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Novel vertical channel double gate structures for high density and low power flash memory applications

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Science in China(Series F) 2008年第6期51卷 799-806页

作者： HUANG Ru ZHOU FaLong cai yimao WU DaKe ZHANG Xing Institute of Microelectronics Peking University Beijing 100871 China

The flash memory technology meets physical and technical obstacles in further scaling. New structures and new materials are implemented as possible solutions. This paper focuses on two kinds of new flash cells for high density and low power memory applications based on the vertical channel double gate structure. The proposed VD-NROM with dual-nitride-trapping-layer and vertical structure can achieve four-bit-per-cell storage capability. And the proposed VSAS-FG cell benefits the high programming efficiency, low power and high density capability, which can be realized without any additional mask and can achieve the self-alignment of the split-gate channel and the floating-gate. The two novel flash cell structures can be considered as potential candidates for different flash memory applications.

关键词： double gate devices flash memory high density low power

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An isolated symmetrical 2T2R cell enabling high precision and high density for RRAM-based in-memory computing

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Science China(Information Sciences) 2024年第5期67卷 287-294页

作者： Yaotian LING Zongwei WANG Yuhang YANG Lin BAO Shengyu BAO Qishen WANG yimao cai Ru HUANG School of Integrated Circuits Beijing Advanced Innovation Center for Integrated Circuits Peking University State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications

In-memory computing(IMC), leveraging emerging memories, holds significant promise in overcoming memory limitations and improving energy efficiency. However, the prevailing IMC array structure based on serially connected transistors and memory cells(1T1R/2T2R), along with the signed weight mapping scheme, can lead to asymmetrical weight sensing issues(AWS) due to electrical asymmetry within the1T1R/2T2R structure, particularly in highly scaled cells where the transistor's resistance becomes significant. In this paper, we propose and fabricate an electrically symmetric memory cell based on a physically isolated 2T2R structure for IMC. This design aims to enhance the precision and density of RRAM-based IMC arrays. The 2T2R cells are manufactured using the back-end-of-line(BEOL) process of a commercial40 nm technology platform. The feasibility of this design is verified through measured and simulated results,showcasing its capability to address the issue of AWS. Compared to conventional 2T2R cells, this design achieves a considerably smaller transistor footprint without compromising accuracy, while also improving integration density by 42.2%. These innovative memory cell advancements have the potential to further advance high-energy-efficient IMC technology.

关键词： RRAM 2T2R multi-level storage weight asymmetry in-memory computing

Integration of biocompatible organic resistive memory and photoresistor for wearable image sensing application

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Science China(Information Sciences) 2018年第6期61卷 32-39页

作者： Qingyu CHEN Min LIN Yichen FANG Zongwei WANG Yuchao YANG Jintong XU yimao cai Ru HUANG Institute of Microelectronics Peking University Research Center of Flexible Electronics Peking University Key Laboratory of Infrared Imaging Materials and Detectors Shanghai Institute of Technical PhysicsChinese Academy of Sciences

The integration of multiple functional devices to achieve complex functions has become an essential requirement for future wearable biomedical electronic devices and systems. In this paper, we present a flexible multi-functional device composed of a biocompatible organic polymer resistive random-access memory(RRAM) and a photoresistor for wearable image sensing application. The resistive layer of organic polymer RRAM is composed by polychloro-para-xylylene(parylene-C), which is a flexible, transparent, biocompatibility and chemical stability polymer material. What is more, parylene-C is quite safe to be used within human body as it is a Food and Drug Administration(FDA)-approved material. This organic RRAM shows stable switching characteristics, low operation voltages(3.25 V for set voltage and-0.55 V for reset voltage), low static power consumption, high storage window and good retention properties(>104s).A multi-functional device that can detect the light intensity of incident light and simultaneously store the information in the memory devices for wearable image sensing application was proposed and fabricated by integrating the organic resistive memory and a photoresistor. The threshold of incident light intensity can be easily adjust by changing the external voltage. This device is promising for building wearable electronic systems with various multiple functionalities.

