记忆电阻器
钙钛矿(结构)
材料科学
可塑性
神经形态工程学
遗忘
变质塑性
电阻随机存取存储器
突触可塑性
计算机科学
纳米技术
光电子学
电压
电子工程
人工智能
人工神经网络
电气工程
化学工程
工程类
复合材料
受体
生物化学
化学
语言学
哲学
作者
Yucheng Wang,Dingyun Guo,Junyu Jiang,Hexin Wang,Yueyang Shang,Jiawei Zheng,Ruixi Huang,Wei Li,Shaoxi Wang
标识
DOI:10.1021/acsami.3c18053
摘要
Capitalizing on rapid carrier migration characteristics and outstanding photoelectric conversion performance, halide perovskite memristors demonstrate an exceptional resistive switching performance. However, they have consistently faced constraints due to material stability issues. This study systematically employs elemental modulation and dimension engineering to effectively control perovskite memristors with different dimensions and A-site elements. Compared to pure 3D and 2D perovskites, the quasi-2D perovskite memristor, specifically BA0.15MA0.85PbI3, is identified as the optimal choice through observations of resistive switching (HRS current < 10–5 A, ON/OFF ratio > 103, endurance cycles > 1000, and retention time > 104 s) and synaptic plasticity characteristics. Subsequently, a comprehensive investigation into various synaptic plasticity aspects, including paired-pulse facilitation (PPF), spike-variability-dependent plasticity (SVDP), spike-rate-dependent plasticity (SRDP), and spike-timing-dependent plasticity (STDP), is conducted. Practical applications, such as memory–forgetting–memory and recognition of the Modified National Institute of Standards and Technology (MNIST) database handwritten data set (accuracy rate reaching 94.8%), are explored and successfully realized. This article provides good theoretical guidance for synaptic-like simulation in perovskite memristors.
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