Neural Synaptic Simulation Based on ZnAlSnO Thin-Film Transistors.

IF 3 3区 工程技术 Q2 CHEMISTRY, ANALYTICAL
Micromachines Pub Date : 2025-09-07 DOI:10.3390/mi16091025
Yang Zhao, Chao Wang, Laizhe Ku, Liang Guo, Xuefeng Chu, Fan Yang, Jieyang Wang, Chunlei Zhao, Yaodan Chi, Xiaotian Yang
{"title":"Neural Synaptic Simulation Based on ZnAlSnO Thin-Film Transistors.","authors":"Yang Zhao, Chao Wang, Laizhe Ku, Liang Guo, Xuefeng Chu, Fan Yang, Jieyang Wang, Chunlei Zhao, Yaodan Chi, Xiaotian Yang","doi":"10.3390/mi16091025","DOIUrl":null,"url":null,"abstract":"<p><p>In the era of artificial intelligence, neuromorphic devices that simulate brain functions have received increasingly widespread attention. In this paper, an artificial neural synapse device based on ZnAlSnO thin-film transistors was fabricated, and its electrical properties were tested: the current-switching ratio was 1.18 × 10<sup>7</sup>, the subthreshold oscillation was 1.48 V/decade, the mobility was 2.51 cm<sup>2</sup>V<sup>-1</sup>s<sup>-1</sup>, and the threshold voltage was -9.40 V. Stimulating artificial synaptic devices with optical signals has the advantages of fast response speed and good anti-interference ability. The basic biological synaptic characteristics of the devices were tested under 365 nm light stimulation, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term plasticity (STP), and long-term plasticity (LTP). This device shows good synaptic plasticity. In addition, by changing the gate voltage, the excitatory postsynaptic current of the device at different gate voltages was tested, two different logical operations of \"AND\" and \"OR\" were achieved, and the influence of different synaptic states on memory was simulated. This work verifies the application potential of the device in the integrated memory and computing architecture, which is of great significance for promoting the high-quality development of neuromorphic computing hardware.</p>","PeriodicalId":18508,"journal":{"name":"Micromachines","volume":"16 9","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12471619/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Micromachines","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/mi16091025","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

Abstract

In the era of artificial intelligence, neuromorphic devices that simulate brain functions have received increasingly widespread attention. In this paper, an artificial neural synapse device based on ZnAlSnO thin-film transistors was fabricated, and its electrical properties were tested: the current-switching ratio was 1.18 × 107, the subthreshold oscillation was 1.48 V/decade, the mobility was 2.51 cm2V-1s-1, and the threshold voltage was -9.40 V. Stimulating artificial synaptic devices with optical signals has the advantages of fast response speed and good anti-interference ability. The basic biological synaptic characteristics of the devices were tested under 365 nm light stimulation, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term plasticity (STP), and long-term plasticity (LTP). This device shows good synaptic plasticity. In addition, by changing the gate voltage, the excitatory postsynaptic current of the device at different gate voltages was tested, two different logical operations of "AND" and "OR" were achieved, and the influence of different synaptic states on memory was simulated. This work verifies the application potential of the device in the integrated memory and computing architecture, which is of great significance for promoting the high-quality development of neuromorphic computing hardware.

Abstract Image

Abstract Image

Abstract Image

基于ZnAlSnO薄膜晶体管的神经突触模拟。
在人工智能时代,模拟大脑功能的神经形态装置受到越来越广泛的关注。本文制作了一种基于ZnAlSnO薄膜晶体管的人工神经突触器件,并对其电学性能进行了测试:电流开关比为1.18 × 107,亚阈值振荡为1.48 V/decade,迁移率为2.51 cm2V-1s-1,阈值电压为-9.40 V。用光信号刺激人工突触装置具有响应速度快、抗干扰能力好等优点。在365 nm光刺激下测试了器件的基本生物学突触特性,包括兴奋性突触后电流(EPSC)、配对脉冲促进(PPF)、短期可塑性(STP)和长期可塑性(LTP)。这种装置显示出良好的突触可塑性。此外,通过改变栅电压,测试了器件在不同栅电压下的兴奋性突触后电流,实现了“与”和“或”两种不同的逻辑运算,并模拟了不同的突触状态对记忆的影响。本工作验证了该器件在集成存储与计算架构中的应用潜力,对推动神经形态计算硬件的高质量发展具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Micromachines
Micromachines NANOSCIENCE & NANOTECHNOLOGY-INSTRUMENTS & INSTRUMENTATION
CiteScore
5.20
自引率
14.70%
发文量
1862
审稿时长
16.31 days
期刊介绍: Micromachines (ISSN 2072-666X) is an international, peer-reviewed open access journal which provides an advanced forum for studies related to micro-scaled machines and micromachinery. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信