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Thermal and electric field driven rf breakdown precursor formation on metal surfaces

Physical Review Accelerators and Beams 2024年第5期27卷 053101-053101页

作者： Ryo Shinohara Soumendu Bagchi Evgenya Simakov Sergey V. Baryshev Danny Perez Department of Electrical and Computer Engineering Michigan State University Michigan 48824 USA Department of Physics and Astronomy Michigan State University East Lansing Michigan 48824 USA Theoretical Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Accelerator Operations and Technology Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Department of Chemical Engineering and Material Science Michigan State University Michigan 48824 USA

The phenomenon of electric breakdown poses serious challenges to the design of devices that operate in high electric field environments. Experimental evidence points toward breakdown events that are accompanied by elevated temperatures and dark current spikes, which is attributed to high-asperity nanostructure formation that enhances the local electric field and triggers a runaway process. However, the exact mechanistic origin of such nanostructures under typical macroscopic operational conditions of electric field and magnetic-field-mediated heating remains poorly understood. In this work, we simulate the evolution of a copper surface under the combined action of the electric fields and elevated temperatures. Using a mesoscale curvature-driven surface evolution model, we show how a copper surface can undergo a type of dynamical instability that naturally leads to the formation of sharp asperities in realistic experimental conditions. Exploring the combined effect of fields and temperature rise, we identify the critical regimes that allow for the formation of breakdown precursors. The results show that thermoelastic stresses, while not essential, can significantly lower the critical electric field required for runaway surface instability, which is consistent with experimental observations that thermal effects can increase breakdown rates.

关键词： Material failure Plastic deformation Room temperature RF Thermal expansion Finite-element method

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MULTI-MODAL REPRESENTATION LEARNING FOR CROSS-MODAL PREDICTION OF CONTINUOUS WEATHER PATTERNS FROM DISCRETE LOW-DIMENSIONAL DATA

arXiv

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arXiv 2024年

作者： Qayyum, Alif Bin Abdul Luo, Xihaier Urban, Nathan M. Qian, Xiaoning Yoon, Byung-Jun Department of Electrical & Computer Engineering Texas A&M University College StationTX77843-3128 United States Computational Science Initiative Brookhaven National Laboratory UptonNY11973-5000 United States Computational Science Initiative Brookhaven National Laboratory United States

World is looking for clean and renewable energy sources that do not pollute the environment, in an attempt to reduce greenhouse gas emissions that contribute to global warming. Wind energy has significant potential to not only reduce greenhouse emission, but also meet the ever increasing demand for energy. To enable the effective utilization of wind energy, addressing the following three challenges in wind data analysis is crucial. Firstly, improving data resolution in various climate conditions to ensure an ample supply of information for assessing potential energy resources. Secondly, implementing dimensionality reduction techniques for data collected from sensors/simulations to efficiently manage and store large datasets. Thirdly, extrapolating wind data from one spatial specification to another, particularly in cases where data acquisition may be impractical or costly. We propose a deep learning based approach to achieve multi-modal continuous resolution wind data prediction from discontinuous wind data, along with data dimensionality reduction. © 2024, CC BY.

关键词： Deep learning

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Special section on edge AI and accelerators

IEEE Open Journal of Circuits and Systems

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IEEE Open Journal of Circuits and Systems 2021年 2卷 128-130页

作者： John, Deepu Li, Yongfu Zhang, Xinmiao School of Electrical and Electronics Engineering University College Dublin DublinD04V1W8 Ireland Department of Micro-Nano Electronics and MoE Key Laboratory of Artificial Intelligence Shanghai Jiao Tong University Shanghai200240 China Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States

This special section presents seven state-of-the-art design techniques for AI hardware accelerators that lead to substantial improvements on energy efficiency, reconfigurability, and resource utilization.

