Synaptic plasticity features and neuromorphic system simulation in AlN-based memristor devices

Journal of Alloys and Compounds(2022)

引用 8|浏览0
暂无评分
摘要
In this paper, we show various memory characteristics of the Ag/AlN/TiN devices for neuromorphic systems. We verified the thickness and the components of the device stack by transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy (EDS). We investigated the long-term memory (LTM) characteristics, and short-term memory (STM) characteristics can be determined by compliance current (CC). It shows LTM characteristics when CC is high and STM characteristics when CC is low. I-V curves for each characteristic were investigated, and potentiation and depression for LTM characteristics. The switching and conduction mechanisms of Ni/Ag/AlN/TiN devices are studied using the schematic drawing of the conducting filament and the energy band diagram, including the work function, electron affinity, and bandgap energy of each layer. The linearity of potentiation and depression was compared for an identical pulse and an incremental pulse. Finally, we investigated Modified National Institute of Standards and Technology (MNIST) pattern accuracy depending on the linearity of potentiation and depression.
更多
查看译文
关键词
Neuromorphic system,Memristor,AlN,MNIST
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要