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Radiation-hardened property of single-walled carbon nanotube film-based field-effect transistors under low-energy proton irradiation

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Journal of Semiconductors 2021年第11期42卷 18-25页

作者： Xiaorui Zhang Huiping Zhu Song’ang Peng Guodong Xiong Chaoyi Zhu Xinnan Huang Shurui Cao Junjun Zhang Yunpeng Yan Yao Yao Dayong Zhang Jingyuan Shi Lei Wang Bo Li Zhi Jin High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Science and Technology on Silicon Devices Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China Department of Chemistry City University of Hong KongHong Kong 999077China

Strong C-C bonds,nanoscale cross-section and low atomic number make single-walled carbon nanotubes(SWCNTs)a potential candidate material for integrated circuits(ICs)applied in outer ***,very little work combines the simulation calculations with the electrical measurements of SWCNT field-effect transistors(FETs),which limits further understanding on the mechanisms of radiation ***,SWCNT film-based FETs were fabricated to explore the total ionizing dose(TID)and displacement damage effect on the electrical performance under low-energy proton irradiation with different fluences up to 1×1015 p/*** negative shift of the threshold voltage and obvious decrease of the on-state current verified the TID effect caused in the oxide *** stability of the subthreshold swing and the off-state current reveals that the displacement damage caused in the CNT layer is not serious,which proves that the CNT film is ***,according to the simulation,we found the displacement damage caused by protons is different in the source/drain contact area and channel area,leading to varying degrees of change for the contact resistance and sheet *** analyzed the simulation results and electrical measurements,we explained the low-energy proton irradiation mechanism of the CNT FETs,which is essential for the construction of radiation-hardened CNT film-based ICs for aircrafts.

关键词： SWCNT FETs low-energy proton irradiation radiation effects electrical performance TID effect displacement damage effect simulation

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Polarization tunable bidirectional photoresponse in Van der Waals α−In2Se3/NbX2 (X=S,Se,andTe) ferroelectric diodes

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Physical Review Materials 2023年第8期7卷 084412-084412页

作者： Shibo Fang Qiuhui Li Chen Yang Baochun Wu Shiqi Liu Jie Yang Jiachen Ma Zongmeng Yang Kechao Tang Jing Lu State Key Laboratory for Mesoscopic Physics and School of Physics Peking University Beijing 100871 People's Republic of China State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics Tsinghua University Beijing 100871 People's Republic China Key Laboratory of Spintronics Materials Devices and Systems of Zhejiang Province Hangzhou 311305 People's Republic of China Key Laboratory of Material Physics School of Physics and Microelectronics Ministry of Education Zhengzhou University Zhengzhou 450001 People's Republic of China Research Center for Materials Architectures and Integration of Nanomembranes (MAIN) Chemnitz University of Technology 09126 Chemnitz Germany School of Integrated Circuits Peking University Beijing 100871 People's Republic of China Collaborative Innovation Center of Quantum Matter Beijing 100871 People's Republic of China Beijing Key Laboratory for Magnetoelectric Materials and Devices (BKL-MEMD) Peking University Beijing 100871 People's Republic of China Peking University Yangtze Delta Institute of Optoelectronics Nantong 226010 People's Republic of China Key Laboratory for the Physics and Chemistry of Nanodevices Peking University Beijing 100871 People's Republic of China

Ferroelectric diodes can generate a polarization-controlled bidirectional photoresponse to simulate inhibition and promotion behaviors in the artificial neuromorphic system with fast speed, high energy efficiency, and nonvolatility. However, the existing ferroelectric diodes based on ferroelectric oxides suffer from a weak bidirectional photoresponse (below 1 mA/W), difficult miniaturization, and a large response photon energy (over 3 eV). Here, we design a series of van der Waals α−In2Se3/NbX2 (X = S, Se, and Te) ferroelectric diodes with bidirectional photoresponse by using ab initio quantum transport simulation. These devices show a maximum bidirectional photoresponse of 30 (−19) mA/W and a minimum response photon energy of 1.3 eV at the monolayer thickness. Our work shows advanced optoelectronic applications of the van der Waals ferroelectric diodes in the future artificial neuromorphic system.

