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13th Asia-Pacific International Symposium on Electromagnetic Compatibility and Technical Exhibition, APEMC 2022

作者： Fang, Lidan Li, Yan Xu, Shaojie Jin, Ning Yu, Heyuan Sun, Zhe Lei, Xiaoyong Huo, Shuyun Li, Erping Li, Bingheng China Jiliang University Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province Zhejiang China Hebei University of Technology College of Electronics & Information Engineering Tianjin China Key Laboratory of Advanced Micro-Nano Electronic Devices & Smart Systems and Applications Zhejiang China

ISBN: (数字)9781665416719

ISBN: (纸本)9781665416719

In this paper, the Izhikevich neuron model is used to simulate the spike signal, and a complete unit-cell equivalent circuit model of the RRAM-based crossbar array including parasitic effects is proposed. By changing the interconnection width, array size, and the RRAM resistance value, influences of the interconnection structure on the transmission characteristics of spike signals in the RRAM-based crossbar array for neuromorphic chips are analyzed. The simulation results show that the IR drop and crosstalk caused by the parasitic RLC components may be the main noise source that changes the operating voltage. Therefore, when the demand is met, the accuracy can be improved by changing the above-mentioned factors. © 2022 IEEE.

关键词： RRAM

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Rapid FSS Design Method Based on Fourier Transform

Rapid FSS Design Method Based on Fourier Transform

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Qiu, Huanran Han, Jiaqi Feng, Qiang Xi, Rui Li, Ying Chen, Hongsheng Zheng, Bin Li, Long Xidian University Hangzhou Institute of Technology Hangzhou311200 China Xidian University Key Laboratory of High-Speed Circuit Design EMC of Ministry of Education School of Electronic Engineering Xi'an710071 China The Electromagnetics Academy Zhejiang University Zhejiang University International Joint Innovation Center Haining314400 China Key Lab of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua China Institute of Zhejiang University Zhejiang University Jinhua321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing312000 China

ISBN: (纸本)9798350375909

This article presents a rapid frequency selective surface (FSS) design method based on Fourier transform. The method aims to overcome the complexity and reduce the time consumption associated with the massive input simulation datasets in traditional design processes, providing an efficient and automated design solution. By introducing Fourier transform, the amount of simulation datasets can be significantly simplified, enhancing the speed and accuracy of neural network training. The method improves precision and speed in handling tasks with multiple parameters, offering an effective tool for fast FSS design. With the aid of neural network construction, users only need to input the desired simulation result curve, and the neural network model will quickly output optimal FSS structure parameters. This approach ensures design accuracy and stability while greatly increasing the efficiency of FSS design. © 2024 IEEE.

关键词： Neural network models

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Design and Analysis of a Novel Miniaturized Ultra-thin Quad-band Metamaterial Absorber 13

Design and Analysis of a Novel Miniaturized Ultra-thin Quad-...

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13th Asia-Pacific International Symposium on Electromagnetic Compatibility and Technical Exhibition, APEMC 2022

作者： Sun, Zhe Yu, Heyuan Lei, Xiaoyong Huo, Shuyun Li, Yan Fang, Lidan Xu, Shaojie Li, Erping Li, Bingheng Hebei University of Technology College of Electronics & Information Engineering Tianjin China China Jiliang University Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province Zhejiang China Zhejiang University Key Laboratory of Advanced Micro-Nano Electronic Devices & Smart Systems and Applications Zhejiang China

ISBN: (数字)9781665416719

ISBN: (纸本)9781665416719

Conventional metamaterial absorber (MMA) are too large to be used in miniaturized devices such as chip systems. To solve this problem, a miniature ultra-thin MMA with four absorption peaks is proposed in this paper. The proposed MMA has a thickness of only 0.2 mm and achieves 99.6%, 97.3%, 99.8% and 99.1% absorption at 12.04 GHz, 17.26 GHz, 21.04 GHz and 23.94 GHz. The paper also analyzes the influence of parameters of the proposed MMA on the absorption performance and proves that it has a certain tunability of the absorption band. By comparing with other MMA work, the MMA proposed in this paper achieves the miniaturization of the structure while ensuring the number of absorption frequency points. This advantage provides a new solution to solve the problem of difficult loading of electromagnetic shielding structures in miniaturized chip architectures. © 2022 IEEE.