关键词： wearable device image sensor flexible biocompatible resistive random-access memory(RRAM) photoresistor

Investigation of Nb Ox-based volatile switching device with self-rectifying characteristics

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Science China(Information Sciences) 2019年第12期62卷 277-280页

作者： Yichen FANG Zongwei WANG caidie CHENG Zhizhen YU Teng ZHANG Yuchao YANG yimao cai Ru HUANG Key Laboratory of Microelectronic Devices and Circuits (MOE) Institute of MicroelectronicsPeking University

Dear editor,Resistive random access memory (RRAM), one of the most promising emerging non-volatile memory technologies, has been extensively investigated by researchers from both academia and industry due to its fast ... 详细信息

关键词： Investigation of Nb Ox-based volatile switching device with self-rectifying characteristics

Memory materials and devices:From concept to application

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InfoMat 2020年第2期2卷 261-290页

作者： Zhenhan Zhang Zongwei Wang Tuo Shi Chong Bi Feng Rao yimao cai Qi Liu Huaqiang Wu Peng Zhou State Key Laboratory of ASIC and System School of MicroelectronicsFudan UniversityShanghaiChina Key Laboratory of Microelectronic Devices and Circuits(MOE) Institute of MicroelectronicsPeking UniversityBeijingChina Key Laboratory of Microelectronic Devices and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijingChina College of Materials Science and Engineering Shenzhen UniversityShenzhenChina Institute of Microelectronics Tsinghua UniversityBeijingChina

Memory cells have always been an important element of information *** emerging technologies like big data and cloud computing,the scale and complexity of data storage has reached an unprecedented peak with a much higher requirement for memory *** is well known,better data storage is mostly achieved by ***,as the size of the memory device is reduced,a series of problems,such as drain gate-induced leakage,greatly hinder the performance of memory *** meet the increasing demands of information technology,novel and high-performance memory is urgently ***,emerging memory technologies are expected to improve memory performance and drive the information *** review will focus on the progress of several emerging memory technologies,including two-dimensional material-based memories,resistance random access memory(RRAM),magnetic random access memory(MRAM),and phasechange random access memory(PCRAM).Advantages,mechanisms,and applications of these diverse memory technologies will be discussed in this review.

关键词： memory MRAM PCRAM RRAM two-dimensional material

Investigation and mitigation of Mott neuronal oscillation fluctuation in spiking neural network

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Science China(Information Sciences) 2024年第2期67卷 291-301页

作者： Lindong WU Zongwei WANG Lin BAO Linbo SHAN Zhizhen YU Yunfan YANG Shuangjie ZHANG Guandong BAI Cuimei WANG John ROBERTSON Yuan WANG yimao cai Ru HUANG School of Integrated Circuits Peking University Beijing Advanced Innovation Center for Integrated Circuits State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Department of Engineering University of Cambridge

Mott devices, featuring low hardware cost and high energy efficiency, have been demonstrated as a key oscillatory element in artificial neurons to enable spiking neural networks(SNNs) such as conversionbased SNNs(CSNNs). However, there will be inevitably non-ideal fluctuation in the oscillation behavior,causing the accuracy degradation of networks. In this paper, we investigate the Mott neuronal oscillation fluctuation(NOF) through experiments and modeling. The results show that the NOF phenomenon conforms to Gaussian distribution and originates from thermal fluctuation induced switching voltage variations. We construct a two-layer CSNN for image recognition tasks to study the NOF effect and propose the activation function boundary(AFB) method to strengthen the stability of the network. The results indicate that AFB can improve the accuracy of CSNN by up to 15.5% by tightening output distribution.

关键词： Mott neuron oscillation fluctuation variation-aware Mott neuronal model conversion-based spiking neural network activation function boundary

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面向新型计算架构的存算融合晶体管器件研究

科学通报 2023年第35期68卷 4862-4871页

作者：蔡一茂吴林东鲍霖王宗巍北京大学集成电路学院北京100871 北京市集成电路高精尖创新中心北京100871 北京邮电大学信息光子学与光通信国家重点实验室北京100876

基于金属-氧化物-半导体场效应晶体管(metal-oxide-semiconductor field-effect transistor,MOSFET)器件和冯·诺伊曼架构的半导体芯片技术带领人类迈进了信息化时代.近年来,新型计算架构蓬勃发展.然而,专用算法和类脑智能算法映射至MOS... 详细信息