关键词： Ferroelectricity First-principles calculations Photocurrent 2-dimensional systems Diodes Ferroelectrics Density functional theory Landauer formula

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Pruning random resistive memory for optimizing analogue AI

arXiv

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arXiv 2023年

作者： Li, Yi Wang, Songqi Zhao, Yaping Wang, Shaocong Zhang, Woyu He, Yangu Lin, Ning Cui, Binbin Chen, Xi Zhang, Shiming Jiang, Hao Lin, Peng Zhang, Xumeng Qi, Xiaojuan Wang, Zhongrui Xu, Xiaoxin Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong State Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Frontier Institute of Chip and System Fudan University Shanghai200433 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong University of Chinese Academy of Sciences Beijing100049 China Institute of Mind The University of Hong Kong Hong Kong

The rapid advancement of artificial intelligence (AI) has been marked by the large language models exhibiting human-like intelligence. However, these models also present unprecedented challenges to energy consumption and environmental sustainability, which are exacerbated by the increasing number of users and the development of even larger models. One promising solution is to revisit analogue computing, a technique that predates digital computing and exploits emerging analogue electronic devices, such as resistive memory, which features in-memory computing, high scalability, and nonvolatility that addresses the von Neumann bottleneck, slowdown of Moore’s law, and volatile DRAM of conventional digital hardware. However, analogue computing still faces the same challenges as before: programming nonidealities and expensive programming due to the underlying devices physics. Therefore, leveraging the efficiency advantage while mitigating the programming disadvantage of analogue computing with resistive memory is a major open problem in AI hardware and electronics communities. Here, we report a universal solution, software-hardware co-design using structural plasticity-inspired edge pruning to optimize the topology of a randomly weighted analogue resistive memory neural network. Software-wise, the topology of a randomly weighted neural network is optimized by pruning connections rather than precisely tuning resistive memory weights. Hardware-wise, we reveal the physical origin of the programming stochasticity using transmission electron microscopy, which is leveraged for large-scale and low-cost implementation of an overparameterized random neural network containing high-performance sub-networks. We implemented the co-design on a 40nm 256K resistive memory macro, observing 17.3% and 19.9% accuracy improvements in image and audio classification on FashionMNIST and Spoken digits datasets, as well as 9.8% (2%) improvement in PR (ROC) in image segmentation on DRIVE datasets, r

关键词： Energy utilization

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Ferroelectricity in HfO2 from a chemical perspective

arXiv

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arXiv 2022年

作者： Yuan, Jun-Hui Mao, Ge-Qi Xue, Kan-Hao Bai, Na Wang, Chengxu Cheng, Yan Lyu, Hangbing Sun, Huajun Wang, Xingsheng Miao, Xiangshui School of Integrated Circuits School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China Hubei Yangtze Memory Laboratories Wuhan430205 China Department of Electronics East China Normal University Shanghai200241 China Key Laboratory of Microelectronics Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China

Ferroelectricity observed in thin film HfO2, either doped with Si, Al, etc. or in the Hf0.5Zr0.5O2 form, has gained great technical significance. However, the soft mode theory faces a difficulty in explaining the origin of such ferroelectricity. In this work, we propose that the 7 cation coordination number of HfO2/ZrO2 lies at the heart of this ferroelectricity, which stems from the proper ionic radii of Hf/Zr compared with O. Among the numerous compounds with non-centrosymmetric nature, e.g., mm2 point group, HfO2 and ZrO2 are special in that they are close to the border of 7 and 8 cation coordination, such that the 8-coordination tetragonal intermediate phase could greatly reduce the switching barrier. Other 7-coordination candidates, including SrI2, TaON, YSBr and YOF are also studied in comparison to HfO2/ZrO2, and six switching paths are analyzed in detail for the Pca21 phase. A rule of preferred switching path in terms of ionic radii ratio and coordination number has been established. We also show the possible route from ferroelectric Pca21 phase to monoclinic P21/c phase in HfO2, which is relevant to the fatigue phenomenon. Copyright © 2022, The Authors. All rights reserved.