关键词： Electromagnetic shielding

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Hybrid surface waves in twisted anisotropic heterometasurfaces

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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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Analysis of Neural Spike Signal Transmission Characteristics in 3-D Heterogeneous Integration 13

Analysis of Neural Spike Signal Transmission Characteristics...

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13th Asia-Pacific International Symposium on Electromagnetic Compatibility and Technical Exhibition, APEMC 2022

作者： Yu, Heyuan Sun, Zhe Lei, Xiaoyong Huo, Shuyun Li, Yan Fang, Lidan Xu, Shaojie Li, Erping Li, Bingheng Hebei University of Technology College of Electronics & Information Engineering Tianjin China China Ji-Liang University Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province Zhejiang China Zhejiang University Key Laboratory of Advanced Micro-Nano Electronic Devices & Smart Systems and Applications Zhejiang China

ISBN: (数字)9781665416719

ISBN: (纸本)9781665416719

With the continuous development of artificial intelligence, spiking neuromorphic chip is favored for its architectural advantages of memory computing integration. The neural spike signal is used as the transmission signal in the spiking neuromorphic chip, and its completely different characteristics from the digital pulse signal will inevitably lead to different signal integrity problems. In this paper, we model the common Through Silicon Via (TSV) and the interconnection structure model of redistribution layers (RDL) in 3-D heterogeneous integration, analyze the insertion loss and transient impedance of the two structures respectively, and finally perform time-domain transient simulations with neural spike signals of different rising edges in the two models to observe their transmission characteristics. The simulation results show that neural spike signals with shorter rising edges can generate more serious signal integrity problems such as loss, reflection, and delay in the RDL-TSV interconnection structure. © 2022 IEEE.

关键词： Time domain analysis

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Extended-localized transition in diffusive quasicrystals

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Physical Review Applied 2024年第6期21卷 064035-064035页

作者： Zhoufei Liu Pei-Chao Cao Ying Li Jiping Huang Department of Physics State Key Laboratory of Surface Physics and Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education) State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center International Joint Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Shaoxing Institute of Zhejiang University

Compared with periodic systems, quasicrystals without translational invariance exhibit unexpected localization properties. The extended-localized transition in quasicrystals has been observed in both quantum and classical wave systems. However, its manifestation in diffusion systems, which serve as novel platforms for exploring phases of matter in condensed-matter physics, remains unexplored. Here we present an implementation of the extended-localized transition in a diffusive quasicrystal based on a coupled-ring chain structure. By modulating the thermal conductivities of the rings, we obtain the diffusive one-dimensional Aubry-André-Harper (AAH) model, which exhibits an extended-localized transition. Thanks to the ring-shaped chain, we clearly demonstrate the extended-localized transition under uniform excitation through temperature-field simulations. For the localized state, the temperature field clearly demonstrates a phenomenon of multiple localization centers, which has no counterpart in wave systems. We also quantitatively investigate the temperature evolution and size effect of this transition. Furthermore, local excitation is used to demonstrate the temperature field for both the extended state and the localized state. Besides, we implement the non-Hermitian diffusive AAH model by rotating the rings, whose temperature field shows a phenomenon of moving multiple localization centers in the localized phase. Finally, we give experimental suggestions for the diffusive AAH model and propose a potential application named the “double-trace distributed generator.” Our results should facilitate the design of flexible thermal devices and efficient heat management.

关键词： Anderson localization Diffusion Heat transfer Skin effect Thermoelectric effects Disordered systems Non-Hermitian systems Quasicrystals

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ESD pulse width effect on RC-triggered NMOS with power on or off 1

ESD pulse width effect on RC-triggered NMOS with power on or...

