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A high precision two-axis GMR angular sensor manufactured by post-annealing

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Science China(Information Sciences) 2024年第6期67卷 465-466页

作者： Zitong ZHOU Zhiqiang CAO Shaohua YAN Xiaolong WANG Libo XIE Shiyang LU Dapeng ZHU Qunwen LENG Weisheng ZHAO School of integrated Circuit Science and Engineering Beihang University Beihang Qingdao Microelectronics research Institute Beihang University National Key lab of Spintronics Institute of International InnovationBeihang University

Angle sensors are widely used in numerous fields such as industry,military,medical care,and the Internet of Things(IoT)[1].Magnetoresistance angle sensors have become a mainstream approach for angle measurement becaus... 详细信息

关键词： Annealing

A survey on blockchain-enabled federated learning and its prospects with digital twin

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Digital Communications and Networks 2024年第2期10卷 248-264页

作者： Kangde Liu Zheng Yan Xueqin Liang Raimo Kantola Chuangyue Hu State Key lab on integrated Services Network School of Cyber EngineeringXidian UniversityXi'anChina Department of Communications and Networking Aalto UniversityEspooFinland Yangtze Delta Region Blockchain Technology research Institute JiaxingChina

Digital Twin(DT)supports real time analysis and provides a reliable simulation platform in the Internet of Things(IoT).The creation and application of DT hinges on amounts of data,which poses pressure on the application of Artificial Intelligence(AI)for DT descriptions and intelligent *** Learning(FL)is a cutting-edge technology that enables geographically dispersed devices to collaboratively train a shared global model locally rather than relying on a data center to perform model ***,DT can benefit by combining with FL,successfully solving the"data island"problem in traditional ***,FL still faces serious challenges,such as enduring single-point failures,suffering from poison attacks,lacking effective incentive *** the successful deployment of DT,we should tackle the issues caused by *** from industry and academia have recognized the potential of introducing Blockchain Technology(BT)into FL to overcome the challenges faced by FL,where BT acting as a distributed and immutable ledger,can store data in a secure,traceable,and trusted ***,to the best of our knowledge,a comprehensive literature review on this topic is still *** this paper,we review existing works about blockchain-enabled FL and visualize their prospects with *** this end,we first propose evaluation requirements with respect to security,faulttolerance,fairness,efficiency,cost-saving,profitability,and support for ***,we classify existing literature according to the functionalities of BT in FL and analyze their advantages and disadvantages based on the proposed evaluation ***,we discuss open problems in the existing literature and the future of DT supported by blockchain-enabled FL,based on which we further propose some directions for future research.

关键词： Digital twin Artificial intelligence Federated learning Blockchain

980 nm Near-Infrared Light-Emitting Diode Using All-Inorganic Perovskite Nanocrystals Doped with Ytterbium Ions

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Tsinghua Science and Technology 2024年第1期29卷 207-215页

作者： Zhenglan Ye Taoran Liu Dan Chen Yazhou Yang Jiayi Li Yaqing Pang Xiangquan Liu Yuhua Zuo Jun Zheng Zhi Liu Buwen Cheng State Key laboratory on integrated Optoelectronics Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Intelligent Network research Institute Zhejiang LabHangzhou 311100China

All-inorganic perovskite(CsPbX3)nanocrystals(NCs)have recently been widely investigated as versatile solution-processable light-emitting *** to its wide-bandgap nature,the all-inorganic perovskite NC Light-Emitting Diode(LED)is limited to the visible region(400-700 nm).A particularly difficult challenge lies in the practical application of perovskite NCs in the infrared-spectrum *** this work,a 980 nm NIR all-inorganic perovskite NC LED is demonstrated,which is based on an efficient energy transfer from wide-bandgap materials(CsPbCl3 NCs)to ytterbium ions(Yb3+)as an NIR emitter doped in perovskite *** optimized CsPbCl3 NC with 15 mol%Yb3+doping concentration has the strongest 980 nm photoluminescence(PL)peak,with a PL quantum yield of 63%.An inverted perovskite NC LED is fabricated with the structure of ITO/PEDOT:PSS/poly-TPD/CsPbCl3:15 mol%Yb3+NCs/TPBi/LiF/*** LED has an External Quantum Efficiency(EQE)of 0.2%,a Full Width at Half Maximum(FWHM)of 47 nm,and a maximum luminescence of 182 cd/m?.The introduction of Yb3+doping in perovskite NCs makes it possible to expand its working wavelength to near-infrared band for next-generation light sources and shows potential applications for optoelectronic integration.

