利用界面工程来调控铁电隧道忆阻器的生物突触行为

作     者：赵建辉 于天奇 邵一铎 郭瑞 林伟南 刘公杰 周振宇 裴逸菲 王静娟 孙凯旋 闫小兵 陈景升 Jianhui Zhao;Tianqi Yu;Yiduo Shao;Rui Guo;Weinan Lin;Gongjie Liu;Zhenyu Zhou;YiFei Pei;Jingjuan Wang;Kaixuan Sun;Xiaobing Yan;Jingsheng Chen

作者机构：Key Laboratory of Brain-like Neuromorphic Devices and Systems of Hebei ProvinceCollege of Electronic and Information EngineeringInstitute of Life Science and Green DevelopmentHebei UniversityBaoding 071002China Department of Materials Science and EngineeringNational University of SingaporeSingapore 117575Singapore 

出 版 物：《Science China Materials》 (中国科学（材料科学（英文版）)

年 卷 期：2023年第66卷第4期

页      面：1559-1568页

核心收录：

学科分类：080903[工学-微电子学与固体电子学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported by the National Key R&D Plan“Nano Frontier”Key Special Project(2021YFA1200502) the National Natural Science Foundation of China(62004056,61874158,and 62104058) the Cultivation Projects of National Major R&D Project(92164109) the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(XDB44000000-7) Hebei Basic Research Special Key Project(F2021201045) the Support Program for the Top Young Talents of Hebei Province(70280011807) the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(SLRC2019018) the Interdisciplinary Research Program of Natural Science of Hebei University(DXK202101) the Institute of Life Sciences and Green Development(521100311) the Natural Science Foundation of Hebei Province(F2022201054 and F2021201022) the Outstanding Young Scientific Research and Innovation Team of Hebei University(605020521001) the Special Support Funds for National High Level Talents(041500120001) the Advanced Talents Incubation Program of the Hebei University(521000981426,521100221071,and 521000981363) the Science and Technology Project of Hebei Education Department(QN2020178 and QN2021026) Baoding Science and Technology Plan Project(2172P011) 

主　　题：数字图像识别 忆阻器 界面工程 控制界面 电阻开关 人工神经网络系统 长时程抑制 长时程增强 

摘      要：界面工程一直是调节铁电隧道结忆阻器(FTM)行为的重要途径,且直接影响其生物突触特性.为了研究界面对人工突触性能的影响,本工作中,我们研究了具有Pt/BaTiO_(3)/La_(0.67)Sr_(0.33)MnO_(3)结构的忆阻器.其中可以通过控制SrTiO_(3)(STO)衬底的终止层和BaTiO_(3)(BTO)薄膜层状生长模式来控制忆阻器器件的界面.由于BTO薄膜相反的铁电极化方向以及与之对应的不同的能带结构,具有不同界面的FTM呈现出相反的电阻开关行为.更重要的是,FTM的突触学习特性也可以通过控制界面来调整.具有不同接口终端的FTM可以调节长时程增强、长时程抑制、尖峰时间依赖性可塑性和配对脉冲促进的不同特性.基于这两种接口工程FTM的突触行为,可以构建人工神经网络系统来完成手写数字图像识别过程,两者的准确率都接近90%.我们的结果为通过纳米级界面工程调整忆阻器的功能提供了有用的参考.