关键词： Ferroelectricity

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Resistive memory-based zero-shot liquid state machine for multimodal event data learning

arXiv

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arXiv 2023年

作者： Lin, Ning Wang, Shaocong Li, Yi Wang, Bo Shi, Shuhui He, Yangu Zhang, Woyu Yu, Yifei Zhang, Yue Zhang, Xinyuan Wong, Kwunhang Wang, Songqi Chen, Xiaoming Jiang, Hao Zhang, Xumeng Lin, Peng Xu, Xiaoxin Qi, Xiaojuan Wang, Zhongrui Shang, Dashan Liu, Qi Liu, Ming Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits and Key Laoratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics the Chinese Academy of Sciences Beijing100029 China The School of Microelectronics Southern University of Science and Technology Shenzhen518055 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong University of Chinese Academy of Sciences Beijing100049 China Frontier Institute of Chip and System Fudan University Shanghai200433 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

The human brain is a complex spiking neural network (SNN), capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains minimal power consumption through event-based signal propagation. However, replicating the human brain in neuromorphic hardware presents both hardware and software challenges. Hardware limitations, such as the slowdown of Moore’s law and Von Neumann bottleneck, hinder the efficiency of digital computers. Additionally, SNNs are characterized by their software training complexities. To this end, we propose a hardware-software co-design on a 40 nm 256 Kb in-memory computing macro that physically integrates a fixed and random liquid state machine (LSM) SNN encoder with trainable artificial neural network (ANN) projections. We showcase the zero-shot LSM-based learning of multimodal events on the N-MNIST and N-TIDIGITS datasets, including visual and audio data association, as well as neural and visual data alignment for brain-machine interfaces. Our co-design achieves classification accuracy comparable to fully optimized software models, resulting in a 152.83 and 393.07-fold reduction in training costs compared to SOTA contrastive language-image pre-training (CLIP) and Prototypical networks, and a 23.34 and 160-fold improvement in energy efficiency compared to cutting-edge digital hardware, respectively. These proof-of-principle prototypes demonstrate zero-shot multimodal events learning capability for emerging efficient and compact neuromorphic hardware. © 2023, CC BY-NC-SA.

关键词： Image enhancement

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Highly-Sensitive FET-based Sensor via Heterogeneous Selective-Assembling Integration of Porphyrin and Silicon Nanowires

Highly-Sensitive FET-based Sensor via Heterogeneous Selectiv...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Xiaokang Li Bocheng Yu Gong Chen Ming Li Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing China Frontiers Science Center for Nano-optoelectronics Peking University Beijing China

ISBN: (数字)9781728162355

ISBN: (纸本)9781728162362

In this paper, we proposed and fabricated a novel heterogeneous porphyrin/silicon nanowire transistor-based sensor using CMOS process technology. With the difference in hydrophobicity of Si 3 N 4 and SiO 2 , the enrichment of porphyrin molecules on silicon nanowires was achieved, and the device showed highly sensitive photo-sensing even under very low illumination power (ΔVt=3.32V @11.3μW/cm 2 ), great dynamic photo-memory characteristic (ΔV t =31.3V @ programming/erasing time of 10s) and excellent temperature sensing (ΔV t =13.6V @ 90°C temperature range). Those performances make the devices applicable to be used in applications of sensitive and smart non-memory light sensing and reliable temperature sensing.

关键词： Nanowires Silicon Sensors Temperature sensors Threshold voltage Sensitivity Transistors

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TCAD Simulation on Random Telegraphy Noise and Grain-Induced Fluctuation of 3D Nand Cell Transisitors

TCAD Simulation on Random Telegraphy Noise and Grain-Induced...

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China Semiconductor Technology International Conference (CSTIC)

作者： Shijie Hu Ming Li Ru Huang Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of Microelectronics Peking University Beijing CHINA Frontiers Science Center for Nano-optoelectronics Peking University Beijing CHINA

ISBN: (数字)9781728165585

ISBN: (纸本)9781728165592

In this work, a TCAD simulation platform was set up to study the real poly-channel modeling, trap-induced noise and random grain doping in 3D NAND cell transistor. The random telegraph noise and size dependence was simulated and analyzed. Simulation results show that the RTN and grain size change have greater influence on threshold voltage (V T ) and channel current (I D ) in 3D NAND than doping fluctuation. It is shown that the instability caused by random doping cannot be ignored, too.