关键词： Special issues and sections Edge computing Artificial intelligence Memory management Convolutional neural networks Hardware acceleration Telecommunication traffic System-on-chip Servers

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Terahertz bound states in the continuum with incident angle robustness induced by a dual period metagrating

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Photonics Research 2022年第3期10卷 810-819页

作者： Wenqiao Shi Jianqiang Gu Xingyuan Zhang Quan Xu Jiaguang Han Quanlong Yang Longqing Cong Weili Zhang Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Tianjin Universityand Key Laboratory of Optoelectronics Information and TechnologyMinistry of EducationTianjin 300072China Nonlinear Physics Centre Australian National UniversityCanberraACT 2601Australia Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhen 518055China School of Electrical and Computer Engineering Oklahoma State UniversityStillwaterOklahoma 74078USA

Metasurface-empowered bound state in the continuum(BIC)provides a unique route for fascinating functional devices with infinitely high quality *** method is particularly attractive to the terahertz community because it may essentially solve the deficiencies in terahertz filters,sensors,lasers,and nonlinear ***,most BIC metasurfaces are limited to specified incident angles that seriously dim their application ***,we propose that a dual-period dielectric metagrating can support multiple families of BICs that originate from guided mode resonances in the dielectric grating and exhibit infinite quality factors at arbitrarily tilted *** robustness was analyzed based on the Bloch theory and verified at tilted incident *** also demonstrate that inducing geometric asymmetry is an efficient way to manipulate the leakage and coupling of these BICs,which can mimic the electromagnetically induced transparency(EIT)effect in our dual-period *** this demonstration,a slow-light effect with a measured group delay of 117 ps was *** incidence-insensitive BICs proposed here may greatly extend the application scenarios of the BIC *** high Q factor and outstanding slow-light effect in the metagrating show exciting prospects in realizing high-performance filters,sensors,and modulators for prompting terahertz applications.

关键词： incident dielectric continuum

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Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection

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IEEE Geoscience and Remote Sensing Letters 2023年 20卷 1页

作者： Zhang, Haopeng Lin, Zijing Gao, Feng Dong, Junyu Du, Qian Li, Heng-Chao Ocean University of China School of Computer Science and Technology Qingdao266100 China Mississippi State University Department of Electrical and Computer Engineering StarkvilleMS39762 United States Southwest Jiaotong University Sichuan Provincial Key Laboratory of Information Coding and Transmission Chengdu610031 China

Synthetic aperture radar (SAR) image change detection is a critical task and has received increasing attention in the remote sensing community. However, existing SAR change detection methods are mainly based on convolutional neural networks (CNNs), with limited consideration of global attention mechanism. In this letter, we explore Transformer-like architecture for SAR change detection to incorporate global attention. To this end, we propose a convolution and attention mixer (CAMixer). First, to compensate for the inductive bias for Transformer, we combine self-attention with shift convolution in a parallel way. The parallel design effectively captures the global semantic information via self-attention and performs local feature extraction through shift convolution simultaneously. Second, we adopt a gating mechanism in the feed-forward network to enhance the nonlinear feature transformation. The gating mechanism is formulated as the element-wise multiplication of two parallel linear layers. Important features can be highlighted, leading to high-quality representations against speckle noise. Extensive experiments conducted on three SAR datasets verify the superior performance of the proposed CAMixer. The source codes will be publicly available at https://***/summitgao/CAMixer. © 2004-2012 IEEE.

关键词： Feature extraction

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Comparison of using photovoltaic system and diesel generator to feed the desired load 4

Comparison of using photovoltaic system and diesel generator...

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4th International Iraqi Conference on engineering Technology and Their Applications, IICETA 2021

作者： Hussain, Ali Nasser Al-Sagar, Zuhair S. Al-Tamimi, Majid Khudair Abbas Abid, Mimouna Hassan, Qusay AL-Abbooda, Karrar Saadoon Baghdad Iraq Baghdad Iraq Department of Electrical Engineering L2GEGI Laboratory University of Tiaret Tiaret Algeria Department of Computer Engineering Al-turath University College Baghdad Iraq College of Technical Engineering The Islamic University Najaf Iraq

