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Continuous-time digital twin with analog memristive neural ordinary differential equation solver

Science advances 2025年第22期11卷 eadr7571页

作者： Hegan Chen Jichang Yang Jia Chen Songqi Wang Shaocong Wang Dingchen Wang Xinyu Tian Yifei Yu Xi Chen Yinan Lin Qifan Zhu Yangu He Xiaoshan Wu Yi Li Xinyuan Zhang Ning Lin Meng Xu Xumeng Zhang Xiaojuan Qi Zhongrui Wang Han Wang Dashan Shang Qi Liu Kwang-Ting Cheng Ming Liu Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China. School of Microelectronics Southern University of Science and Technology Shenzhen 518055 China. Center for Advanced Semiconductors and Integrated Circuits the University of Hong Kong Hong Kong China. Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong China. School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan 430074 China. State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai 200433 China. State Key Lab of Fabrication Technologies for Integrated Circuits and Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China. University of Chinese Academy of Sciences Beijing 100049 China.

Digital twins, which replicate real-world entities through computational models, are transforming manufacturing and automation. While recent advances in machine learning have enabled data-driven digital twin development using discrete-time data and finite-depth models on digital hardware, these approaches face significant limitations. They struggle to capture continuous-time dynamics and model complex systems, and suffer from substantial time and energy overheads due to physically separated storage and processing as well as frequent analog-digital (A/D) conversions. Here, we propose a memristive neural ordinary differential equation (ODE) solver for digital twins. Our approach is intrinsically time-continuous using infinite-depth neural networks to model complex dynamics. Fully analog memristor arrays collocate storage and computation, addressing the von Neumann bottleneck and reducing A/D conversion requirements. We experimentally validate our solver on digital twins of HP variable-resistor model and Lorenz96 dynamics, demonstrating a 166.5-fold/369.3-fold speedup and a 499.0-fold/673.9-fold improvement in energy efficiency, respectively. This work paves the way to future digital twins for Industry 4.0.

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Topologically Protected Entanglement Emitters

Topologically Protected Entanglement Emitters

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CLEO: QELS_Fundamental Science, QELS 2022

作者： Dai, Tianxiang Ao, Yutian Bao, Jueming Mao, Jun Chi, Yulin Fu, Zhaorong You, Yilong Chen, Xiaojiong Zhai, Chonghao Tang, Bo Yang, Yan Li, Zhihua Yuan, Luqi Gao, Fei Lin, Xiao Thompson, Mark G. O'Brien, Jeremy L. Li, Yan Hu, Xiaoyong Gong, Qihuang Wang, Jianwei State Key Laboratory for Mesoscopic Physics School of Physics Peking University Beijing100871 China Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Quantum Engineering Technology Labs H. H. Wills Physics Laboratory Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom Department of Physics The University of Western Australia Perth6009 Australia Frontiers Science Center for Nano-Optoelectronics Collaborative Innovation Center of Quantum Matter Peking University Beijing100871 China Collaborative Innovation Center of Extreme Optics Shanxi University Shanxi Taiyuan030006 China Peking University Yangtze Delta Institute of Optoelectronics Jiangsu Nantong226010 China

ISBN: (纸本)9781557528209

We report topologically-protected entanglement emitters, that emit topological Einstein-Podolsky-Rosen state and multiphoton entangled state from a plug-and-play silicon-photonic chip in ambient conditions. The device emulating a photonic anomalous Floquet insulator allows the generation of four-photon topological entangled states at nontrivial edge modes. © Optica Publishing Group 2022, © 2022 The Author(s)

关键词： Silicon photonics

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In-Situ Fluorine-Doped Znsno Thin Film and Thin-Film Transistor

SSRN

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SSRN 2023年

作者： Yin, Xuemei Lin, Delang Zhong, Wei Deng, Sunbin Xu, Yuming Chen, Yayi Lu, Lei Li, Guijun Kwok, Hoi Sing Li, Yi Chen, Rongsheng The School of artificial intelligence Zhuhai City Polytechnic College Zhuhai China The School of Microelectronics South China University of Technology Guangzhou China The School of Integrated Circuits Guangdong University of Technology Guangzhou China Purdue University West Lafayette United States The State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The Hong Kong University of Science and Technology Hong Kong Zhuhai Southern Integrated Circuit Design Service Center Zhuhai China Peking University China

