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IEEE International Conference on Power and Energy Applications (ICPEA)

作者： Shangkun Wang Junchao Zhang Xiaofeng Yang Shijia Guo Huanshuai Yan Bingshe Xu College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Department of Computer Engineering Shanxi Vocational University of Engineering Science and Technical College Yuci China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

A circuit using STM32 chip as the main control is designed to address the issue of semiconductor laser performance being easily affected by injection current and operating temperature. It can achieve high-precision and high stability constant current drive and constant temperature control, and has complete protection functions. The system adopts LT3080 The AD5160, TS5A3159 chips and sampling resistors have been designed with a constant current negative feedback circuit; Design a constant voltage limiting module using LM317 chip to ensure that the forward voltage of the semiconductor laser does not exceed the rated maximum value, and the slow start module slowly increases the current to the set value; The electrostatic protection circuit effectively avoids the damage of high-voltage static electricity and surge current to the laser; Design a temperature sampling module with ADN8834 as the core, and use incremental digital PID technology to control the heating or cooling of TEC. The experimental results show that this driving circuit can continuously adjust the current of the semiconductor laser, with a range of 0 to 100 mA. The current regulation accuracy has reached 0.01mA, and the stability has reached 0.02%; The temperature control accuracy within 10–40 °C is 0.01 °C, and the stability can reach 0.12%.

关键词： Accuracy Semiconductor lasers Laser feedback Laser stability Circuit stability Voltage control Protection Laser applications Surges Thermal stability

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Characteristic Mode Analysis of Nanostructures using Hydrodynamic Volume Integral Equation

Characteristic Mode Analysis of Nanostructures using Hydrody...

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Antennas and Propagation & USNC/URSI National Radio science Meeting

作者： Meruyert Khamitova Ran Zhao Doolos Aibek uulu Hakan Bagci Electrical and Computer Engineering (ECE) Program Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Kingdom of Saudi Arabia School of Electronic Science and Engineering University of Electronic Science and Technology of China (UESTC) Chengdu Sichuan China Department of Mathematics and Natural Sciences University of Central Asia (UCA) Naryn Kyrgyzstan

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

The characteristic mode analysis (CMA) is formulated and implemented for the hydrodynamic volume integral equation (HDVIE) that is used to mathematically model electromagnetic field interactions and conduction current dynamics on nanoantennas and nanoscatterers. The proposed method produces excitation-independent characteristic hydrodynamic currents and the corresponding modal significance curves, providing useful information that can be used to optimize the performance of a nanoantenna. Numerical results demonstrate the reliability and the applicability of the proposed approach.

关键词： Solid modeling Nanoantennas Integral equations Hydrodynamics Mathematical models Characteristic mode analysis Numerical models

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Optimal data distribution in FeFET-based computing-in-memory macros

Optimal data distribution in FeFET-based computing-in-memory...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Yonguk Sim Choongseok Song Eun Chan Park Jongwook Jeon Daewoong Kwon Doo Seok Jeong Department of Semiconductor Engineering Hanyang University Seoul Republic of Korea Division of Materials Science and Engineering Hanyang University Seoul Republic of Korea Department of Electronic Engineering Hanyang University Seoul Republic of Korea Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Republic of Korea

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Computing-in-memory (CIM) may offer a power-efficient solution to the acceleration of major workloads for memory-bound deep neural networks given memory and processing units on the same die, particularly, when incorporating the processing units into the memory domains. Further, CIM macros utilizing nonvolatile memory with multibit data significantly boost their data density and realize zero standby power by gating power when idle. Ferroelectric Field-Effect-Transistor (FeFET) is a leading contender for this type of CIM. In this work, we designed mixed signal CIM macros based on FeFETs and identified their optimal performance with the size of a sub-array (n M × n w ) addressed at one cycle, where n w is the number of FeFETs representing a single w-bit weight. The simulations performed identified the optimal sub-array $n_M^{\ast} \times w/2$ for w-bit weights with different $n_M^{\ast}$ (i.e., parallelism) for different weight resolution w, which highlights a ∼29× improvement in figure of merit for 8-bit weights compared with the case of no weight-splitting (n w = 1).

