Yan Wang , Chaohui Su , Yiming Zheng , Kexin Zhou , Zhenli Wen , Yujun Fu , Qi Wang , Deyan He
{"title":"High consistency VO2 memristor for artificial auditory neuron","authors":"Yan Wang , Chaohui Su , Yiming Zheng , Kexin Zhou , Zhenli Wen , Yujun Fu , Qi Wang , Deyan He","doi":"10.1016/j.mee.2023.112101","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>With scalability and diverse device behavior, memristors present potential for executing neuromorphic computation with lower hardware cost and </span>power consumption. However, Low consistency currently limited the application of memristors. Herein, we report a VO</span><sub>2</sub><span>-based memristor fabricated through magnetron<span> sputtering and multiple annealing processes<span>, exhibiting extremely low in both cycle-to-cycle (C2C) and device-to-device (D2D) variations. Further, a Hodgkin-Huxley model neuron circuit based on the extremely high consistency of the devices is established, which achieves auditory neuron perception simulation through spatiotemporal processing of spike signals, allowing for clear differentiation of sound source direction and displaying patterns akin to biological behavior. This easily implemented and highly consistent artificial neuron offers a promising approach for the development of next-generation artificial auditory systems.</span></span></span></p></div>","PeriodicalId":18557,"journal":{"name":"Microelectronic Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Microelectronic Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167931723001661","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
With scalability and diverse device behavior, memristors present potential for executing neuromorphic computation with lower hardware cost and power consumption. However, Low consistency currently limited the application of memristors. Herein, we report a VO2-based memristor fabricated through magnetron sputtering and multiple annealing processes, exhibiting extremely low in both cycle-to-cycle (C2C) and device-to-device (D2D) variations. Further, a Hodgkin-Huxley model neuron circuit based on the extremely high consistency of the devices is established, which achieves auditory neuron perception simulation through spatiotemporal processing of spike signals, allowing for clear differentiation of sound source direction and displaying patterns akin to biological behavior. This easily implemented and highly consistent artificial neuron offers a promising approach for the development of next-generation artificial auditory systems.
期刊介绍:
Microelectronic Engineering is the premier nanoprocessing, and nanotechnology journal focusing on fabrication of electronic, photonic, bioelectronic, electromechanic and fluidic devices and systems, and their applications in the broad areas of electronics, photonics, energy, life sciences, and environment. It covers also the expanding interdisciplinary field of "more than Moore" and "beyond Moore" integrated nanoelectronics / photonics and micro-/nano-/bio-systems. Through its unique mixture of peer-reviewed articles, reviews, accelerated publications, short and Technical notes, and the latest research news on key developments, Microelectronic Engineering provides comprehensive coverage of this exciting, interdisciplinary and dynamic new field for researchers in academia and professionals in industry.