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arXiv 2024年

作者： Xie, Jiayi Li, Hongfeng Cheng, Jin Cai, Qingrui Tan, Hanbo Zu, Lingyun Qu, Xiaobo Han, Hongbin The Department of Automation Tsinghua University Beijing100084 China Institute of Medical Technology Peking University Health Science Center Beijing100191 China The Institute of Medical Technology Peking University Health Science Center Beijing100191 China The School of Mathematical Sciences Fudan University Shanghai200433 China The National Integrated Circuit Industry Education Integration Innovation Platform School of Electronic Science and Engineering National Model Microelectronics College Xiamen University Xiamen361102 China Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen361102 China The Department of Endocrinology and Metabolism Department of Cardiology Institute of Vascular Medicine Peking University Third Hospital Beijing100191 China Department of Radiology Peking University Third Hospital Beijing100191 China Peking University Third Hospital Beijing Key Laboratory of Magnetic Resonance Imaging Devices and Technology Beijing100191 China NMPA key Laboratory of Evaluation of Medical Imaging Equipment and Technique Beijing100191 China

The brain extracellular space (ECS), an irregular, extremely tortuous nanoscale space located between cells or between cells and blood vessels, is crucial for nerve cell survival. It plays a pivotal role in high-level brain functions such as memory, emotion, and sensation. However, the specific form of molecular transport within the ECS remain elusive. To address this challenge, this paper proposes a novel approach to quantitatively analyze the molecular transport within the ECS by solving an inverse problem derived from the advection-diffusion equation (ADE) using a physics-informed neural network (PINN). PINN provides a streamlined solution to the ADE without the need for intricate mathematical formulations or grid settings. Additionally, the optimization of PINN facilitates the automatic computation of the diffusion coefficient governing long-term molecule transport and the velocity of molecules driven by advection. Consequently, the proposed method allows for the quantitative analysis and identification of the specific pattern of molecular transport within the ECS through the calculation of the Péclet number. Experimental validation on two datasets of magnetic resonance images (MRIs) captured at different time points showcases the effectiveness of the proposed method. Notably, our simulations reveal identical molecular transport patterns between datasets representing rats with tracer injected into the same brain region. These findings highlight the potential of PINN as a promising tool for comprehensively exploring molecular transport within the ECS. © 2024, CC BY-NC-SA.

关键词： Molecules

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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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1.8-kV circular AlGaN/GaN/AlGaN double-heterostructure high electron mobility transistor

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Chinese Physics B 2019年第2期28卷 391-394页

作者： Sheng-Lei Zhao Zhi-Zhe Wang Da-Zheng Chen Mao-Jun Wang Yang Dai Xiao-Hua Ma Jin-Cheng Zhang Yue Hao Key Laboratory for Wide Band-Gap Semiconductor Materials and Devices School of MicroelectronicsXidian University China Electronic Product Reliability and Environmental Testing Research Institute Institute of Microelectronics Peking University School of Information Science and Technology Northwest University

In this paper, we present a 1.8-kV circular AlGaN/GaN/AlGaN double-heterostructure high electron mobility transistor(DH HEMT) with a gate-drain spacing L_(GD)= 18.8 μm. Compared with the regular DH HEMT, our circular structure has a high average breakdown electric-field strength that increases from 0.42 MV/cm to 0.96 MV/cm. The power figure of meritV_(BR)~2/RON for the circular HEMT is as high as 1.03 ×10~9 V^2·Ω^(-1)·cm^(-2). The divergence of electric field lines at the gate edge and no edge effect account for the breakdown enhancement capability of the circular structure. Experiments and analysis indicate that the circular structure is an effective method to modulate the electric field.

