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Science Bulletin 2024年第10期69卷 1427-1436页

作者：屈恒泽张胜利曹江吴振华柴扬李卫胜李连忠任文才王欣然曾海波 MIIT Key Laboratory of Advanced Display Materials and Devices College of Material Science and EngineeringNanjing University of Science and TechnologyNanjing 210094China School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of Microelectronics Device and Integrated Technology Institute of Microelectronics of Chinese Academy of SciencesBeijing 100029China Department of Applied Physics The Hong Kong Polytechnic UniversityHong Kong 999077China National Laboratory of Solid State Microstructures School of Electronic Science and Engineering and Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China School of Integrated Circuits Nanjing UniversitySuzhou 215163China Suzhou Laboratory Suzhou 215009China

Developing low-power FETs holds significant importance in advancing logic circuits,especially as the feature size of MOSFETs approaches sub-10 ***,this has been restricted by the thermionic limitation of SS,which is limited to 60 mV per decade at room ***,we proposed a strategy that utilizes 2D semiconductors with an isolated-band feature as channels to realize subthermionic SS in *** high-throughput calculations,we established a guiding principle that combines the atomic structure and orbital interaction to identify their sub-thermionic transport *** guides us to screen 192 candidates from the 2D material database comprising 1608 ***,the physical relationship between the sub-thermionic transport performances and electronic structures is further revealed,which enables us to predict 15 systems with promising device performances for low-power applications with supply voltage below 0.5 *** work opens a new way for the low-power electronics based on 2D materials and would inspire extensive interests in the experimental exploration of intrinsic steep-slope MOSFETs.

关键词： 2D materials Electronic band structures Transport properties Steep-slope transistors DFT-NEGF calculations

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On-chip integrated few-mode erbium–ytterbium co-doped waveguide amplifiers

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Photonics Research 2024年第5期12卷 1067-1077页

作者： XIWEN HE DEYUE MA CHEN ZHOU MINGYUE XIAO WEIBIAO CHEN ZHIPING ZHOU Aerospace Laser Technology and Systems Department Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China School of Physical Sciences University of Science and Technology of ChinaHefei 230026China School of Microelectronics Shanghai UniversityShanghai 201800China State Key Laboratory of Advanced Optical Communications Systems and Networks School of ElectronicsPeking UniversityBeijing 100871China

We propose for the first time,to the best of our knowledge,an on-chip integrated few-mode erbium–ytterbium co-doped waveguide amplifier based on an 800 nm thick Si_(3)N_(4)platform,which demonstrates high amplification gains and low differential modal gains(DMGs)*** eccentric waveguide structure and a co-propagating pumping scheme are adopted to balance the gain of each mode.A hybrid mode/polarization/wavelengthdivision(de)multiplexer with low insertion loss and crosstalk is used for multiplexing and demultiplexing in two operation wavebands centered at 1550 nm and 980 nm,where the light in these two bands serves as the signal light and pump light of the amplifier,*** results demonstrate that with an input signal power of 0.1 mW,TE_(0)mode pump power of 300 mW,and TE_(1)mode pump power of 500 m W,the three signal modes(TE_(0)∕TM_(0)∕TE_(1))all exhibit amplification gains exceeding 30 dB,while maintaining a DMG of less than 0.1 dB.

关键词： waveguide pump amplifier

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Point-of-Care Testing (POCT) System based on self-Recovery Memoristor Chip with Low Energy Consuption(1.547 TOPS/W) and High Recognition (1142 fram/s)

Point-of-Care Testing (POCT) System based on self-Recovery M...

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International Electron Devices Meeting (IEDM)

作者： Xu Zheng Lizhou Wu Yixuan Liu Qiqiao Wu Yuanlu Xie Yi Li Jinru Lai Wenxuan Sun Danian Dong Jie Yu Xiaoxin Xu Wenchang Zhang Ming Liu State key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics of the Chinese Academy of Sciences (IMECAS) Beijing China University of the Chinese Academy of Sciences Beijing School of Microelectronics Fudan University Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China University of Science and Technology of China

The Point-of-Care Testing (POCT) system based on image analysis suffers high power consumption, detection delay and lack of privacy security. In this work, we proposed an efficient POCT system based on memristor chip, which can support edge computing and realize real-time recognition of medical graphics. To solve the problem of the decrease of long-term inference accuracy caused by chip degradation, we designed the error correction and in-situ recovery module, which increased the recognition accuracy to 90% after 250 days. Benefit by the high speed and low power consumption of the memristor, the efficiency of POCT system is up to 1.547TOPS/W and the recognition rate is reach to 1142 frames/s.