In this paper, in-situ fluorine-doped ZnSnO (ZTO:F) thin films prepared by co-sputtering are proposed. It was found that the F had been successfully introduced into the ZTO thin films and distributed uniformly in the bulk. The corresponding top-contact bottom-gated ZTO:F thin film transistors (TFTs) were fabricated with an annealing temperature of 350 oC. The fabricated TFTs exhibit a field-effect mobility of 14.2 cm2V-1s-1, on-off ratio of over 109, and subthreshold swing (SS) as low as 87 mV/decade due to the incorporation of F. In addition, the bias stability of fabricated TFTs was also examined and the Vth shifts under negative gate bias stress are not more than ±0.1V even without any passivation. It is expected that the In-free ZTO:F amorphous oxide semiconductor and the corresponding TFTs have potential for low-cost and environmentally safe fabrication. © 2023, The Authors. All rights reserved.

关键词： Thin film transistors

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Erratum to: CMN: a co-designed neural architecture search for efficient computing-in-memory-based mixture-of-experts

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Science China Information Sciences 2024年第11期67卷 1-1页

作者： Han, Shihao Liu, Sishuo Du, Shucheng Li, Mingzi Ye, Zijian Xu, Xiaoxin Li, Yi Wang, Zhongrui Shang, Dashan Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong China ACCESS-AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong China Key Lab of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Beijing China Laboratory of Microelectronics Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Microelectronics Southern University of Science and Technology Shenzhen China

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Aligned monolayer MoS2 ribbons growth on sapphire substrate via NaOH-assisted chemical vapor deposition

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Science China Materials 2020年第6期63卷 1065-1075页

作者： Shike Hu Jing Li Xiaoyi Zhan Shuang Wang Longbiao Lei Yijian Liang He Kang Yanhui Zhang Zhiying Chen Yanping Sui Da Jiang Guanghui Yu Songang Peng Zhi Jin Xinyu Liu State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Microwave Devices and Integrated Circuits Department Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China

This study reports the growth of aligned monolayer molybdenum disulfide(MoS2)ribbons on a sapphire substrate via NaOH-assisted chemical vapor *** length of MoS2 ribbon is up to 400μ*** MoS2 ribbon has excellent single crystal properties,a carrier mobility of^150 cm^2V^-1s^-1,and a optical response of 103 mA W^-1 at a wavelength of 550 *** growth model of MoS2 ribbons was *** reacts with MoO3 to form sodium molybdate droplets,which increase the fluidity of the molybdenum source on the substrate,realizing the vapor-liquid-solid growth of MoS2 on *** monolayer MoS2 ribbons have two kinds of arrangements on the sapphire substrate,one is the oriented growth affected by the interlayer van der Waals force and the lattice,and the other is the aligned growth constrained by the sapphire *** results promote the basic research and device applications of MoS2,and introduce a new way of synthesizing other one dimensional(1D)and 2D nanostructures.

关键词： MoS2 aligned ribbons vapor-liquid-solid step epitaxy

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Wideband Antenna-in-Package Dielectric Resonator Antenna Using High-Resistance Silicon Substrate for Satellite Communications

Wideband Antenna-in-Package Dielectric Resonator Antenna Usi...

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UK, Europe, China Millimeter Waves and THz Technology Workshop (UCMMT)

作者： Ning-Shuang Fang Qiang Wang Li-Tao Chen Kwok Wa Leung Nan Yang Kai Lu Guodong Su Yunliang Long School of Electronics and Information Technology (School of Microelectronics) and Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-Sen University Guangzhou China Comba Telecom Technology (Guangzhou) Limited Department of Electronic Engineering State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong China Information and Communication Technology Center CityU Shenzhen Research Institute Shenzhen China Zhejiang Provincial Laboratory of Integrated Circuit Design Hangzhou Dianzi University Hangzhou China

A wideband antenna-in-package (AiP) dielectric resonator antenna (DRA) is presented in this paper. Air vias and metallic vias are used to form the equivalent DRA. To obtain a wideband design, a slot-loaded DRA mode and a fundamental DRA mode are simultaneously excited. Two metal strips are attached on the top surface for better impedance matching. To verify the design idea, a prototype is designed with a simulated bandwidth larger than 20 %. It should be mentioned that the presented design is compatible with silicon-based process, and thus suitable for AiP and heterogeneous integration systems.

