET HfO2 based Ferroelectrics

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Meta-optic accelerators for object classification

Meta-optic accelerators for object classification

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2023 Flat Optics: Components to Systems, FLatOptics 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Zheng, Hanyu Liu, Quan Zhou, You Kravchenko, Ivan I. Huo, Yuankai Valentine, Jason Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37212 United States Department of Computer Science Vanderbilt University NashvilleTN37212 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37212 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37212 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States

A meta-optic platform for accelerating object classification is demonstrated. End-to-end design is used to co-optimize the optical and digital systems resulting in high-speed classifiers that are demonstrated for hand... 详细信息

ISBN: (纸本)9781957171289

关键词： Imaging systems Machine vision Neural networks Optical components Optical neural systems Optical systems

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Vectorial liquid‑crystal holography

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eLight 2024年第1期4卷 251-261页

作者： Ze‑Yu Wang Zhou Zhou Han Zhang Yang Wei Hong‑Guan Yu Wei Hu Wei Chen Hai‑Tao Dai Ling‑Ling Ma Cheng‑Wei Qiu Yan‑Qing Lu National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollaborative Innovation Center of Advanced MicrostructuresCollege of Engineering and Applied SciencesNanjing UniversityNanjing 210023China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Tianjin Key Laboratory of Low Dimensional Materials Physics and Preparing Technology School of ScienceTianjin UniversityTianjin 300072China

Vectorial optics with fine inhomogeneous polarization control are highly *** have been captivated a promising candidate,but their static post-fabrication geometry largely limits the dynamic *** crystal(LC)is usually employed as an additional index-changing layer together with ***,most of the reported LCs only impart a varying but uniform phase on top of that from the metasurface,which we term“scalar”LC ***,we pixelate a single-layer LC to display versatile and tunable vectorial holography,in which the polarization and amplitude could be arbitrarily and independently controlled at varying spatial ***,the subtle and vectorial LC-holography highlights the broadband and electrically-switchable *** vectorial LC holography reveals significant opportunities for advanced cryptography,super-resolution imaging,and many other applications.

关键词： Liquid crystals Vectorial optics Holography

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Smart Home Security System Using Face Recognition Based on IoT- CNN 2

Smart Home Security System Using Face Recognition Based on I...

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2nd International Conference on Information Technology Research and Innovation, ICITRI 2023

作者： Febriantono, M. Aldiki Zuhair, Alvin Khaeruddin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia University of Islam Blitar Electrical Engineering Department Blitar Indonesia University of Muhammadiyah Malang Diploma III Electronic Technology Vocational Study Program Malang Indonesia

ISBN: (纸本)9798350324945

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning computer Vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning computer Vision holds tremendous benefits for homeowners. © 2023 IEEE.

关键词： Face recognition

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Understanding wide field-of-view flat lenses:an analytical solution[Invited]

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Chinese Optics Letters 2023年第2期21卷 111-118页

作者：杨帆安森松 Mikhail Y.Shalaginov 张华亮胡崛隽古田 Department of Materials Science&Engineering Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA Department of Electrical&Computer Engineering University of Massachusetts LowellLowellMassachusetts 01854USA Materials Research Laboratory Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA

Wide field-of-view(FOV)optics are widely used in various imaging,display,and sensing *** wide FOV optics rely on complicated lens assembly comprising multiple elements to suppress coma and other Seidel *** emergence of flat optics exemplified by metasurfaces and diffractive optical elements(DOEs)offers a promising route to expand the FOV without escalating complexity of optical *** date,design of large FOV flat lenses has been relying upon iterative numerical ***,we derive,for the first time,to the best of our knowledge,an analytical solution to enable computationally efficient design of flat lenses with an ultra-wide FOV approaching 180°.This analytical theory further provides critical insights into working principles and otherwise non-intuitive design trade-offs of wide FOV optics.