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cVTS: A Constrained Voronoi Tree Search Method for High Dimensional Analog Circuit Synthesis 23

cVTS: A Constrained Voronoi Tree Search Method for High Dime...

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Proceedings of the 60th Annual ACM/IEEE Design Automation Conference

作者： Aidong Zhao Xianan Wang Zixiao Lin Zhaori Bi Xudong Li Changhao Yan Fan Yang Li Shang Dian Zhou Xuan Zeng State Key Laboratory of Integrated Chips and Systems Microelectronics Department Fudan University Shanghai China Department of Electrical Engineering University of Texas at Dallas USA Department of Electrical and Computer Engineering University of California at San Diego USA School of Data Science Fudan University Shanghai China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9798350323481

A constrained Voronoi tree-based domain decomposition method for high-dimensional Bayesian optimization is proposed to solve large scale analog circuit synthesis problems, which can be formulated as high-dimensional heterogeneous black-box optimization. Hierarchical Voronoi tree progressively breaks down the design space into partitions with implicit performance boundaries such that promising regions are efficiently explored. Fast exploitation is ensured in Voronoi nest via local Bayesian optimization with a few observations. A slice-enhanced Gibbs sampling method is proposed to sample acquisition function cMES in irregular polyhedrons with design constraints. Compared with state-of-the-art methods, cVTS achieves significant speed up without loss of accuracy.

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Frontiers in high entropy alloys and high entropy functional materials

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Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao Zhang Xue-Qian Wang Feng-Qi Zhang Xiao-Ya Cui Bing-Bing Fan Jia-Ming Guo Zhi-Min Guo Rui Huang Wen Huang Xu-Bo Li Meng-Ru Li Yan Ma Zhi-Hua Shen Yong-Gang Sun De-Zhuang Wang Fei-Yang Wang Li-Qiang Wang Nan Wang Tian-Li Wang Wei Wang Xiao-Yang Wang Yi-Han Wang Fu-Jie Yu Yu-Zhen Yin Ling-Kun Zhang Yi Zhang Jian-Yang Zhang Qi Zhao Yu-Ping Zhao Xin-Dong Zhu Yasir Sohail Ya-Nan Chen Tao Feng Qi-Long Gao Hai-Yan He Yong-Jiang Huang Zeng-Bao Jiao Hua Ji Yao Jiang Qiang Li Xiao-Ming Li Wei-Bing Liao Huai-Jun Lin Hui Liu Qi Liu Qing-Feng Liu Wei-Di Liu Xiong-Jun Liu Yang Lu Yi-Ping Lu Wen Ma Xue-Fei Miao Jie Pan Qing Wang Hong-Hui Wu Yuan Wu Tao Yang Wei-Ming Yang Qian Yu Jin-Yu Zhang Zhi-Gang Chen Liang Mao Yang Ren Bao-Long Shen Xun-Li Wang Zhe Jia He Zhu Zhen-Duo Wu Si Lan School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and EngineeringSoutheast UniversityNanjing 211189China Department of Physics City University of Hong KongHongKong 999077China School of Materials Science and Engineering Tianjin UniversityTianjin 300072China School of Physics and Microelectronics Zhengzhou UniversityZhengzhou 450001China Department of Mechanical Engineering Research Institute for Advanced ManufacturingThe Hong Kong Polytechnic UniversityHong Kong 100872China Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou 310027China Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Institute of Advanced Wear&Corrosion Resistance and Functional Materials Jinan UniversityGuangzhou 510632China School of Mechanics and Civil Engineering China University of Mining and TechnologyXuzhou 221116China School of Physical Sciences Great Bay UniversityDongguan 523000China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical EngineeringNanjing Tech UniversityNanjing 211816China Beijing Advanced Innovation Center for Materials Genome Engineering Research Institute for Carbon NeutralityUniversity of Science and Technology BeijingBeijing 100083China Department of Mechanical Engineering The University of Hong KongHong Kong 999077China School of Computing Macquarie UniversitySydney 2113Australia Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laborato

