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Hybrid surface waves in twisted anisotropic heterometasurfaces

Physical Review Applied 2024年第6期21卷 064034-064034页

作者： Xinyan Zhang Chenxu Bian Zheng Gong Ruoxi Chen Tony Low Hongsheng Chen Xiao Lin Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation International Joint Innovation Center The Electromagnetics Academy at Zhejiang University Department of Electrical and Computer Engineering Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Shaoxing Institute of Zhejiang University

Recent advances in twisted photonic structures (e.g., twisted bilayer graphene and twisted anisotropic metasurfaces) have enabled many exotic phenomena of light-matter interactions, such as topological transition of the isofrequency contour of surface waves at the magic angle, photonic flatbands, and localization-to-delocalization transition of light. In general, the optical features of these twisted photonic structures are sensitive to the interlayer twist angle. Here we investigate the mode hybridization of surface waves supported by twisted bilayer anisotropic heterometasurfaces, whose two constituent metasurfaces are nonidentical and support surface waves with similar spatial confinements but distinct polarizations. Counterintuitively, we find that the shape of the isofrequency contour of these hybrid surface waves—eigenmodes with both transverse magnetic and transverse electric wave components—can be insensitive to the twist angle, due to the weak interlayer electromagnetic coupling. Moreover, the interlayer distance provides a unique route to reshape the dispersion of one specific kind of hybrid surface wave, while it has negligible influence on the other kinds. Our finding enriches the physics of light-matter interactions in twisted photonic structures and may open new possibilities to mold the flow of light at the subwavelength scale.

关键词： Classical optics Light-matter interaction Metamaterials Metasurfaces Near-field optics Photonics Plasmonics Van der Waals interaction

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GNS3 Communication Network Emulation for Substation GOOSE Based Protection Schemes

GNS3 Communication Network Emulation for Substation GOOSE Ba...

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International Conference on Environment and electrical engineering (EEEIC)

作者： Abdulmueen Alrashide Mahmoud S. Abdelrahman Ibtissam Kharchouf Osama A. Mohammed Department of Electrical and Computer Engineering Florida International University Energy Systems Research Laboratory Miami Fl USA Department of Electrical &#x0026 Computer Engineering Florida International University Miami FL USA

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

This paper presents a communication network model used to study the impact of the communication layer on smart grid protection schemes. Communication failure due to hardware malfunction or cyber-attack could lead to major impacts on the smart grid. Some critical devices require real-time data or close to real-time to make the right decision at the right time and keep the system in a stable zone, such as a protection relay. Active man in the middle attack adds additional latency to the packet delivery. A false data injection attack could drive the system to an unstable point, eventually leading to a blackout. This paper designed and implemented communication emulation model for a local area network on the FIU smart grid testbed. Two cases were tested in the developed communication model. In the first case, two physical raspberry pi boards were used to represent two nodes in the smart grid and one traffic generated within the virtual network. In the second case, five ABB Protection Relays and COM600 substation automation devices were connected to GNS3. The two cases showed that GNS3 could be used to emulate the communications network and study the impact of the network performance on the real-world substation environment.

关键词： Performance evaluation LAN emulation Substation automation Emulation Europe Real-time systems Hardware

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Synthetic helicoidal rotation of a quasielectrostatic ring resonator for ultrabroadband magnet-free nonreciprocity

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Physical Review Applied 2024年第6期22卷 064020-064020页

作者： Aravind Nagulu Ahmed Mekawy Mykhailo Tymchenko Dimitrios Sounas Harish Krishnaswamy Andrea Alù Department of Electrical and Systems Engineering Washington University in St. Louis St. Louis Missouri 63130 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Electrical Engineering Wayne State University Detroit Michigan 48202 USA Department of Electrical Engineering Columbia University New York New York 10027 USA Physics Program Graduate Center City University of New York New York New York 10016 USA