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Third-Order Low-Pass Filters for Limiting the Signal Spectrum at the Differential Input of the Analog/Digital Converters

Third-Order Low-Pass Filters for Limiting the Signal Spectru...

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International Conference for Young Scientists on Issues of Physics and Technology in Science, Power Industry and Medicine 2019, IPTSPIM 2019

作者： Yu Denisenko, D. Prokopenko, N.N. Butyrlagin, N.V. Department of Information System and Radio Engineering Don State Technical University Gagarin Sq. 1 Rostov-on-Don344000 Russia Department of Automatic Control Systems Southern Federal University Bolshaya Sadovaya St. 33 Rostov-on-Don344000 Russia Institute for Design Problems in Microelectronics of Russian Academy of Sciences Institute for Design Problems in Microelectronics Ras Sovetskaya St. 3 Zelenograd124681 Russia

Two new architectures of the third-order low-pass filters (LPF) based on differential (Op-Amp) and differential difference amplifiers (DDA) with a paraphase output are compared. This architectures designed for practical use as anti-aliasing filters in analog-to-digital converters of sensor signals of various physical quantities. The basic equations of the developed LPF modifications that make possible to perform their parametric synthesis are given. The computer simulation results are presented, which show that the LPFs under consideration provide the guaranteed frequency response (FR) attenuation outside the bandwidth being implemented on Op-Amps by Analog Device (AD8132) and Texas Instruments (THS4131). © Published under licence by IOP Publishing Ltd.

关键词： Low pass filters

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Emerging Internet of Things driven carbon nanotubes-based devices

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Nano Research 2022年第5期15卷 4613-4637页

作者： Shu Zhang Jinbo Pang Yufen Li Feng Yang Thomas Gemming Kai Wang Xiao Wang Songang Peng Xiaoyan Liu Bin Chang Hong Liu Weijia Zhou Gianaurelio Cuniberti Mark HRümmeli Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of Shandong Institute for Advanced Interdisciplinary Research(iAIR)University of JinanJinan 250022China Department of Chemistry Guangdong Provincial Key Laboratory of CatalysisSouthern University of Science and TechnologyShenzhen 518055China Leibniz Institute for Solid State and Materials Research Dresden P.O.Box 270116Dresden D-01171Germany State Key Laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong University27 Shandanan RoadJinan 250100China School of Electrical Engineering Qingdao UniversityQingdao 266071China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences 1068 Xueyuan AvenueShenzhen University TownShenzhen 518055China High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China School of Chemistry and Chemical Engineering University of JinanJinan 250022China College of Energy Soochow Institute for Energy and Materials InnovationsSoochow UniversitySuzhou 215006China Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhou 215006China Centre of Polymer and Carbon Materials Polish Academy of SciencesM.Curie Sklodowskiej 34Zabrze 41-819Poland Institute of Environmental Technology(CEET) VSB-Technical University of Ostrava17.Listopadu 15Ostrava 70833Czech Republic Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics D

Carbon nanotubes(CNTs)have attracted great attentions in the field of electronics,sensors,healthcare,and energy *** emerging applications have driven the carbon nanotube research in a rapid ***,the structure control over CNTs has inspired an intensive research vortex due to the high promises in electronic and optical device ***,this in-depth review is anticipated to provide insights into the controllable synthesis and applications of high-quality ***,the general synthesis and post-purification of CNTs are briefly ***,the state-of-the-art electronic device applications are discussed,including field-effect transistors,gas sensors,DNA biosensors,and pressure ***,the optical sensors are delivered based on the *** addition,energy applications of CNTs are discussed such as thermoelectric energy ***,future opportunities are proposed for the Internet of Things(IoT)oriented sensors,data processing,and artificial intelligence.