Owing to their exceptional properties,high-entropy alloys(HEAs)and high-entropy materials have emerged as promising research areas and shown diverse ***,the recent advances in the field are comprehensively reviewed,organized into five *** first section introduces the background of HEAs,covering their definition,significance,application prospects,basic properties,design principles,and *** subsequent section focuses on cutting-edge high-entropy structural materials,highlighting developments such as nanostructured alloys,grain boundary engineering,eutectic systems,cryogenic alloys,thin films,micro-nano-lattice structures,additive manufacturing,high entropy metallic glasses,nano-precipitate strengthened alloys,composition modulation,alloy fibers,and refractory *** the following section,the emphasis shifts to functional materials,exploring HEAs as catalysts,magneto-caloric materials,corrosion-resistant alloys,radiation-resistant alloys,hydrogen storage systems,and materials for ***,the review encompasses functional high-entropy materials outside the realm of alloys,including thermoelectric,quantum dots,nanooxide catalysts,energy storage materials,negative thermal expansion ceramics,and high-entropy wave absorption *** paper concludes with an outlook,discussing future directions and potential growth areas in the *** this comprehensive review,researchers,engineers,and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： High entropy alloys Cutting-edge structural materials Cutting-edgefunctional materials

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BMRMIA:A Platform for Radiologists to Systematically Learn Automated Medical Image Analysis by Three Dimensional Medical Decision Support System

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Computer Modeling in engineering & Sciences 2022年第5期131卷 851-863页

作者： Yankun Cao Lina Xu Zhi Liu Xiaoyan Xiao Mingyu Wang Qin Li Hongji Xu Geng Yang School of Software Shandong UniversityJinan250101China School of Information Science and Engineering Shandong UniversityQingdao266237China School of Computer Science and Technology Shandong Jianzhu UniversityJinan250012China Department of Nephrology Qilu Hospital of Shandong UniversityJinan250012China State Key Laboratory of ASIC&Systems The School of MicroelectronicsFudan UniversityShanghai200433China Shenzhen Institute of Information Technology Shenzhen518172China

Contribution:This paper designs a learning and training platform that can systematically help radiologists learn automated medical image analysis *** platform can help radiologists master deep learning theories and medical applications such as the three-dimensional medical decision support system,and strengthen the teaching practice of deep learning related courses in hospitals,so as to help doctors better understand deep learning knowledge and improve the efficiency of auxiliary ***:In recent years,deep learning has been widely used in academia,industry,*** increasing number of companies are starting to recruit a large number of professionals in the field of deep *** numbers of colleges and universities also offer courses related to deep learning to help radiologists learn automated medical image analysis *** now,however,there is no practical training platform that can help radiologists learn automated medical image analysis ***:The platform proposes the basic learning,model combat,business application(BMR)concept,including the learning guidance system and the assessment training system,which constitutes a closed-loop learning guidance mode of“learning-assessment-training-learning”.Findings:The survey results show that most of radiologists met their learning expectations by using this *** platform can help radiologists master deep learning techniques quickly,comprehensively and firmly.

关键词： BMR deep learning three dimensional medical decision support system deep learning engineer standard

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P-10.2: Design and Simulation of Integrated Ultraviolet HEMT-LED enabled by P-GaN Selective Epitaxy Growth

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SID Symposium Digest of Technical Papers 2023年第S1期54卷 789-791页

作者： Jingyang Zhang Wei Huang Zhaojun Liu Department of electronic and electrical engineering Southern University of Science and Technology Shenzhen Guangdong China 518055 A State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics & Systems School of Microelectronics Fudan University Shanghai China 200433

Based on previous work, the ultraviolet HEMT-LED we fabricated by selective epitaxy growth, this paper further performed simulation to explore the most appropriate p-GaN selection size. P-GaN grown by Selective Epitaxy Growth (SEG) can not only be employed as a junction termination to reduce the electric field crowding of the gate of HEMT, but also form an active region by contacting with 2-dimentional electron gas (2DEG). The simulation results provide an effective reference for the design of p-GaN grown by SEG, and further pave the way for the realization of the idea of integration through the selection of growth methods.