Suitably tailored forms of spatiotemporal modulation in electronic circuit networks have been recently employed to overcome fundamental challenges in modern electronic systems, including breaking reciprocity, squeezing the footprint of high-Q resonators, and overcoming the delay-bandwidth limit. Rotating patterns of temporal modulations have been used to synthesize angular momentum, which replaces magnetic bias to break reciprocity in integrated circuits. However, this approach is limited by trade-offs between modulation speed, footprint, and bandwidth of operation. Rotating switching patterns in commutated capacitor networks also enables compact filters and quasielectrostatic wave propagation, overcoming the delay-bandwidth limit. In this paper, we combine these mechanisms in an integrated-circuit ring that synthetically rotates in two dimensions, realizing an effective helicoidal motion that provides ultrabroadband quasielectrostatic nonreciprocal responses fitting within a theoretically infinitesimal size. We also analyze the impact of modulation signal noise on time-modulated nonreciprocal components and unveil the role of a dynamic noise mechanism based on which the noise level increases in the presence of a strong signal passing through the component, along with methods to mitigate this effect. We experimentally verify these principles in a three-port integrated circulator based on a 65-nm CMOS process that operates from dc to 1 GHz with a miniaturization factor of 2 × 106.

关键词： Metamaterials Non-reciprocal transmission Photonics Topolectrical circuits

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Optimal Information Provision for Strategic Hybrid Workers

arXiv

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arXiv 2022年

作者： Shah, Sohil Amin, Saurabh Jaillet, Patrick The Laboratory for Information and Decision Systems The Department of Electrical Engineering and Computer Science Laboratory for Information and Decision Systems Operations Research Center CambridgeMA United States

We study the problem of information provision by a strategic central planner who can publicly signal about an uncertain infectious risk parameter. Signalling leads to an updated public belief over the parameter, and agents then make equilibrium choices on whether to work remotely or in-person. The planner maintains a set of desirable outcomes for each realization of the uncertain parameter and seeks to maximize the probability that agents choose an acceptable outcome for the true parameter. We distinguish between stateless and stateful objectives. In the former, the set of desirable outcomes does not change as a function of the risk parameter, whereas in the latter it does. For stateless objectives, we reduce the problem to maximizing the probability of inducing mean beliefs that lie in intervals computable from the set of desirable outcomes. We derive the optimal signalling mechanism and show that it partitions the parameter domain into at most two intervals with the signals generated according to an interval-specific distribution. For the stateful case, we consider a practically relevant situation in which the planner can enforce in-person work capacity limits that progressively get more stringent as the risk parameter increases. We show that the optimal signalling mechanism for this case can be obtained by solving a linear program. We numerically verify the improvement in achieving desirable outcomes using our information design relative to no information and full information benchmarks. Copyright © 2022, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Using Deep Reinforcement Learning in Optimal Energy Management for Residential House Aggregators with Uncertain User Behaviors

Using Deep Reinforcement Learning in Optimal Energy Manageme...

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IEEE Student Conference on Electric Machines and systems

作者： Yujun Lin Linfang Yan Hongxun Hui Yin Chen Xia Chen Jinyu Wen State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China State Grid (Suzhou) City & Energy Research Institute Suzhou China Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macau China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow U.K.

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

In this study, the home energy management problem, which can be regarded as a high-dimensional optimization problem, for numerous residential houses, is addressed. The concept of the aggregator is utilized to reduce the state and action space and to handle the high dimensionality. A two-stage deep reinforcement learning (DRL)-based approach is proposed for the aggregators to track the schedule from a superior grid and guarantee the operation constraints. In the first stage, a DRL control agent is set to learn the optimal scheduling strategy interacting with the environment based on the soft-actor-critic framework and generate the aggregate control actions. In the second stage, the aggregate control actions are disaggregated to individual appliances considering the users' behaviors. The uncertainty of an electric vehicle's charging demand is quantitatively expressed based on the driver's experience. An aggregate anxiety concept is introduced to characterize the driver's anxiety on the electric vehicle's range and uncertain events. Finally, simulations are conducted to verify the effectiveness of the proposed approach under dynamic user behaviors, and comparisons show the superiority of the proposed approach over other benchmark methods.

关键词： Schedules Uncertainty Aggregates Anxiety disorders Optimal scheduling Deep reinforcement learning Electric vehicle charging Temperature control Vehicle dynamics Resistance heating

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Enhanced Memory Performance in Ferroelectric NAND Applications: The Role of Tunnel Dielectric Position for Robust 10-Year Retention

Enhanced Memory Performance in Ferroelectric NAND Applicatio...