关键词： perovskite nanocrystals rare-earth doping Light-Emitting Diode(LED) near-infrared optical interconnection

Highly sensitive flexible strain sensor based on the two-dimensional semiconductor tellurium with a negative gauge factor

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Science China(Information Sciences) 2024年第7期67卷 295-304页

作者： Jiarui HE Yusong QU Shengyao CHEN Cong WANG Lena DU Xiaoshan DU Yuanyuan ZHENG Guozhong ZHAO He TIAN College of Mathematics and Physics Beijing University of Chemical Technology School of integrated Circuits Tsinghua University Beijing China & The Beijing National Research Center for Information Science and Technology (BNRist)Tsinghua University CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology &University of Chinese Academy of Sciences Beijing Key lab of Terahertz Spectroscopy and Imaging Key Lab of Terahertz OptoelectronicsMinistry of Education Department of Physics Capital Normal University

research on flexible strain sensors has advanced rapidly in recent years, with particular attention being devoted to two-dimensional(2D) semiconductor materials owing to their exceptional mechanical and electrical properties that are conducive to sophisticated sensing performance. However, resistive strain sensors based on 2D semiconductor materials typically exhibit positive gauge factors(GF), while materials for strain sensors with a negative GF remain elusive. We have identified a trend of reduction in the band gap of the emerging 2D semiconductor material tellurium(Te) under strain in simulations reported in past research,and have observed a negative GF in the Te-based strain sensor. In this study, we combined Te with a flexible polyethylene terephthalate(PET) substrate to manufacture a flexible strain sensor with a significantly negative GF. The results of tests revealed that the Te-based strain sensor achieved an impressive maximum sensitivity of-139.7 within a small range of bending-induced strain(< 1%). Furthermore, it exhibited excellent linearity and good cyclic stability, and was successfully applied to monitor limb movements. The work here verifies the significant potential for the use of Te-based strain sensors in next-generation flexible electronics.

关键词： 2D semiconductor materials 2D tellurium flexibleelectronics strain sensors negative gauge factor high sensitivity

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10期67卷 100-114页

作者： Shihao HAN Sishuo LIU Shucheng DU Mingzi LI Zijian YE Xiaoxin XU Yi LI Zhongrui WANG Dashan SHANG Department of Electrical and Electronic Engineering The University of Hong Kong ACCESS-AI Chip Center for Emerging Smart Systems InnoHK Centers Key lab of Fabrication Technologies for integrated Circuits Chinese Academy of Sciences laboratory of Microelectronics Devices and integrated Technology Institute of MicroelectronicsChinese Academy of Sciences University of Chinese Academy of Sciences School of Microelectronics Southern University of Science and Technology

Artificial intelligence(AI) has experienced substantial advancements recently, notably with the advent of large-scale language models(LLMs) employing mixture-of-experts(MoE) techniques, exhibiting human-like cognitive skills. As a promising hardware solution for edge MoE implementations, the computing-in-memory(CIM) architecture collocates memory and computing within a single device, significantly reducing the data movement and the associated energy consumption. However, due to diverse edge application scenarios and constraints, determining the optimal network structures for MoE, such as the expert's location,quantity, and dimension on CIM systems remains elusive. To this end, we introduce a software-hardware co-designed neural architecture search(NAS) framework, CIM-based MoE NAS(CMN), focusing on identifying a high-performing MoE structure under specific hardware constraints. The results of the NYUD-v2 dataset segmentation on the RRAM(SRAM) CIM system reveal that CMN can discover optimized MoE configurations under energy, latency, and performance constraints, achieving 29.67×(43.10×) energy savings,175.44×(109.89×) speedup, and 12.24× smaller model size compared to the baseline MoE-enabled Visual Transformer, respectively. This co-design opens up an avenue toward high-performance MoE deployments in edge CIM systems.

关键词： mixture-of-experts computing-in-memory neural architecture search resistive random-access memory static random-access memory

A New Speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

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Computers, Materials & Continua 2024年第7期80卷 119-138页

作者： Mohamed Karray Nesrine Triki Mohamed Ksantini ESME ESME Research LabIvry Sur Seine94200France CEM Lab ENISUniversity of SfaxSfax3038Tunisia

Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the *** Sign Recognition System(TSRS)is one of themost important components *** the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing ***,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed ***,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured ***,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise *** addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting *** rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,***,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.