基于金属-氧化物-半导体场效应晶体管(metal-oxide-semiconductor field-effect transistor,MOSFET)器件和冯·诺伊曼架构的半导体芯片技术带领人类迈进了信息化时代.近年来,新型计算架构蓬勃发展.然而,专用算法和类脑智能算法映射至MOSFET电路时,通常面临硬件开销大、系统能效低等挑战.针对上述问题,本文研制了具有存算融合特点的新型晶体管器件,有效适配了专用算法和类脑计算应用:在基础数值计算方面,针对多项式计算,研制了电荷捕获型晶体管,利用器件的本征非线性动力学特征,基于单器件实现了三元素乘法运算,有效加速了多项式回归任务;在新兴智能计算方面,针对神经网络计算,研制了离子栅型神经形态晶体管,利用双栅耦合的方式实现了神经元的非线性激活和时空信息整合功能,并基于此提出了神经元相关性脉冲神经网络,实现了注意力转变现象的模拟.本文的工作将为新型计算架构芯片的构建提供新的思路.

关键词：电荷捕获型晶体管离子栅型晶体管多项式加速计算类脑神经网络

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Editor’s note

Science China(Information Sciences) 2011年第5期54卷 913-914页

作者： HUANG Ru, Guest Editor Peking University Beijing 100871, China ZHAO Bin, Guest Editor Fairchild Semiconductor 32 Discovery, Irvine, CA 92618, USA WANG RunSheng, Guest Editor Assistant cai yimao, Guest Editor Assistant Peking University Beijing 100871, China Peking University Beijing China Fairchild Semiconductor Irvine USA

In recent years, driven by ever-increasing market demand in computing, communication, and multimedia applications, the microelectronics industry has undergone rapid development. Because of technical innovation and advances in almost all aspects of materials, processes, equipment, devices, circuits and systems, siliconbased logic and memory IC technologies using nano-scaling continue to be the industry’s major R&D focus. This maintains microelectronics industry adherence to the traditional "Moore’s Law", increasing the function

关键词： than s note Editor

Toward memristive in-memory computing:principles and applications

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Frontiers of Optoelectronics 2022年第2期15卷 101-125页

作者： Han Bao Houji Zhou Jiancong Li Huaizhi Pei Jing Tian Ling Yang Shengguang Ren Shaoqin Tong Yi Li Yuhui He Jia Chen yimao cai Huaqiang Wu Qi Liu Qing Wan Xiangshui Miao School of Integrated Circuits School of Optical and Electronic InformationWuhan National Laboratory for OptoelectronicsOptics Valley LaboratoryHuazhong University of Science and TechnologyWuhan 430074China Hubei Yangtze Memory Laboratories Wuhan430205China AI Chip Center for Emerging Smart Systems InnoHK CentersHong Kong Science ParkHong KongChina School of Integrated Circuits Peking UniversityBeijing 100871China School of Integrated Circuits Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084China Frontier Institute of Chip and System Fudan UniversityShanghai 200433China School of Electronic Science and Engineering and Collaborative Innovation Centre of Advanced MicrostructuresNanjing UniversityNanjing 210093China

With the rapid growth of computer science and big data,the traditional von Neumann architecture suffers the aggravating data communication costs due to the separated structure of the processing units and *** in-memory computing paradigm is considered as a prominent candidate to address these issues,and plentiful applications have been demonstrated and *** applications can be broadly categorized into two major types:soft computing that can tolerant uncertain and imprecise results,and hard computing that emphasizes explicit and precise numerical results for each task,leading to different requirements on the computational accuracies and the corresponding hardware *** this review,we conduct a thorough survey of the recent advances of memristive in-memory computing applications,both on the soft computing type that focuses on artificial neural networks and other machine learning algorithms,and the hard computing type that includes scientific computing and digital image *** the end of the review,we discuss the remaining challenges and future opportunities of memristive in-memory computing in the incoming Artificial Intelligence of Things era.

关键词： Memristor In-memory computing Matrix-vector multiplication Machine learning Scientific computing Digital image processing

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