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Piezotronic neuromorphic devices:principle,manufacture,and applications

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International Journal of Extreme Manufacturing 2024年第3期6卷 363-385页

作者： Xiangde Lin Zhenyu Feng Yao Xiong Wenwen Sun Wanchen Yao Yichen Wei Zhong Lin Wang Qijun Sun Department of Research Shanghai University of Medicine and Health Sciences Affiliated Zhoupu HospitalShanghai 201318People’s Republic of China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 101400People’s Republic of China Center on Nanoenergy Research School of Chemistry and Chemical EngineeringGuangxi UniversityNanning 530004People’s Republic of China Shandong Zhongke Naneng Energy Technology Co. LtdDongying 257061People’s Republic of China Georgia Institute of Technology AtlantaGA 30332-0245United States of America

With the arrival of the era of artificial intelligence(AI)and big data,the explosive growth of data has raised higher demands on computer hardware and *** techniques inspired by biological nervous systems are expected to be one of the approaches to breaking the von Neumann *** neuromorphic devices modulate electrical transport characteristics by piezopotential and directly associate external mechanical motion with electrical output signals in an active manner,with the capability to sense/store/process information of external *** this review,we have presented the piezotronic neuromorphic devices(which are classified into strain-gated piezotronic transistors and piezoelectric nanogenerator-gated field effect transistors based on device structure)and discussed their operating mechanisms and related manufacture ***,we summarized the research progress of piezotronic neuromorphic devices in recent years and provided a detailed discussion on multifunctional applications,including bionic sensing,information storage,logic computing,and electrical/optical artificial ***,in the context of future development,challenges,and perspectives,we have discussed how to modulate novel neuromorphic devices with piezotronic effects more *** is believed that the piezotronic neuromorphic devices have great potential for the next generation of interactive sensation/memory/computation to facilitate the development of the Internet of Things,AI,biomedical engineering,etc.

关键词： piezotronics neuromorphic devices strain-gated transistors piezoelectric nanogenerators synaptic transistors

CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review

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International Journal of Extreme Manufacturing 2023年第4期5卷 292-312页

作者： Yixin Zhu Huiwu Mao Ying Zhu Xiangjing Wang Chuanyu Fu Shuo Ke Changjin Wan Qing Wan School of Electronic Science and Engineering and Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023People’s Republic of China Yongjiang Lab Ningbo 315201People’s Republic of China School of Micro-Nano Electronics Hangzhou Global Scientific and Technological Innovation CentreZhejiang University38 Zheda RoadHangzhou 310027People’s Republic of China

neuromorphic computing is a brain-inspired computing paradigm that aims to construct efficient,low-power,and adaptive computing systems by emulating the information processing mechanisms of biological neural *** the core of neuromorphic computing are neuromorphic devices that mimic the functions and dynamics of neurons and synapses,enabling the hardware implementation of artificial neural *** types of neuromorphic devices have been proposed based on different physical mechanisms such as resistive switching devices and electric-double-layer *** devices have demonstrated a range of neuromorphic functions such as multistate storage,spike-timing-dependent plasticity,dynamic filtering,*** achieve high performance neuromorphic computing systems,it is essential to fabricate neuromorphic devices compatible with the complementary metal oxide semiconductor(CMOS)manufacturing *** improves the device’s reliability and stability and is favorable for achieving neuromorphic chips with higher integration density and low power *** review summarizes CMOS-compatible neuromorphic devices and discusses their emulation of synaptic and neuronal functions as well as their applications in neuromorphic perception and *** highlight challenges and opportunities for further development of CMOS-compatible neuromorphic devices and systems.