关键词： metasurface metalens field-of-view

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Analysis of Partial Discharges in Oil-Impregnated Transformer Paper Insulation and PET-G Insulation

IEEE Open Journal of Instrumentation and Measurement

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IEEE Open Journal of Instrumentation and Measurement 2025年 4卷

作者： Kameli, Sayed Mohammad Abuelrub, Abdelaziz AlShaikh Saleh, Mohammad Refaat, Shady S. Ghrayeb, Ali Abu-Rub, Haitham Olesz, Marek Texas A&M University at Qatar Electrical and Computer Engineering Department Doha Qatar Texas A&M University Department of Electrical and Computer Engineering College StationTX77843 United States University of Hertfordshire School of Physics Engineering and Computer Science Department of Engineering HatfieldAL10 9EU United Kingdom Hamad Bin Khalifa University Qatar Foundation Electrical and Computer Engineering Program in College of Science and Engineering Doha Qatar Gdańsk University of Technology Department of Electrical Power Engineering Gdańsk80-233 Poland

Partial discharge (PD) is a widespread phenomenon instigated in power transformer (PT) insulation systems. PDs are triggered by voids that vary in size and position within the PT insulation. The electrical characteristics of those damaging, PD-causing cavities must be well understood, to accelerate the development of advanced PD detection techniques. Thus, the impact of varying the radius and position of spherical air voids on the characteristics of PDs in PTs is examined using a 3-D finite element analysis (FEA) model designed in COMSOL Multiphysics. The spherical voids are positioned between two windings of a 512 kV, three-phase (3φ ) PT. The peak electric field (EF) and aggregate energy in the FEA model are used in conjunction with laboratory measurements of the apparent discharge magnitude, for detailed analysis of Polyethylene Terephthalate Glycol (PET-G)-based cylindrical voids with different heights. Simulations demonstrate that the inception of PD activity in the PT model occurs for spherical voids with a radius exceeding 1 mm. Furthermore, the most severe PDs occur within the press-board insulation, adjacent to the uppermost part of the innermost windings. Experiments demonstrate that a significant increase in PD activity was observed for PET-G-based cylindrical voids with heights exceeding 1 mm. © 2022 IEEE.

关键词： Partial discharges

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On the Reliability of High-Performance Dual Gate (DG) W-Doped In2O3 FET

On the Reliability of High-Performance Dual Gate (DG) W-Dope...

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2024 IEEE Symposium on VLSI Technology and Circuits, VLSI Technology and Circuits 2024

作者： Aabrar, Khandker Akif Park, Hyeonwoo Kirtania, Sharadindu G. Sarkar, Eknath Al Mamun, Md Abdullah Deng, Sunbin Zhang, Chengyang Rayner, Gilbert B. Cho, Kyeongjae Datta, Suman School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States University of Texas at Dallas Department of Materials Science and Engineering RichardsonTX75080 United States Kurt J. Lesker Company Jefferson HillsPA15025 United States

ISBN: (纸本)9798350361469

We demonstrate a high performance back-end-of-line (BEOL) compatible tungsten (W)-doped In2O3 channel (IWO) dual gate (DG) field-effect transistor (FET) with ultra low-leakage current -15 A/μ m and high ION/IOFF ratio of 5.8× 1011 at 2.5V overdrive (Vov). In addition, the IWO DG FET demonstrates a record low negative bias temperature instability (NBTI) of 7.2mV, record low hot carrier degradation (HCD) of 63mV and a low positive bias temperature instability (PBTI) of 85mV at 1V Vov which makes IWO DG FET a potential candidate for realizing high density embedded-DRAM for last-level cache (LLC). Furthermore, we develop a comprehensive modeling framework for assesing the reliability of amorphous oxide semiconductor (AOS) channel FETs which can provide insights into the threshold voltage (VT) instability mechanisms and help design appropriate mitigation strategies. © 2024 IEEE.

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Frequency multiplexed emission from cavity-enhanced T centers

Frequency multiplexed emission from cavity-enhanced T center...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Komza, Lukasz Zhang, Xueyue Tang, Yu-Lung Song, Hanbin Sipahigil, Alp Department of Physics University of California Berkeley BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States Department of Materials Science and Engineering University of California Berkeley BerkeleyCA94720 United States

To enable efficient s pin-photon interfaces with T centers, cavity-enhanced emission is essential. We build an integrated photonics platform demonstrating cavity-enhanced emission from multiple T centers across distin... 详细信息

ISBN: (纸本)9781957171395

关键词： Photonic integrated circuits

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