关键词： Degradation Nonvolatile memory Computational modeling Parallel processing In-memory computing Common Information Model (computing) Common Information Model (electricity)

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Is machine learning redefining the perovskite solar cells?

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Journal of Energy Chemistry 2022年第3期31卷 74-90,I0004页

作者： Nishi Parikh Meera Karamta Neha Yadav Mohammad Mahdi Tavakoli Daniel Prochowicz Seckin Akin Abul Kalam Soumitra Satapathi Pankaj Yadav Department of Science School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Electrical Engineering School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Telecommunication Ministry of CommunicationMumbai LSAMumbai 400072MaharashtraIndia Department of Electrical Engineering and Computer Science Massachusetts Institute of TechnologyCambridgeMA 02139USA Institute of Physical Chemistry Polish Academy of SciencesKasprzaka 44/5201-224 WarsawPoland Department of Metallurgical and Materials Engineering Karamanoglu Mehmetbey University70200 KaramanTurkey Department of Chemistry Faculty of ScienceKing Khalid UniversityAbha 61413P.O.Box 9004Saudi Arabia Department of Physics Indian Institute of Technology RoorkeeRoorkeeHaridwarUttarakhand 247667India Department of Solar Energy School of TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia

Development of novel materials with desirable properties remains at the forefront of modern scientific *** learning(ML),a branch of artificial intelligence,has recently emerged as a powerful technology in optoelectronic devices for the prediction of various properties and rational design of *** halide perovskites(MHPs)have been at the centre of attraction owing to their outstanding photophysical properties and rapid development in solar cell ***,the application of ML in the field of MHPs is also getting much attention to optimize the fabrication process and reduce the cost of ***,we comprehensively reviewed different applications of ML in the designing of both MHP absorber layers as well as complete perovskite solar cells(PSCs).At the end,the challenges of ML along with the possible future direction of research are *** believe that this review becomes an indispensable roadmap for optimizing materials composition and predicting design strategies in the field of perovskite technology in the future.

关键词： Machine learning Metal halide perovskites Perovskite solar cell Lead free perovskites

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Intrinsic carrier multiplication in layered Bi_(2)O_(2)Se avalanche photodiodes with gain bandwidth product exceeding 1 GHz

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Nano Research 2021年第6期14卷 1961-1966页

作者： Vinod K.Sangwan Joohoon Kang David Lam J.Tyler Gish Spencer A.Wells Jan Luxa James P.Male GJeffrey Snyder Zdenek Sofer Mark C.Hersam Department of Materials Science and Engineering Northwestern UniversityEvanstonIL60208USA Department of Inorganic Chemistry University of Chemistry and Technology PragueTechnicka 516628Prague 6Czech Republic Department of Chemistry Northwestern UniversityEvanstonIL60208USA Department of Electrical and Computer Engineering Northwestern UniversityEvanstonIL60208USA

Emerging layered semiconductors present multiple advantages for optoelectronic technologies including high carrier mobilities,strong light-matter interactions,and tunable optical absorption and ***,metal-semiconductor-metal avalanche photodiodes(APDs)are fabricated from Bi2O2Se crystals,which consist of electrostatically bound[Bi2O2]2+and[Se]2−*** resulting APDs possess an intrinsic carrier multiplication factor up to 400 at 7 K with a responsivity gain exceeding 3,000 A/W and bandwidth of~400 kHz at a visible wavelength of 515.6 nm,ultimately resulting in a gain bandwidth product exceeding 1 *** to exceptionally low dark currents,Bi2O2Se APDs also yield high detectivities up to 4.6×1014 Jones.A systematic analysis of the photocurrent temperature and bias dependence reveals that the carrier multiplication process in Bi2O2Se APDs is consistent with a reverse biased Schottky diode model with a barrier height of~44 meV,in contrast to the charge trapping extrinsic gain mechanism that dominates most layered semiconductor *** this manner,layered Bi2O2Se APDs provide a unique platform that can be exploited in a diverse range of high-performance photodetector applications.