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2025 IEEE International Reliability Physics Symposium, IRPS 2025

作者： Venkatesan, Prasanna Padovani, Andrea Fernandes, Lance Ravikumar, Priyankka Park, Chinsung Tran, Huy Wang, Zekai Jayasankar, Hari Garlapati, Amrit Song, Taeyoung Chen, Hang Chern, Winston Wang, Zheng Kim, Kijoon Woog, Jongho Lim, Suhwan Kim, Kwangsoo Kim, Wanki Ha, Daewon Yu, Shimeng Dattal, Suman Larcher, Luca Thareja, Gaurav Khanl, Asif School of Electrical and Computer Engineering Georgia Institute of Technology GA United States University of Modena and Reggio Emilia Engineering Department 'Enzo Ferrari' Italy Institute of Electronics and Nanotechnology Georgia Institute of Technology GA United States Micron Technology United States Samsung Electronics Advanced Device Research Laboratory Semiconductor Research Center South Korea School of Material Science and Engineering Georgia Institute of Technology GA United States Applied Materials United States

ISBN: (纸本)9798331504779

We report a comprehensive study on memory window (MW) enhancement and retention loss (RL) in ferroelectric (FE) field effect transistors for NAND applications with a dielectric layer inserted within the FE film (next to the gate GBL devices or in the middle of the FE layer TDL devices). Using a temperature-dependent modeling framework, we show that MW and RL properties are controlled respectively by carriers trapping into defects at the dielectric-FE interface and by its fragile balance with FE depolarization. While MW enhancement is achieved whenever the inserted dielectric layer is present, a robust retention is obtained only in TDL FEFETs, thanks to a stabilization of the trapped charge preventing FE depolarization. Simulation results clearly demonstrate that the fragile balance between above phenomena is ultimately controlled by the position of the dielectric layer, which determines i) the field redistribution within the stack, ii) the magnitude of charge de-trapping, and iii) the magnitude of the depolarization field. Our results provide critical guidelines for the improvement of FE 3D-NAND reliability. © 2025 IEEE.

关键词： 3D-NAND FEFET Ginestra™ Retention

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Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 959-973页

作者： Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Department of Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Gene Regulation and Systems Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055China

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.

关键词： Transcription start site Machine learning Deep learning Meta-learning RNA sequencing

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Convergence Condition of Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation

Convergence Condition of Simplified Information Geometry App...

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IEEE Conference on Vehicular Technology (VTC)

作者： Mingrui Fan Jiyuan Yang Yan Chen An-An Lu Xiqi Gao Xiang-Gen Xia Dirk Slock National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China Department of Electrical and Computer Engineering University of Delaware Newark DE USA Department of Communication Systems EURECOM Biot France

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

In this paper, we prove the convergence of the simplified information geometry approach (SIGA), which was proposed for massive MIMO-OFDM channel estimation. For a general Bayesian inference problem, we first show that the iteration of the common second-order natural parameter (SONP) is separated from that of the common first-order natural parameter (FONP). Hence, the convergence of the common SONP can be checked independently. We show that with the initialization satisfying a specific but large range, the common SONP is convergent regardless of the value of the damping factor. For the common FONP, we establish a sufficient condition of its convergence and prove that the convergence of the common FONP relies on the spectral radius of a particular matrix related to the damping factor. We give the range of the damping factor that guarantees the convergence in the worst case. Further, we determine the range of the damping factor for massive MIMO-OFDM channel estimation by using the specific properties of the measurement matrices. Simulation results are provided to confirm the theoretical results.

关键词： Damping Sufficient conditions Information geometry Vehicular and wireless technologies Simulation Channel estimation Bayes methods

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Recent Advancements in Vehicle to Vehicle Charging

Recent Advancements in Vehicle to Vehicle Charging

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International Conference on Power Electronics and Drive systems (PEDS)

作者： Anindita Golder Kushan Tharuka Lulbadda Tarlochan Sidhu Sheldon S. Williamson Department of Electrical and Computer Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Ontario Tech University Oshawa ON Canada

More and more electric vehicles and charging stations are penetrating into the power system today which introduce new challenges. As a result, the concept of vehicle to vehicle charging (V2V) is gaining interest. Therefore, it is important to understand the concept of V2V charging. In this paper, some of the recent developments in the area of vehicle to vehicle (V2V) charging are explored.

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