关键词： AlGaN/GaN/AlGaN DH HEMTs circular structure breakdown voltage

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Unveiling the origin of unconventional moiré ferroelectricity

arXiv

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arXiv 2024年

作者： Niu, Ruirui Li, Zhuoxian Han, Xiangyan Liu, Qianling Qu, Zhuangzhuang Wang, Zhiyu Han, Chunrui Watanabe, Kenji Taniguchi, Takashi Liu, Kaihui Mao, Jinhai Shi, Wu Peng, Bo Han, Zheng Vitto Gan, Zizhao Lu, Jianming State Key Laboratory for Mesoscopic Physics School of Physics Peking University Beijing100871 China Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan School of Physical Sciences CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of Sciences Beijing China State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China National Engineering Research Center of Electromagnetic Radiation Control Materials School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-Electronics Shanxi University Taiyuan030006 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan030006 China

Interfacial ferroelectricity emerges in heterostructures consisting of non-polar van der Waals (vdW) layers, greatly expanding the scope of two dimensional ferroelectrics. In particular, the unconventional moiré ferroelectricity observed in bilayer graphene/boron nitride (BN) heterostructures, exhibits promising functionalities with topological current, superconductivity and synaptic responses. However, the debate about its mechanism – correlation driven charge transfer between two graphene layers – limits device reproducibility and hence large-scale production. Here by designing a single-layer graphene encapsulated by lattice-mismatched WSe2, we identify the ferroelectricity as stemming from – instead of graphene moiré bands – the particular BN, where interfacial sliding ferroelectricity must play a role. With similar structures, multilayer twisted MoS2 is found to reproduce the ferroelectricity. The key is a conductive moiré ferroelectric, where the screened gate and the pinned domain wall together result in unchanged electronic states, i.e. anomalous screening. The intimate connection to interfacial sliding ferroelectricity thus provides advantages of diverse choices of constituent materials and robust polarization switching while preserving the unique anomalous screening, paving the way to reproducible and reliable memory-based devices in artificial intelligence. © 2024, CC BY.

关键词： Ferroelectricity

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Source-field-plated β-(Al x Ga 1-x ) 2 O 3 MOSFET with breakdown voltage over 7kV

Micro and Nanostructures

引用

Micro and Nanostructures 2025年 206卷

作者： Hongyu Liu Haozhong Wu Yuangang Wang Yuanjie Lv Shida Han Tingting Han Shaobo Dun Hongyu Guo Xuanze Zhou Guangwei Xu Shibing Long Zhihong Feng National Key Laboratory of Solid-State Microwave Devices and Circuits Hebei Semiconductor Research Institute Hebei Shijiazhuang 050051 China School of Microelectronics University of Science and Technology of China Hefei China

In this letter, β-(Al x Ga 1-x ) 2 O 3 MOSFET with high breakdown voltage are demonstrated. A 150-nm β-(Al 0.14 Ga 0.86 ) 2 O 3 epitaxial layer and a 30-nm Ga 2 O 3 buffer were grown on Fe-doped semi-insulating β-Ga 2 O 3 substrate by metal-organic chemical vapor deposition. The epitaxial thin film exhibits relatively high crystalline quality, with a FWHM of 54 arcsec in the XRD rocking curve and a surface roughness of 2.3 nm. A T-shaped gate and source-field-plated are fabricated to mitigate electric field crowding. The β-(Al 0.14 Ga 0.86 ) 2 O 3 MOSFET with source-drain length of 84 μm demonstrates breakdown voltage of 7.2 kV, combined with the specific on-resistance of 3534 mΩ cm 2 , corresponding to power figures of merit of 14.7 MW/cm 2 . The results highlight the potential of β-(Al x Ga 1-x ) 2 O 3 for high-voltage power electronics.

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Temperature-Dependent Characteristics of GaN Schottky Barrier Diodes with TiN and Ni Anodes

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Chinese Physics Letters 2019年第5期36卷 54-58页

作者： Ting-Ting Wang Xiao Wang Xiao-Bo Li Jin-Cheng Zhang Jin-Ping Ao Key Laboratory of Wide Band-Gap Semiconductor Materials and Devices School of MicroelectronicsXidian UniversityXi’an 710071 Institute of Technology and Science Tokushima UniversityTokushima 770-8506Japan