关键词： layered semiconductor photodetector high-frequency Schottky diode impact ionization

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Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse

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IEEE Transactions on Mobile Computing 2025年

作者： Liu, Guangyuan Du, Hongyang Wang, Jiacheng Niyato, Dusit Kim, Dong In Nanyang Technological University College of Computing and Data Science Energy Research Institute @ NTU Interdisciplinary Graduate Program Singapore University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Nanyang Technological University College of Computing and Data Science Singapore Sungkyunkwan University Department of Electrical and Computer Engineering Korea Republic of

The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user experience. However, generating these images, especially through Generative Diffusion Models (GDMs), in mobile edge computing environments presents significant challenges due to the limited computing resources of edge devices and the dynamic nature of wireless networks. This paper proposes a novel framework that integrates contract-inspired contest theory, Deep Reinforcement Learning (DRL), and GDMs to optimize image generation in these resource-constrained environments. The framework addresses the critical challenges of resource allocation and semantic data transmission quality by incentivizing edge devices to efficiently transmit high-quality semantic data, which is essential for creating realistic and immersive images. The use of contest and contract theory ensures that edge devices are motivated to allocate resources effectively, while DRL dynamically adjusts to network conditions, optimizing the overall image generation process. Experimental results demonstrate that the proposed approach not only improves the quality of generated images but also achieves superior convergence speed and stability compared to traditional methods. This makes the framework particularly effective for optimizing complex resource allocation tasks in mobile edge Metaverse applications, offering enhanced performance and efficiency in creating immersive virtual environments. © 2002-2012 IEEE.

关键词： Resource allocation

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Development of Flexible Sendust Composite Sheets with Enhanced Magnetic Permeability for Microwave Absorbers and Antennas

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IEEE Transactions on Magnetics 2025年

作者： Whalen, Matthew P. Plouff, David T. Shevchenko, Nicholas B. Mirotznik, Mark Xiao, John Q. University of Delaware Quantum Science and Engineering Program NewarkDE19716 United States University of Delaware Department of Physics and Astronomy NewarkDE19716 United States University of Delaware Center for Composite Materials NewarkDE19716 United States University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States

The demand for high-frequency soft magnetic composites with elevated permeability and flexibility is growing for applications in microwave absorbers and magnetodielectric antennas. However, balancing high permeability with mechanical flexibility remains challenging. This study presents flexible Sendust (FeSiAl) composite sheets, fabricated with a hot-pressing technique that aligns flakes within an acrylic rubber and epoxy resin matrix. The alignment significantly enhances relative permeability at high frequencies, achieving single-layer film properties of μr' = 14.8 and μr"= 20.4 at 1 GHz, alongside high saturation magnetization (118 eμg) and high hesitivity (44.7 kΩ m-1), outperforming commonly used materials such as NiZn ferrite. Our method supports customizable thickness without sacrificing permeability, establishing a versatile platform for advanced conformal microwave absorber and antenna applications. © 2025 IEEE.

关键词： Saturation magnetization

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Mixed Delay/Nondelay Embeddings Based Neuromorphic Computing with Patterned Nanomagnet Arrays 9

Mixed Delay/Nondelay Embeddings Based Neuromorphic Computing...

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9th Annual IEEE International Conference on Rebooting Computing, ICRC 2024

作者： Ti, Changpeng Hassan, Usman Vatsavai, Sairam Sri McCarter, Margaret Vasdev, Aastha An, Jincheng Achinuq, Barat Welp, Ulrich Cheung, Sen-Ching Thakkar, Ishan G. Todd Hastings, J. Department of Electrical and Computer Engineering University of Kentucky LexingtonKY40506 United States Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Materials Science Division Argonne National Laboratory LemontIL60439 United States Department of Physics University of Kentucky LexingtonKY40506 United States