ISBN: (纸本)9781665494618

The work in this paper presents techno-economic evolution for two energy systems (conventional and renewable) set with grid connection. The investigation was carried out by using an experimental measurement for the desired load and weather data (solar irradiance and ambient temperature). The simulation process performed using MATLAB and HOMER software at 1-minute time step resolution. The economic optimisation objective presented for two energy systems scenarios (i) photovoltaic/grid and (ii) diesel/grid. The component prices and economic assumptions based on the Iraqi market and regulations. The diesel generator is designed to work at the same period of the photovoltaic system operation (only during day hours), where the annual operation hours recorded 4380 hours/year which can produce 2349 kWh/year and consume diesel fuel by about 1826 letters/year. The results showed that the photovoltaic system based on scenario (A) can generate energy approx. 7895 kWh and the diesel generator based on scenario (B) can generate energy approx. 2346 kWh. The total net present cost and the cost of energy for scenario (A) by about ($1079) and ($0.035/kWh) respectively, and scenario (B) ($12287) and ($0.598/kWh) respectively. Based on the obtained results the used of solar energy is highly recommended than diesel generators due to the lowest cost and participation in grid energy support. © 2021 IEEE.

关键词： Solar energy

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Rapid Brain Meninges Surface Reconstruction with Layer Topology Guarantee

Rapid Brain Meninges Surface Reconstruction with Layer Topol...

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IEEE International Symposium on Biomedical Imaging

作者： Peiyu Duan Yuan Xue Shuo Han Lianrui Zuo Aaron Carass Caitlyn Bernhard Savannah Hays Peter A. Calabresi Susan M. Resnick James S. Duncan Jerry L. Prince Department of Biomedical Engineering Johns Hopkins School of Medicine USA Department of Biomedical Engineering Yale University USA Department of Electrical and Computer Engineering Johns Hopkins University USA Laboratory of Behavioral Neuroscience National Institute on Aging National Institutes of Health USA Department of Neurology Johns Hopkins School of Medicine USA

The meninges, located between the skull and brain, are composed of three membrane layers: the pia, the arachnoid, and the dura. Reconstruction of these layers can aid in studying volume differences between patients with neurodegenerative diseases and normal aging subjects. In this work, we use convolutional neural networks (CNNs) to reconstruct surfaces representing meningeal layer boundaries from magnetic resonance (MR) images. We first use the CNNs to predict the signed distance functions (SDFs) representing these surfaces while preserving their anatomical ordering. The marching cubes algorithm is then used to generate continuous surface representations; both the subarachnoid space (SAS) and the intracranial volume (ICY) are computed from these surfaces. The proposed method is compared to a state-of-the-art deformable model-based reconstruction method, and we show that our method can reconstruct smoother and more accurate surfaces using less computation time. Finally, we conduct experiments with volumetric analysis on both subjects with multiple sclerosis and healthy controls. For healthy and MS subjects, ICYs and SAS volumes are found to be significantly correlated to sex (p<0.01) and age (p≤0.03) changes, respectively.

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Battle Against Fluctuating Quantum Noise: Compression-Aided Framework to Enable Robust Quantum Neural Network

Battle Against Fluctuating Quantum Noise: Compression-Aided ...

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Design Automation Conference

作者： Zhirui Hu Youzuo Lin Qiang Guan Weiwen Jiang Electrical and Computer Engineering Department George Mason University Fairfax VA US Quantum Science and Engineering Center George Mason University Fairfax VA US Earth and Environmental Sciences Division Los Alamos National Laboratory NM US Department of Computer Science Kent State University Kent OH

Recently, we have been witnessing the scale-up of superconducting quantum computers; however, the noise of quantum bits (qubits) is still an obstacle for real-world applications to leveraging the power of quantum computing. Although there exist error mitigation or error-aware designs for quantum applications, the inherent fluctuation of noise (a.k.a., instability) can easily collapse the performance of error-aware designs. What’s worse, users can even not be aware of the performance degradation caused by the change in noise. To address both issues, in this paper we use Quantum Neural Network (QNN) as a vehicle to present a novel compression-aided framework, namely QuCAD, which will adapt a trained QNN to fluctuating quantum noise. In addition, with the historical calibration (noise) data, our framework will build a model repository offline, which will significantly reduce the optimization time in the online adaption process. Emulation results on an earthquake detection dataset show that QuCAD can achieve 14.91% accuracy gain on average in 146 days over a noise-aware training approach. For the execution on a 7-qubit IBM quantum processor, ibm-jakarta, QuCAD can consistently achieve 12.52% accuracy gain on earthquake detection.