关键词： carbon nanotubes electronics sensors electronic skins Internet of Things artificial intelligence

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Recent progress of integrated circuits and optoelectronic chips

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Science China(Information Sciences) 2021年第10期64卷 103-135页

作者： Yue HAO Shuiying XIANG Genquan HAN Jincheng ZHANG Xiaohua MA Zhangming ZHU Xingxing GUO Yahui ZHANG Yanan HAN Ziwei SONG Yan LIU Ling YANG Hong ZHOU Jiangyi SHI Wei ZHANG Min XU Weisheng ZHAO Biao PAN Yangqi HUANG Qi LIU Yimao CAI Jian ZHU Xin OU Tiangui YOU Huaqiang WU Bin GAO Zhiyong ZHANG Guoping GUO Yonghua CHEN Yong LIU Xiangfei CHEN Chunlai XUE Xingjun WANG Lixia ZHAO Xihua ZOU Lianshan YAN Ming LI School of Microelectronics Xidian University State Key Laboratory of Integrated Service Networks Xidian University National Integrated Circuit Innovation Center School of Microelectronics Fudan University School of Integrated Circuit Science and Engineering Beihang University China Center for Information Industry Development Frontier Institute of Chip and System Fudan University Institute of Microelectronics Peking University Nanjing Electronic Devices Institute State Key Laboratory of Functional Material for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Institute of Microelectronics Tsinghua University Center for Carbon-based Electronics Department of Electronics Peking University CAS Key Laboratory of Quantum Information University of Science and Technology of China CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Origin Quantum Computing Company Limited Key Laboratory of Flexible Electronics & Institute of Advanced Materials Nanjing Tech University State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China National Laboratory of Solid State Microstructures & College of Engineering and Applied Sciences Nanjing University State Key Laboratory on Integrated Optoelectronics Institute of Semiconductors Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University School of Electrical and Electronic Engineering Tiangong University Center for Information Photonics and Communications School of Information Science and TechnologySouthwest Jiaotong University School of Electronic Electrical and Communication Engineering

Integrated circuits(ICs) and optoelectronic chips are the foundation stones of the modern information society. The IC industry has been driven by the so-called "Moore's law" in the past 60 years, and now has entered the post Moore's law era. In this paper, we review the recent progress of ICs and optoelectronic chips. The research status, technical challenges and development trend of devices, chips and integrated technologies of typical IC and optoelectronic chips are focused on. The main contents include the development law of IC and optoelectronic chip technology, the IC design and processing technology, emerging memory and chip architecture, brain-like chip structure and its mechanism, heterogeneous integration, quantum chip technology, silicon photonics chip technology, integrated microwave photonic chip, and optoelectronic hybrid integrated chip.

关键词： integrated circuit semiconductor science and technology optoelectronic device and chip photonic integrated circuit wide bandgap semiconductors silicon photonics hybrid integration quantum chip integrated microwave photonic photonic neural computing

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Random memristor-based dynamic graph CNN for efficient point cloud learning at the edge

npj Unconventional Computing

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npj Unconventional Computing 2024年第1期1卷 1-9页

作者： Yifei Yu Shaocong Wang Meng Xu Bo Wang Jichang Yang Songqi Wang Yue Zhang Xiaoshan Wu Hegan Chen Dingchen Wang Xi Chen Ning Lin Xiaojuan Qi Zhongrui Wang Woyu Zhang Dashan Shang Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong China School of Microelectronics Southern University of Science and Technology Shenzhen 518055 China Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China University of Chinese Academy of Sciences Beijing 100049 China

The broad integration of 3D sensors into devices like smartphones and AR/VR headsets has led to a surge in 3D data, with point clouds becoming a mainstream representation method. Efficient real-time learning of point cloud data on edge devices is crucial for applications such as autonomous vehicles and embodied AI. Traditional machine learning models on digital processors face limitations, with software challenges like high training complexity, and hardware challenges such as large time and energy overheads due to von Neumann bottleneck. To address this, we propose a software-hardware co-designed random memristor-based dynamic graph CNN (RDGCNN). Software-wise, we transform point cloud into graph, and propose random EdgeConv for efficient hierarchical and topological features extraction. Hardware-wise, leveraging memristor’s intrinsic stochasticity and in-memory computing capability, we achieve significant reductions in training complexity and energy consumption. RDGCNN demonstrates high accuracy and efficiency across various point cloud tasks, paving the way for future edge 3D vision.

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