The effect of temperature on the characteristics of gallium nitride (GaN) Schottky barrier diodes (SBDs) with TiN and Ni anodes is evaluated. With increasing the temperature from 25 to 175℃, reduction of the turn-on voltage and increase of the leakage current are observed for both GaN SBDs with TiN and Ni anodes. The performance after thermal treatment shows much better stability for SBDs with Ti N anode, while those with Ni anode change due to more interface states. It is found that the leakage currents of the GaN SBDs with TiN anode are in accord with the thermionic emission model whereas those of the GaN SBDs with Ni anode are much higher than the model. The Silvaco TCAD simulation results show that phonon-assisted tunneling caused by interface states may lead to the instability of electrical properties after thermal treatment, which dominates the leakage currents for GaN SBDs with Ni anode. Compared with GaN SBDs with Ni anode, GaN SBDs with TiN anode are beneficial to the application in microwave power rectification fields due to lower turn-on voltage and better thermal stability.

关键词： GaN SBD Temperature-Dependent Characteristics of GaN Schottky Barrier Diodes with TiN and Ni Anodes TiN Ni

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One-step fabrication of TiO2/graphene hybrid mesoporous film with enhanced photocatalytic activity and photovoltaic performance

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Chinese Journal of Catalysis 2020年第8期41卷 1208-1216页

作者： Junxiong Guo Yiyi Li Shangdong Li Xumei Cui Yu Liu Wen Huang Linna Mao Xiongbang Wei Xiaosheng Zhang State Key Laboratory of Electronic Thin Films and Integrated Devices School of Electronic Science and Engineering(National Exemplary School of Microelectronics)University of Electronic Science and Technology of ChinaChengdu 610054SichuanChina College of Optoelectronic Engineering Chengdu University of Information TechnologyChengdu 610225SichuanChina Institute of Microelectronics Tsinghua National Laboratory for Information Science and Technology(TNList)Tsinghua UniversityBeijing 100084China

We synthesized a mesoporous film based on TiO2-reduced graphene oxide(RGO)hybrids using a one-step vapor-thermal method without the need for an additional annealing *** vapor-thermally prepared TiO2-graphene hybrid(VTH)features unique structures with an ultra-large specific surface area of^260 m^2 g^-1 and low aggregation,giving rise to enhanced light harvesting and increased charge generation and separation *** was observed that a mesoporous film with uniform pore distribution is simultaneously obtained during the VTH growth *** a 5.0 wt%RGO VTH film was used as the active layer in photocatalysis,the highest photocatalytic activity for degradation of methyl orange was *** another,when a 0.75 wt%RGO VTH film was used as the photoanode in a dye-sensitized solar cell,the power conversion efficiency reached 7.58%,which represents an increase of 73.1%compared to a solar cell using an a photoanode of pure TiO2 synthesized by a traditional solvothermal *** is expected that this facile method for the synthesis of TiO2/graphene hybrid mesoporous films will be useful in practical applications for preparing other metal oxide/graphene hybrids with ultra-high photocatalytic activity and photovoltaic performance.

关键词： TiO2-graphene hybrid Catalytic activity Photoanode Vapor-thermal method Mesoporous film

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Manipulating magnetism and transport properties of EuCd2P2 with a low carrier concentration

arXiv

引用

arXiv 2024年

作者： Chen, Xiyu Wang, Ziwen Zhou, Zhiyu Yang, Wuzhang Liu, Yi Lu, Jia-Yi Ren, Zhi Cao, Guang-Han Tafti, Fazel Dong, Shuai Wang, Zhi-Cheng Key Laboratory of Quantum Materials and Devices of Ministry of Education School of Physics Southeast University Nanjing211189 China School of Science Westlake University Hangzhou310024 China Institute of Natural Sciences Westlake Institute for Advanced Study Hangzhou310024 China Department of Applied Physics Zhejiang University of Technology Hangzhou310023 China School of Physics Interdisciplinary Center for Quantum Information State Key Laboratory of Silicon and Advanced Semiconductor Materials Zhejiang University Hangzhou310058 China Collaborative Innovation Centre of Advanced Microstructures Nanjing University Nanjing210093 China Department of Physics Boston College Chestnut HillMA02467 United States