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1st Annual International EOS/ESD Symposium on Design and System, IEDS 2020

作者： Zhu, Xinyu Yu, Fangjun Shen, Hongyu Xu, Zekun Dong, Shurong Key Laboratory of Micro-nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science Electronic Engineering Zhejiang University Hangzhou310027 China

The robustness of RC-triggered NMOS clamp in 28nm process is significantly reduced under the condition of long pulse width and power on. The simulation results show that the device faces the risk of turning off in the... 详细信息

ISBN: (纸本)9781585373284

关键词： Simulation Turning Electrostatic discharges Robustness Delays Clamps Transient analysis

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Design and Manipulation of Electromagnetic Metasurface Based on Bidirectional Deep Neural Network

Design and Manipulation of Electromagnetic Metasurface Based...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Qun Ren Yongjing Dang Xiaouyue Wu Keck-Voon Ling Wei E. I. Sha Yanwei Pang School of Electrical and Information Engineering Tianjin University Tianjin China Key Laboratory of Micro-Nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science and Electronic Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

In the current research field, metasurface technology has attracted much attention because of its excellent electromagnetic wave manipulation ability, and is widely used in the field of micro and nano photonics. In the lower frequency band, the megahertz band, metasurface technology also shows great potential for development, especially in the field of medical imaging, which is becoming increasingly important. However, the design process of metasurfaces is intricate and computationally costly. To tackle this challenge, this paper introduces a deep learning-based approach for the electromagnetic control and design of metasurfaces in the megahertz frequency band. By developing a Deep Neural Network (DNN), we are able to rapidly predict the electromagnetic response of metasurfaces, substantially reducing the time and memory consumption required for simulations. Moreover, the application of deep learning technology in metasurface design extends beyond forward prediction to inverse design, allowing for the prediction of metasurface structures that meet specific electromagnetic response requirements from the design objectives. This method overcomes the limitations of traditional design methods, offering new possibilities for the advancement of metasurface technology.

关键词： Electric potential Design methodology Memory management Electromagnetic scattering Artificial neural networks Predictive models Metasurfaces Electromagnetics Frequency control Photonics

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Design of a Double-layer Miniaturized Metamaterial Absorber in 5G Millimeter-wave Band

Design of a Double-layer Miniaturized Metamaterial Absorber ...

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International Conference on microwave and Millimeter Wave Technology Proceedings

作者： Yunxi Wu Yan Li Erping Li Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province China Jiliang University Zhejiang China Key Laboratory of Advanced Micro-Nano Electronic Devices & Smart Systems and Applications Zhejiang University Zhejiang China

A double-layer miniaturized metamaterial absorber based on the indium-tin-oxide (ITO) resistive film in a 5G millimeter-wave band is proposed in this paper. Its core structure is implemented by two layers. The first layer is a glass substrate with ITO resistive film attached, and another ITO is attached to the FR-4 substrate in the second layer. The simulation results reveal that under the conditions of transverse electric or transverse magnetic polarization, the absorption efficiency of the designed structure exceeds 90% in the bandwidth of 23.3GHz ~ 35.2GHz, and reaches the peak of nearly 100% at the resonant point of 28GHz. Further analysis shows that the absorption performance of the incident angle from 0° to 40° can reach more than 90% in the operating frequency, which is relatively stable.

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EMI Radiation Prediction of Packages Based on Convolution Neural Network

EMI Radiation Prediction of Packages Based on Convolution Ne...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Xiaotian Yang Yan Li Erping Li Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province China Jiliang University Zhejiang China Key Laboratory of Advanced Micro-Nano Electronic Devices & Smart Systems and Applications Zhejiang University Zhejiang China

With the increase of the current operating frequency, the electromagnetic interference (EMI) problem of extra-highspeed electronic equipment and systems becomes more and more complex, and the traditional analysis and design methods cannot efficiently deal with the current EMI problems. Therefore, this paper proposes a method of predicting electromagnetic radiation using a two-dimensional (2-D) convolutional neural network (CNN) in deep learning. This method can quickly and accurately predict the maximum 3-m pin map (PINMAP) package radiation electric field. By comparing the prediction results with the full-wave simulation results, both results are in good agreement, and the CNN prediction time is at the millisecond level. Therefore, the method that can accurately and effectively predict the radiation value has been verified.

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