关键词： Solid modeling Three-dimensional displays Fluctuations Doping Tools Semiconductor process modeling Transistors

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A New Design Methodology of Highly Reliable TFT Based Integrated circuits in Display Applications

A New Design Methodology of Highly Reliable TFT Based Integr...

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International Conference on Display Technology, ICDT 2019

作者： Geng, Di Su, Yue Li, Ling Liu, Ming Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing China

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Efficient Electroabsorption Modulation of Mid- and Far-Infrared Radiation by Driving the Band-Inversion Transition of InAs/GaSb Type-II Quantum Wells

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Physical Review Applied 2021年第6期16卷 064053-064053页

作者： Jun Li Jiang-Tao Liu Zhenhua Wu Wei Huang Cheng Li Department of Physics Semiconductor Photonics Research Center Xiamen University Xiamen 361005 China College of Mechanical and Electrical Engineering Guizhou Minzu University Guiyang 550025 China Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China

Based on the self-consistent calculations of the eight-band k⋅p model and Poisson equation, we theoretically demonstrate that the intersubband optical absorption of InAs/GaSb type-II quantum wells (QWs) is effectively tuned by the electric-field-driven band-inversion transition. By utilizing this property, InAs/GaSb QWs can be made into highly efficient electroabsorption modulators (EAMs) for TM-polarized mid-infrared radiation (MIR) (approximately 4.2–12μm) and TE-polarized far-infrared radiation (FIR) (approximately 12–100μm). At low temperature, an example p-i-n waveguide EAM composed of six-period InAs/GaSb QWs achieves a drive voltage of <0.5 V, a 3-dB cutoff bandwidth of approximately 24.6 GHz, and a dynamic power consumption of ≤0.06 mW/GHz for a 20-dB on:off ratio modulation of 4.46-μm TM-polarized radiation. Although the modulation efficiencies drop by 70%–80% when the temperature increases, the performance of InAs/GaSb EAMs is (at least) comparable with conventional 1.55-μm EAMs at 300 K. These results suggest that InAs/GaSb EAMs are promising devices for high-speed and low-power-consumption MIR (or FIR) free-space optical communications.

关键词： Integrated optics Optoelectronics Heterostructures III-V semiconductors Quantum wells Two-dimensional electron gas Waveguides Infrared techniques

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Deep-Learning-Enhanced Single-Spin Readout in Silicon Carbide at Room Temperature

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Physical Review Applied 2022年第3期17卷 034046-034046页

作者： Yu-Wei Liao Qiang Li Mu Yang Zheng-Hao Liu Fei-Fei Yan Jun-Feng Wang Ji-Yang Zhou Wu-Xi Lin Yi-Dan Tang Jin-Shi Xu Chuan-Feng Li Guang-Can Guo CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei 230026 People’s Republic of China CAS Center For Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei 230026 People’s Republic of China High-Frequency High-Voltage Devices and Integrated Circuits R&D Center Institute of Microelectronics of Chinese Academy of Sciences 100029 Beijing China

Defect spin qubits in silicon carbide have recently drawn widespread attention. Extraction of spin information in the presence of noise always requires multiple repeated measurements, which consumes a large amount of time resources. In this paper, we propose a deep-learning-enhanced method to extract effective parameters from continuous-wave optically detected magnetic resonance (ODMR) spectra and Rabi oscillations with less time consumption. Even if the signal-to-noise ratio is reasonably low, a well-trained convolutional neural network (CNN) can predict the resonance peaks of ODMR spectra or the period of Rabi oscillations. Because of the fast output of predictions by the CNN, this method can be used to sense the magnetic field in the environment and microwave intensities in real time.

关键词： Coherent control Color centers Crystal defects Quantum information with solid state qubits Semiconductor compounds Artificial neural networks Machine learning Optically detected magnetic resonance

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