Materials that exhibit strongly coupled magnetic order and electronic properties are crucial for both fundamental research and technological applications. However, finding a material that not only shows remarkable magnetoresistive responses but also has an easily tunable ground state remains a challenge. Here, we report successful manipulation of the magnetic and transport properties of EuCd2P2, which is transformed from an A-type antiferromagnet (TN = 11 K) exhibiting colossal magnetoresistance into a ferromagnet (TC = 47 K) with metallic behavior. The dramatic alteration results from a low hole concentration of 1019 cm-3 induced by changing the growth conditions. Electronic structure and total energy calculations confirm the tunability of magnetism with a small carrier concentration for EuCd2P2. It is feasible to switch between the magnetic states by using field-effect to control the carrier density, thereby changing the magneto-electronic response. The controllable magnetism and electrical transport of EuCd2P2 make it a potential candidate for spintronics. Copyright © 2024, The Authors. All rights reserved.

关键词： Electronic properties

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Hybrid memristor-CMOS neurons for in-situ learning in fully hardware memristive spiking neural networks

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science Bulletin 2021年第16期66卷 1624-1633,M0003页

作者： Xumeng Zhang Jian Lu Zhongrui Wang Rui Wang Jinsong Wei Tuo Shi Chunmeng Dou Zuheng Wu Jiaxue Zhu Dashan Shang Guozhong Xing Mansun Chan Qi Liu Ming Liu Frontier Institute of Chip and System Fudan UniversityShanghai 200433China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China Department of Electrical and Electronic Engineering the University of Hong KongHong KongChina Zhejiang Laboratory Hangzhou 311122China Department of Electronic and Computer Engineering the Hong Kong University of Science and TechnologyHong KongChina

Spiking neural network,inspired by the human brain,consisting of spiking neurons and plastic synapses,is a promising solution for highly efficient data processing in neuromorphic ***,memristor-based neurons and synapses are becoming intriguing candidates to build spiking neural networks in hardware,owing to the close resemblance between their device dynamics and the biological ***,the functionalities of memristor-based neurons are currently very limited,and a hardware demonstration of fully memristor-based spiking neural networks supporting in-situ learning is very ***,a hybrid spiking neuron combining a memristor with simple digital circuits is designed and implemented in hardware to enhance neuron *** hybrid neuron with memristive dynamics not only realizes the basic leaky integrate-and-fire neuron function but also enables the in-situ tuning of the connected synaptic ***,a fully hardware spiking neural network with the hybrid neurons and memristive synapses is experimentally demonstrated for the first time,and in-situ Hebbian learning is achieved with this *** work opens up a way towards the implementation of spiking neurons,supporting in-situ learning for future neuromorphic computing systems.

关键词： Memristor Hybrid neuron In-situ learning Fully hardware Spiking neural network

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Potential-based model for asymmetric and symmetric double-gate organic thin-film transistors

引用

Organic Electronics 2025年 144卷

作者： Xiaohui Li Yan Yang Zongcheng Su Yu Xiong Changjiang Chen Long Wang Wei Zhou Hongjun Wang Xiaoxin Xu China State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu 610054 China College of Communication Engineering (College of Microelectronic) Chengdu University of Information Technology Chengdu 610225 China Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics of Chinese Academy of Sciences Beijing China

This paper proposes a potential-based model for asymmetric and symmetric double-gate organic thin-film transistors (DG-OTFT). The model is derived strictly from the accurate solution of one-dimensional Poisson's equation and current continuity equation. By preserving the proper physics, this model can exactly describe the distribution of electric potential and carrier density of DG-OTFT, and analyze the approximate and non-approximate distribution under the large voltage. Moreover, discussing the Ids characteristics of DG-OTFT based on surface potential equation, the causes of shoulder current are also analyzed in this paper. The theoretical calculations based on this model have good consistency with experimental data, playing an important role in promoting the development of DG-OTFT technology and providing valuable insights for its application in large-scale electronic devices.

关键词： Thin film transistors

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