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2019 IEEE International Conference on Electron devices and Solid-State circuits, EDSSC 2019

作者： Zhu, Yajun Niu, Yuze Lu, Wengao Huang, Zhaofeng Zhang, Yacong Chen, Zhongjian Key Laboratory of Microelectronic Devices and Circuits Department of Microelectronics Peking University Beijing China

ISBN: (纸本)9781728102863

This paper presents a ROIC (Readout Integrated Circuit) with NUC (Non-uniformity Calibration), which is applied in a silicon diode uncooled IRFPA (Infrared Focal Plane Array). We propose blind pixel to calibrate chip temperature non-uniformity and DAC-based calibration for calibrating process non-uniformity. The ROIC is fabricated using a 0.35\mu \mathrm{m} CMOS process with array size of 160\times 120. Power consumption of the ROIC is 41mW, noise of the DAC is less than 2\muV, and the circuit's SNR (Signal-to-Noise Ratio) is 72dB. © 2019 IEEE.

关键词： Pixels

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Implementation of Lateral Divisive Inhibition Based on Ferroelectric Fet with Ultra-Low Hardware Cost for Neuromorphic Computing

Implementation of Lateral Divisive Inhibition Based on Ferro...

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China Semiconductor Technology International Conference (CSTIC)

作者： Shuhan Liu Tianyi Liu Zhiyuan Fu Cheng Chen Qianqian Huang Ru Huang Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing China

ISBN: (数字)9781728165585

ISBN: (纸本)9781728165592

In this work, a novel bio-inspired hardware design of lateral divisive inhibition is proposed and demonstrated by using only one transistor of ferroelectric FET. The proposed design is simulated based on our developed FeFET model, and is also proved to be functional in spiking neural network. The new design with ultra-low hardware cost exhibits good biological plausibility, showing its great potential for neuromorphic computing.

关键词： Neuromorphic engineering Computational modeling Biological system modeling Neural networks Hardware Transistors Task analysis

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Physical Insights into the Impact of Internal Metal Gate on the Subthreshold Behavior of NCFET Based on Domain Switching Dynamics

Physical Insights into the Impact of Internal Metal Gate on ...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Tianyue Fu Qianqian Huang Liang Chen Chang Su Ru Huang Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing China

ISBN: (数字)9781728162355

ISBN: (纸本)9781728162362

In this work, the influences of the internal metal of gate stack in Negative Capacitance FET (NCFET) are clarified based on domain switching dynamics physically. By analyzing the equivalent ferroelectric (FE)/dielectric (DE) series capacitor, a new method is proposed to study the domain switching process for metal-ferroelectric-insulator-metal (MFIM) structure. Our results illustrate that NC effect of FE/DE series capacitor is closely related to the switching capabilities of FE layer, embodied by the distribution of switching activation field Ea of domains, which also provide the design direction of FE layer for the subthreshold swing optimization of NCFET.

关键词： Switches Iron Logic gates Capacitors Periodic structures Optimization Electric potential

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Origin of Steep Subthreshold Swing Within the Low Drain Current Range in Negative Capacitance Field Effect Transistor

Origin of Steep Subthreshold Swing Within the Low Drain Curr...

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China Semiconductor Technology International Conference (CSTIC)

作者： Chang Su Qianqian Huang Mengxuan Yang Liang Chen Zhongxin Liang Ru Huang Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing CHINA

ISBN: (数字)9781728165585

ISBN: (纸本)9781728165592

Negative capacitance FET (NCFET) can achieve the steeper subthreshold swing (SS) than conventional MOSFET for the reduction of supply voltage V DD , while many experimental results indicate that NCFETs show the steeper SS only within a limited drain current range. In this work, the physical origin and parameter impacts of drain current range corresponding to steeper SS in NCFET are investigated, based on the modeling of domain switching dynamics of ferroelectric (FE). It is found that the larger remnant polarization is beneficial for the steeper SS with the larger drain current range. Besides, simulation results indicate that only within the limited window of sweeping rate and FE switching time, the drain current range can be enlarged for the steeper switching in NCFET.

