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氧化锌/氧化钽双介质层忆阻器的突触特性分析
引用本文:胡敏锐,周海芳,赖云锋. 氧化锌/氧化钽双介质层忆阻器的突触特性分析[J]. 福州大学学报(自然科学版), 2020, 48(5): 596-601
作者姓名:胡敏锐  周海芳  赖云锋
作者单位:福州大学物理与信息工程学院 福建 福州 350108,福州大学物理与信息工程学院 福建 福州 350108,福州大学物理与信息工程学院 福建 福州 350108
基金项目:福建省自然科学基金资助项目(2019J01218)
摘    要:人工突触的开发是模拟人脑功能的关键。忆阻器由于具备独特的电阻记忆行为,在人工突触研究领域得到广泛的关注。氧化钽和氧化锌均是优良的忆阻器材料,鉴于有关ZnO/TaOx双介质忆阻器突触特性的研究较少,本文将氧化锌介质层引入Ti/TaOx/ITO忆阻器中拟改善其突触性能。研究发现,器件Ti/ZnO/TaOx/ITO在功耗和电导调制线性度方面皆有改善,并有着电阻渐变的行为,利于器件突触功能的实现及应用。为此对Ti/ZnO/TaOx/ITO双介质层器件进行了电压脉冲训练,并成功模拟了学习饱和、经验学习以及短时程记忆向长时程记忆转变等生物突触行为。

关 键 词:忆阻器  低功耗  突触行为  人工突触  氧化钽
收稿时间:2019-11-25
修稿时间:2020-01-08

Study on synaptic properties of ZnO/TaOx double layer memristor
HU Minrui,ZHOU Haifang,LAI Yunfeng. Study on synaptic properties of ZnO/TaOx double layer memristor[J]. Journal of Fuzhou University(Natural Science Edition), 2020, 48(5): 596-601
Authors:HU Minrui  ZHOU Haifang  LAI Yunfeng
Affiliation:College of Physics and Information Engineering,Fuzhou University,Fuzhou,College of Physics and Information Engineering,Fuzhou University,Fuzhou,College of Physics and Information Engineering,Fuzhou University,Fuzhou
Abstract:The development of artificial synapses is the key to simulating human brain function. Memristors have attracted extensive attention in the field of artificial synapse because of their unique resistance memory behavior. TaOx and ZnO are both excellent memristor materials. In this work, ZnO layer was introduced into the Ti/TaOx/ITO memristors to improve their synaptic properties for the few studies on the synaptic characteristics of ZnO/TaOx dual-media memristor. It is found that the Ti/ZnO/TaOx/ITO device has improved the properties of power consumption and conductivity modulation linearity, and accompanied by the behavior of gradual resistance switching. It is very useful for the realization and application of synaptic function of the device. By applying voltage pulse to train Ti/ZnO/TaOx/ITO dual-layer devices, we successfully simulated such biological synaptic behaviors as learning saturation, experiential learning and the transition from short time memory to long time memory memory.
Keywords:memristor   low power consumption   synaptic behaviors   artificial synapses   TaOx
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