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Hand Gesture Recognition from an Open-Set Perspective

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IEEE Transactions on Multimedia 2025年

作者： Zhou, Jun Xu, Chi Cheng, Li China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Vision and Learning Laboratory Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

Existing hand gesture recognition methods predominantly rely on a close-set assumption, which in essence limits the viewpoints, gesture categories, and hand shapes at test time to closely resemble those seen during training. This requirement is however rarely met in practice, as images are often captured from unconstrained viewpoints, with novel gestures and unseen hand shapes that can differ significantly from the training data. This motivates us to investigate an open-set hand gesture recognition problem, where hand gestures are still recognizable from unconstrained viewpoints, and novel gesture classes and hand shapes can be incrementally learned with just a few examples. To address this, we propose a viewpoint influence elimination network that extracts view-independent features, significantly improving performance in scenarios with unconstrained viewpoints. Moreover, a joint-weighted classification scheme is introduced to augment the cosine similarity metric for evaluating few-shot incremental learning of novel gestures and shapes. Finally, as existing hand gesture recognition datasets primarily adhere to the close-set assumption, a new hand gesture recognition dataset, OHG, is introduced in this paper, that includes a wide range of viewpoints, diverse gesture classes, and distinct hand shapes. Experimental hand gesture recognition results demonstrate the superior performance of our approach in both unconstrained viewpoint and few-shot incremental learning scenarios. The source code and the OHG dataset are to be made available at https://***/zhoujun-7/OSHGR. © 1999-2012 IEEE.

关键词： Palmprint recognition

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Interpretable inverse-designed cavity for nonlinear photon pair generation on-chip 28

Interpretable inverse-designed cavity for nonlinear photon p...

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Integrated Optics: Devices, Materials, and Technologies XXVIII 2024

作者： Jia, Zhetao Qarony, Wayesh Park, Jagang Hooten, Sean Wen, Difan Zhiyenbayev, Yertay Seclì, Matteo Redjem, Walid Dhuey, Scott Schwartzberg, Adam Kanté, Boubacar Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States Hewlett Packard Labs Hewlett Packard Enterprise 820 N McCarthy Blvd MilpitasCA95035 United States Applied Science and Technology Graduate Group University of California Berkeley BerkeleyCA94720 United States Molecular Foundry Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States

ISBN: (纸本)9781510670389

Inverse design has proved to be a powerful tool in photonics for compact, high-performance devices. To date, applications have been limited to linear systems but have rarely been investigated or demonstrated in nonlinear regimes. In addition, the "black box"nature of inverse design techniques hinders the understanding of the optimized structure. Here, we propose an inverse design approach to amplify the efficiency of on-chip photon pair generation. We implement this strategy based on the open-source package EMopt. Our method employs a multi-frequency co-optimization strategy and calculates gradients with respect to the design parameters via the adjoint method. The resulting efficiency enhancement stems not only from the field intensification due to the confinement of light from high-quality factor cavity resonances but also from the improvement of phase-matching conditions, along with coupling between the cavity and waveguide mode considered in the design. We demonstrate the capability of the proposed method by fabricating and characterizing an optimized device that enables the efficient generation of photon pairs. Our design follows the fabrication constraints and can be used for scalable quantum light sources in large-scale computing and communication applications. Interestingly, the shape of the proposed design can also be explained by the effective potential method. The proposed optimization technique can be generalized to other nonlinear processes for compact frequency-mixing devices on-chip. © 2024 SPIE.

关键词： Design

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