关键词： neuromorphic computing neuromorphic devices CMOS-compatible resistive switching device transistor

neuromorphic circuits based on memristors: endowing robots with a human-like brain

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Journal of Semiconductors 2024年第6期45卷 47-63页

作者： Xuemei Wang Fan Yang Qing Liu Zien Zhang Zhixing Wen Jiangang Chen Qirui Zhang Cheng Wang Ge Wang Fucai Liu School of Optoelectronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu 610054China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313099China

Robots are widely used,providing significant convenience in daily life and *** the rapid development of artificial intelligence and neuromorphic computing in recent years,the realization of more intelligent robots through a pro-found intersection of neuroscience and robotics has received much *** circuits based on memristors used to construct hardware neural networks have proved to be a promising solution of shattering traditional control limita-tions in the field of robot control,showcasing characteristics that enhance robot intelligence,speed,and energy ***-ing with introducing the working mechanism of memristors and peripheral circuit design,this review gives a comprehensive analysis on the biomimetic information processing and biomimetic driving operations achieved through the utilization of neuro-morphic circuits in brain-like *** hardware neural network approaches,including digital-analog hybrid circuit design,novel device structure design,multi-regulation mechanism,and crossbar array,are summarized,which can well simulate the motor decision-making mechanism,multi-information integration and parallel control of brain at the hardware *** will be definitely conductive to promote the application of memristor-based neuromorphic circuits in areas such as intelligent robotics,artificial intelligence,and neural ***,a conclusion and future prospects are discussed.

关键词： neuromorphic devices neuromorphic circuits hardware networks memristors humanlike robots

Advances in the Application of Perovskite Materials

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Nano-Micro Letters 2023年第10期15卷 334-381页

作者： Lixiu Zhang Luyao Mei Kaiyang Wang Yinhua Lv Shuai Zhang Yaxiao Lian Xiaoke Liu Zhiwei Ma Guanjun Xiao Qiang Liu Shuaibo Zhai Shengli Zhang Gengling Liu Ligang Yuan Bingbing Guo Ziming Chen Keyu Wei Aqiang Liu Shizhong Yue Guangda Niu Xiyan Pan Jie Sun Yong Hua Wu‑Qiang Wu Dawei Di Baodan Zhao Jianjun Tian Zhijie Wang Yang Yang Liang Chu Mingjian Yuan Haibo Zeng Hin‑Lap Yip Keyou Yan Wentao Xu Lu Zhu Wenhua Zhang Guichuan Xing Feng Gao Liming Ding Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing 100190People’s Republic of China University of Chinese Academy of Sciences Beijing 100049People’s Republic of China Department of Physics Link.ping University58183 Link.pingSweden Institute of Applied Physics and Materials Engineering University of MacaoMacao 999078People’s Republic of China School of Materials Science and Engineering Yunnan UniversityKunming 650091People’s Republic of China School of Microelectronics Science and Technology Sun Yat-sen UniversityZhuhai 519082People’s Republic of China College of Electronic Information and Optical Engineering Nankai UniversityTianjin 300350People’s Republic of China Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of TechnologyShenzhen 518055People’s Republic of China School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094People’s Republic of China College of Optical Science and Engineering Zhejiang UniversityHangzhou 310027People’s Republic of China State Key Laboratory of Superhard Materials Jilin UniversityChangchun 130012People’s Republic of China College of Electronic and Optical Engineering Nanjing University of Posts and TelecommunicationsNanjing 210023People’s Republic of China School of Chemistry Sun Yat-sen UniversityGuangzhou 510006People’s Republic of China School of Environment and Energy South China University of TechnologyGuangzhou 510000People’s Republic of China Department of Chemistry Imperial College LondonLondon W120BZUK College of Chemistry Nankai UniversityTianjin 300071People’s Republic of China Institute for Advanced Materials and Technology University of Science and Technology BeijingBeijing 100083People’s Republic of China Institute of Semiconductors Chinese Academy of SciencesBeijing 100083People’s Republic of China School

Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allow metal halide perovskite to be employed in a wide variety of applications. This article provides a holistic review over the current progress and future prospects of metal halide perovskite materials in representative promising applications, including traditional optoelectronic devices(solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices(artificial synapses and memristors) and pressure-induced emission. This review highlights the fundamentals, the current progress and the remaining challenges for each application, aiming to provide a comprehensive overview of the development status and a navigation of future research for metal halide perovskite materials and devices.

关键词： Perovskites Optoelectronic devices neuromorphic devices Pressure-induced emission