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Memristor-Based Bayesian Spiking Neural Network for Ibd Diagnosis

SSRN

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SSRN 2024年

作者： Ma, Jianxia Li, Xiaowen Wu, Qiqiao Chen, Yuanwen Yang, Jianguo Jin, Yang Department of Gastroenterology Hua Dong Hospital FuDan University Shanghai200040 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200438 China State Key Laboratory of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China Zhangjiang Lab. Shanghai201210 China

Traditional deep learning methods, such as deep neural networks, have achieved remarkable success in image processing, natural language processing, graph computation, and other fields. However, in the diagnosis of Inflammatory Bowel Disease (IBD), conventional deep learning methods are highly susceptible to generating overconfident results, which can lead to great loss of life and property if it results in misdiagnosis of the patient. In this work, we propose a memristor-based IBD diagnostic system inspired by the idea of variational inference based on Bayes' law. The memristors in our system are used for both synaptic weight storage and entropy sources so that an efficient Bayesian inference system can be realized. Our memristor-based true random number generator can produce probability-tunable bitstreams required for Bayesian inference with a mean-square error that is reduced by 10.9× than that of a conventional pseudo-random generator. The proposed system consists of a coarse-grained and a fined-grained spiking neural network, and an optimized strategy that trims the neuron’s threshold is proposed for maintaining the appropriate model sparsity and reducing information loss. With Bayesian inference, our work achieves lower diagnostic error rates, which are reduced by 10.79% and 0.49% for the coarse-grained and fine-grained networks, respectively. The proposed system is easy to hardware implement and presents a novel solution for community-wide IBD diagnosis. © 2024, The Authors. All rights reserved.

关键词： Mean square error

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Nondestructive visualization of graphene on Pt with methylene blue surface modification

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Science China Materials 2022年第10期65卷 2763-2770页

作者： He Kang Yanhui Zhang Yun Wu Shike Hu Jing Li Zhiying Chen Yanping Sui Shuang Wang Sunwen Zhao Runhan Xiao 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 Science and Technology on Monolithic Integrated Circuits and Modules Laboratory Nanjing Electronic Device InstituteNanjing 210016China Microwave Devices and Integrated Circuits Department Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China

Efficient large-scale nondestructive quality assessment of graphene on Pt is essential to the in-depth growth research and practical applications of ***,we present a very simple method for directly observing the domains and defects in graphene on Pt using an ordinary optical *** was achieved by modifying graphene on Pt using methylene blue(MB).Because the chemical activities of graphene and Pt surface differ significantly,the adsorption and reaction of MB on graphene and platinum surface *** can determine the distribution of graphene crystal domains and defects by comparing the colors in the optical *** addition,this characterization method causes no obvious damage to the Pt substrate and ***,it does not affect the recycling of the substrate or the subsequent characterization or application of *** study provides a nondestructive method for measuring the quality of graphene on Pt on a large scale,as well as a reference for the characterization and doping of other two-dimensional materials.

关键词： graphene Pt nondestructive visualization surface modification methylene blue

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High Area Efficiency (6 TOPS/mm2) Multimodal Neuromorphic Computing System Implemented by 3D Multifunctional RRAM Array

High Area Efficiency (6 TOPS/mm2) Multimodal Neuromorphic Co...

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International Electron Devices Meeting (IEDM)

作者： Wenxuan Sun Yi Li Woyu Zhang Xu Zheng Danian Dong Jie Yu Jinru Lai Shaoyang Fan Hongzhou Wang Xiaoxin Xu Ming Liu State Key Lab of Fabrication Technologies for Integrated Circuits Institute of Microelectronics Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China Fudan University Shanghai China

For the first time, we demonstrated a multifunction three-dimensional (3D) vertical random-access memory (RRAM) array (MF-ЗDRRAM) where different layers exhibit nonvolatile properties and volatile characteristics respectively, to implement multimodal neuromorphic computing. The RRAM cells in the 1 st layer (WL: TiN) and the 2 nd layer (WL: Ru) have different dynamic characteristics, which are used to construct multi-scale reservoirs (M-RC). The RRAM in 3 rd layer (WL: W) exhibits analog switching behavior, applying for convolutional neural network (CNN) and full connection (FC) layer. A multimodal neuromorphic computing system with the network of M-RC+CNN is implemented by the MF-3DRRAM. The multifunction of the fabricated MF-3DRRAM chip is validated through the multimodal video recognition task, exhibiting high accuracy (98%), high area efficiency (6 TOPS/mm2) and low energy consumption (1.4pJ/operation). This proposed MF-3DRRAM is of great significance for miniaturized, low-power hardware implementations for edge computing.

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