关键词： MOSFET Simulation Switches Capacitance Iron Hafnium compounds Switching circuits

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Device Modeling and Application Simulation of Ferroelectric-FETS with Dynamic Multi-Domain Behavior

Device Modeling and Application Simulation of Ferroelectric-...

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China Semiconductor Technology International Conference (CSTIC)

作者： Zhiyuan Fu Cheng Chen Jin Luo Qianqian Huang Ru Huang Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing CHINA

ISBN: (数字)9781728165585

ISBN: (纸本)9781728165592

In this work, a ferroelectric-FET (FeFET) model based on multi-domain Preisach theory is developed. Instead of the single-domain Landau-Khalatnikvo (L-K) and tanh based model, the Preisach model with dynamic module is established to accurately model the dynamic behavior of multi-domain FeFET. Moreover, a FeFET-based neuron structure is presented and simulated based on the developed device model, showing the promising potential of FeFET for neuromorphic computing.

关键词： Semiconductor device modeling Neuromorphic engineering Computational modeling Neurons

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Topology Optimization of Random Memristors for Input-Aware Dynamic SNN

arXiv

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arXiv 2024年

作者： Wang, Bo Wang, Shaocong Lin, Ning Li, Yi Yu, Yifei Zhang, Yue Yang, Jichang Wu, Xiaoshan He, Yangu Wang, Songqi Chen, Rui Li, Guoqi Qi, Xiaojuan Wang, Zhongrui Shang, Dashan Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

There is unprecedented development in machine learning, exemplified by recent large language models (GPT4) and world simulators (SORA), which are artificial neural networks (ANNs) running on digital computers. However, they still cannot parallel human brains in terms of energy efficiency and the streamlined adaptability to inputs of different difficulties, due to differences in signal representation, optimization, run-time reconfigurability, and hardware architecture. To address these fundamental challenges, we introduce pruning optimization for input-aware dynamic memristive spiking neural network (PRIME). Signal representation-wise, PRIME employs leaky integrate-and-fire neurons to emulate the brain’s inherent spiking mechanism. Drawing inspiration from the brain’s structural plasticity, PRIME optimizes the topology of a random memristive SNN, without expensive memristor conductance fine-tuning. For runtime reconfigurability, inspired by the brain’s dynamic adjustment of computational depth, PRIME employs an input-aware dynamic early stop policy to minimize latency during inference, thereby boosting energy efficiency without compromising performance. Architecture-wise, PRIME leverages memristive in-memory computing, mirroring the brain and mitigating the von Neumann bottleneck. We validated our system using a 40 nm 256 Kb memristor-based in-memory computing macro on neuromorphic image classification and image inpainting. Our results demonstrate the classification accuracy and Inception Score (IS) are comparable to the software baseline, while achieving 37.83× and 62.50× improvements in energy efficiency. Furthermore, we attained 77.0% and 12.5% computational load savings with minimal reduction in performance. The system also exhibits robustness against stochastic synaptic noise of analogue memristors. Our software-hardware co-designed model paves the way to future brain-inspired neuromorphic computing of brain-like energy efficiency and adaptivity. Copyright © 202

关键词： Memristors

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Low power and high uniformity of HfOx-based RRAM via tip-enhanced electric fields

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中国科学:化学（英文版） 2019年第10期62卷 160-166页

作者： Xiaokang LI Baotong ZHANG Bowen WANG Xiaoyan XU Yuancheng YANG Shuang SUN Qifeng CAI Shijie HU Xia AN Ming LI Ru HUANG Key Laboratory of Microelectronic Devices and Circuits(MOE) Institute of MicroelectronicsPeking University Beijing 100871 China

In this paper,the HfOx-based resistive random access memory (RRAM) devices with sub-100 nm pyramid-type electrodes were *** the help of tip-enhanced electric field around the pyramid-type electrodes,it was experimentally demonstrated that the novel devices have better cycle-to-cycle variation control,lower forming/set voltage (1.97/0.7 V) and faster switching speed (≤ 30 ns under 0.9 V pulse) as well as better endurance reliability than conventional flat electrode resistive memory *** addition,the novel RRAM is experimentally demonstrated with independence of electrode number for the first time to present great potential in scaling *** novel structure metal-oxide based RRAM will be suitable for the future low-power non-volatile memory application.

