Imitation of a Dual-Modal Synapse Based on a Hf0.5Zr0.5O2 Ferroelectric Tunnel Junction for Neuromorphic Computing

IF 4.3 3区材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-13 DOI:10.1021/acsaelm.4c0143410.1021/acsaelm.4c01434

Hang Yang, Mengyuan Duan, Chaoyang Kang, Guanghong Yang*, Weifeng Zhang* and Caihong Jia*,

{"title":"Imitation of a Dual-Modal Synapse Based on a Hf0.5Zr0.5O2 Ferroelectric Tunnel Junction for Neuromorphic Computing","authors":"Hang Yang, Mengyuan Duan, Chaoyang Kang, Guanghong Yang*, Weifeng Zhang* and Caihong Jia*, ","doi":"10.1021/acsaelm.4c0143410.1021/acsaelm.4c01434","DOIUrl":null,"url":null,"abstract":"Bioinspired artificial synapses have attracted considerable attention in the field of neuromorphic computing. Hf0.5Zr0.5O2 thin films exhibit robust ferroelectricity even at a thickness of less than 10 nm, which contributes to energy efficiency and fast write/read speed. In this work, we report a low-cost and low-energy consumption dual-modal synapse with both excitation and inhibition in a Hf0.5Zr0.5O2 ferroelectric tunnel junction. This transition is controlled by ferroelectric polarization switching and electron trapping by adjusting pulse duration. Furthermore, its excitation effect can simulate logic operations and pain perception nociceptors. The combined excitation and inhibition effects can simulate the dual-pulse Bienenstock–Cooper–Munro learning rule and image edge recognition. This contributes to the development of in-memory computing, image processing, and analog perception systems.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"88","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acsaelm.4c01434","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

Abstract

Bioinspired artificial synapses have attracted considerable attention in the field of neuromorphic computing. Hf_0.5Zr_0.5O₂ thin films exhibit robust ferroelectricity even at a thickness of less than 10 nm, which contributes to energy efficiency and fast write/read speed. In this work, we report a low-cost and low-energy consumption dual-modal synapse with both excitation and inhibition in a Hf_0.5Zr_0.5O₂ ferroelectric tunnel junction. This transition is controlled by ferroelectric polarization switching and electron trapping by adjusting pulse duration. Furthermore, its excitation effect can simulate logic operations and pain perception nociceptors. The combined excitation and inhibition effects can simulate the dual-pulse Bienenstock–Cooper–Munro learning rule and image edge recognition. This contributes to the development of in-memory computing, image processing, and analog perception systems.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于 Hf0.5Zr0.5O2 铁电隧道结的双模突触仿真，用于神经形态计算

受生物启发的人工突触在神经形态计算领域备受关注。即使厚度小于 10 纳米，Hf0.5Zr0.5O2 薄膜也能表现出强大的铁电性，这有助于提高能效和快速写入/读取速度。在这项工作中，我们报告了一种在 Hf0.5Zr0.5O2 铁电隧道结中同时具有激励和抑制功能的低成本、低能耗双模突触。通过调节脉冲持续时间，铁电极化转换和电子捕获可以控制这种转换。此外，其激发效应可以模拟逻辑运算和痛觉感受器。激发和抑制的组合效应可以模拟双脉冲比能斯托克-库珀-门罗学习规则和图像边缘识别。这有助于内存计算、图像处理和模拟感知系统的发展。

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分钟内获得全文去求助

来源期刊