关键词： Driving automation advanced driver assistance systems(ADAS) traffic sign recognition(TSR) artificial intelligence ensemble learning belief functions voting method

Large circuit models: opportunities and challenges

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Science China(Information Sciences) 2024年第10期67卷 25-66页

作者： Lei CHEN Yiqi CHEN Zhufei CHU Wenji FANG Tsung-Yi HO Ru HUANG Yu HUANG Sadaf KHAN Min LI Xingquan LI Yu LI Yun LIANG Jinwei LIU Yi LIU Yibo LIN Guojie LUO Hongyang PAN Zhengyuan SHI Guangyu SUN Dimitrios TSARAS Runsheng WANG Ziyi WANG Xinming WEI Zhiyao XIE Qiang XU Chenhao XUE Junchi YAN Jun YANG Bei YU Mingxuan YUAN Evangeline F.Y.YOUNG Xuan ZENG Haoyi ZHANG Zuodong ZHANG Yuxiang ZHAO Hui-Ling ZHEN Ziyang ZHENG Binwu ZHU Keren ZHU Sunan ZOU Huawei Noah’s Ark lab School of integrated Circuits Peking University Faculty of Electrical Engineering and Computer Science Ningbo University Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Department of Computer Science and Engineering The Chinese University of Hong Kong School of integrated Circuits Southeast University Huawei HiSilicon Peng Cheng laboratory School of Computer Science Peking University School of Microelectronics State Key Laboratory of Integrated Chips and System Fudan University School of Artificial Intelligence Shanghai Jiao Tong University

Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.

关键词： AI-rooted EDA large circuit models (LCMs) multimodal circuit representation learning circuit optimization

Hybrid-integrated 200 Gb/s REC-DML array transmitter based on photonic wire bonding technology

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Chinese Optics Letters 2024年第8期22卷 64-69页

作者： Yuxin Ma Jie Zhao Tongtong Yang Yipeng Mei Zhenxing Sun Jun Lu Shaobo Li Xiang Ma Xiangfei Chen Key laboratory of Intelligent Optical Sensing and Manipulation of the Ministry of Education&National laboratory of Solid State Microstructures&College of Engineering and Applied Sciences&Institute of Optical Communication Engineering&Nanjing University-Tongding Joint lab for Large-Scale Photonic integrated Circuits Nanjing UniversityNanjing 210023China Optical Communication research and Development Center 54th Research Institute of China Electronics Technology Group CorporationShijiazhuang 050081China

An 8-channel hybrid-integrated chip for 200 Gb/s(8×25 Gb/s)signal transmission has been *** channels are all within the O-band,and with a spacing of 800 *** core of this chip is a monolithic integrated multi-wavelength laser array of 8 directly-modulated distributed feedback(DFB)*** using the reconstruction equivalent chirp technique,multi-wavelength integration and asymmetric phase shift structures are achieved in the laser *** output laser beams of the array are combined by a planar light-wave circuit,which is hybrid-integrated with the laser array by photonic wire *** results of this transmitter chip show good single-mode working of each unit laser,with a sidemode suppression ratio above 50 dB,and the modulation bandwidth is above 20 *** eye diagrams are obtained in the lasers for 25 Gb/s non-return-to-zero modulation,which implies a total 200 Gb/s transmission rate for the whole chip.

关键词： direct modulation laser array reconstruction equivalent chirp photonic wire bonding hybrid integration

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Contact engineering for temperature stability improvement of Bi-contacted MoS2 field effect transistors

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Science China(Information Sciences) 2024年第6期67卷 172-179页

作者： Zizheng LIU Qing ZHANG Xiaohe HUANG Chunsen LIU Peng ZHOU State Key laboratory of integrated Chip and Systems School of MicroelectronicsZhangjiang Fudan International Innovation CenterFudan University Frontier Institute of Chip and System Shanghai Key Lab for Future Computing Hardware and SystemFudan University Shaoxin laboratory

Semimetallic bismuth（Bi） is one of the most effective strategies for reducing the contact resistance of two-dimensional transition metal dichalcogenide field effect transistors（FETs）. However, the low melting point of Bi contact（271.5℃） limits its reliable applications. In this study, we demonstrated that the temperature stability of Bi-contacted electrodes could be improved by inserting a high-melting point semimetallic antimony（Sb） between the Bi contacting layer and the gold（Au） capping layer. The proposed Bi/Sb/Au contact electrodes tended to form a metal mixture with a continuous surface during the heating process（Voids appeared on the surface of the Bi/Au contact electrodes after heating at 120℃）. Because of the improved contacting layer formed by the semimetal Bi/Sb alloy, the fabricated Bi/Sb/Au-contacted molybdenum sulfide（MoS2） FETs with different gate lengths demonstrated higher on-state current stability after heating treatment than the Bi/Au contact. Because of the Bi/Sb/Au contact and poly（methyl methacrylate） package, the MoS2FETs demonstrated time stability of at least two months from the almost unchanged transfer characteristics. The electrical stability indicates that the insertion of semimetallic Sb is a promising technology for reliable Bi-based contact.

关键词： temperature stability semimetallic bismuth contact semimetallic antimony contact MoS$_{2}$ FETs time stability