关键词： RRAM pyramid-type electrode variation reliability switching speed conducting filament

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A 1μW-to-158μW Output Power Pseudo Open-Loop Boost DC-DC with 86.7% Peak Efficiency using Frequency-Programmable Oscillator and Hybrid Zero Current Detection

A 1μW-to-158μW Output Power Pseudo Open-Loop Boost DC-DC w...

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IEEE International Symposium on circuits and Systems (ISCAS)

作者： Xiaolong Chen Enbin Gong Hao Zhang Le Ye Ru Huang Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking university Beijing 100871 China

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

This paper proposed a pseudo-open boost DC-DC converter whose input voltage ranges from 300mV-to-500mV and output voltage ranges from 1.2V-to-1.8V. The output power ranges from 1μW to 158μW. Three key structures are designed to realize the high energy conversion efficiency when the load reaches ultra-light: the pseudo open-loop structure, the frequency-programmable oscillator, and the hybrid zero current detection (H-ZCD) circuit. The pseudo open-loop structure eliminates the analog comparators or error amplifiers used in converter and the quiescent power loss is much reduced. The frequency-programmable ring oscillator is able to output 9-bit binary frequency ranges from 500Hz-100KHz, so the power consumption of clock generation is saved when load power reaches to ultra-light. The proposed H-ZCD is designed to reduce the inductor power loss with just tiny power consumption. Accordingly, the high efficiency boost DC-DC works in the discontinuous condition mode (DCM) and the constant on time pulse frequency modulation (PFM) is proposed. As a simulation result, the peak efficiency of the converter reaches to 86.7% while the load power is 13.7μW.

关键词： Ring oscillators DC-DC power converters Power demand Switches Capacitors Energy efficiency

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Applications of MXenes in human-like sensors and actuators

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Nano Research 2023年第4期16卷 5767-5795页

作者： Jinbo Pang Songang Peng Chongyang Hou Xiao Wang Ting Wang Yu Cao Weijia Zhou Ding Sun Kai Wang Mark H.Rümmeli Gianaurelio Cuniberti Hong Liu Institute for Advanced Interdisciplinary Research(iAIR) Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of ShandongUniversity of JinanJinan 250022China Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany 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 Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of TechnologyShandong Academy of SciencesJinan 250353China School of Bioengineering Qilu University of TechnologyShandong Academy of ScienceJinan 250353China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Ministry of Education) Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao 266000China School of Electrical and Computer Engineering Jilin Jianzhu UniversityChangchun 130118China Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key L

Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.

关键词： MXenes sensors actuators gas sensors biosensors tactile sensors sound sensors artificial retina

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An 81–99 GHz Tripler with Fundamental Cancellation and 3rd Harmonic Enhancement Technique in 40-nm CMOS

An 81–99 GHz Tripler with Fundamental Cancellation and 3rd ...

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IEEE International Symposium on circuits and Systems (ISCAS)

作者： Xiaolei Su Xiucheng Hao Dong Wang Zhengkun Shen Zexue Liu Junhua Liu Huailin Liao Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing 100871 China

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

An 81–99 GHz tripler for wireless transceiver LO generation is presented in this paper. To suppress the fundamental signal and enhance the 3rd harmonic, the inversion signal is applied to the gate of the cascading transistor of the push-push differential pair. A capacitor is connected to the source and drain of the cascading transistor to further suppress the fundamental signal. Without additional filters, the tripler achieves more than 40 dBc of fundamental suppression with an even harmonic suppression of up to 60 dBc. The tripler reaches an output power of −2.6 dBm (4-dBm input) at 91.5 GHz with a 20% bandwidth of from 81 to 99 GHz. The core area of the chip occupies only 190 μm×530 μm in TSMC 40-nm CMOS process and consumes 28.2 mW.

关键词： Harmonic analysis Power harmonic filters Transistors Radio frequency Parasitic capacitance Capacitors Inductors

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