ISBN: (纸本)9798331541279

Patterned nanomagnet arrays (PNAs) have been shown to exhibit a strong geometrically frustrated dipole interaction. Some PNAs have also shown emergent domain wall dynamics. Previous works have demonstrated methods to physically probe these magnetization dynamics of PNAs to realize neuromorphic reservoir systems that exhibit chaotic dynamical behavior and high-dimensional nonlinearity. These PNA reservoir systems from prior works leverage echo state properties and linear/nonlinear short-term memory of component reservoir nodes to map and preserve the dynamical information of the input time-series data into nondelay spatial embeddings. Such mappings enable these PNA reservoir systems to imitate and predict/forecast the input time series data. However, these prior PNA reservoir systems are based solely on the nondelay spatial embeddings obtained at component reservoir nodes. As a result, they require a massive number of component reservoir nodes, or a very large spatial embedding (i.e., high-dimensional spatial embedding) per reservoir node, or both, to achieve acceptable imitation and prediction accuracy. These requirements reduce the practical feasibility of such PNA reservoir systems. To address this shortcoming, we present a mixed delay/nondelay embeddings-based PNA reservoir system. Our system uses a single PNA reservoir node with the ability to obtain a mixture of delay/nondelay embeddings of the dynamical information of the time-series data applied at the input of a single PNA reservoir node. Our analysis shows that when these mixed delay/nondelay embeddings are used to train a perceptron at the output layer, our reservoir system outperforms existing PNA-based reservoir systems for the imitation of NARMA 2, NARMA 5, NARMA 7, and NARMA 10 time series data, and for the short-term and long-term prediction of the Mackey Glass time series data. © 2024 IEEE.

关键词： Time series

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Measurement of Synthetic-Dimension Band Structures in Silicon Coupled Ring Resonators 16

Measurement of Synthetic-Dimension Band Structures in Silico...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Zhang, Ruming Li, Liucun Kamata, Mikiya Baba, Toshihiko Ozawa, Tomoki Ota, Yasutomo Iwamoto, Satoshi Research Center for Advanced Science and Technology The University of Tokyo Tokyo153-8904 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan Keio University Department of Applied Physics and Physico-Informatics Yokohama223-8533 Japan

We fabricated integrated silicon coupled-ring resonators and measured photonic band structures for synthetic frequency lattices with different configurations. A phase difference between two modulation signals introduc... 详细信息

ISBN: (纸本)9798350372076

关键词： Silicon photonics

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Emergent Ferromagnetism in CaRuO₃/CaMnO₃ (111)-Oriented Superlattices

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Nano Letters 2024年第8期24卷 2567-2573页

作者： Kane, Margaret Bhandari, Churna Holtz, Megan E. Balakrishnan, Purnima P. Grutter, Alexander J. Fitzsimmons, Michael Yang, Chao-Yao Satpathy, Sashi Paudyal, Durga Suzuki, Yuri Department of Materials Science and Engineering Stanford University Stanford 94305 CA United States Ames National Laboratory Iowa State University Ames 50011 IA United States Metallurgical and Materials Engineering Colorado School of Mines Golden 80401 CO United States NIST Center for Neutron Research National Institute of Standards and Technology Gaithersburg 20899 MD United States Neutron Scattering Division Oak Ridge National Laboratory Oak Ridge 37830 TN United States Department of Material Science and Engineering National Yang Ming Chiao Tung University Hsinchu City 30100 Taiwan Department of Physics & Astronomy University of Missouri Columbia 65211 MO United States Department of Applied Physics Stanford University Stanford 94305 CA United States Geballe Laboratory for Advanced Materials Stanford University Stanford 94305 CA United States Department of Electrical and Computer Engineering Iowa State University Ames 50011 IA United States

The boundary between CaRuO3 and CaMnO3 is an ideal test bed for emergent magnetic ground states stabilized through interfacial electron interactions. In this system, nominally antiferromagnetic and paramagnetic materi... 详细信息

The boundary between CaRuO₃ and CaMnO₃ is an ideal test bed for emergent magnetic ground states stabilized through interfacial electron interactions. In this system, nominally antiferromagnetic and paramagnetic materials combine to yield interfacial ferromagnetism in CaMnO₃ due to electron leakage across the interface. In this work, we show that the crystal symmetry at the surface is a critical factor determining the nature of the interfacial interactions. Specifically, by growing CaRuO₃/CaMnO₃ heterostructures along the (111) instead of the (001) crystallographic axis, we achieve a 3-fold enhancement of the magnetization and involve the CaRuO₃ layers in the ferromagnetism, which now spans both constituent materials. The stabilization of a net magnetic moment in CaRuO₃ through strain effects has been long-sought but never consistently achieved, and our observations demonstrate the importance of interface engineering in the development of new functional heterostructures. © 2024 American Chemical Society.

关键词： complex oxides emergent magnetism manganites ruthenatess superlattices

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