记忆电阻器
计算机科学
电子工程
GSM演进的增强数据速率
可靠性(半导体)
功率(物理)
材料科学
电气工程
工程类
人工智能
物理
量子力学
作者
Yinxing Zhang,Xiaotong Jia,Jikang Xu,Zhenqiang Guo,Weifeng Zhang,Yongrui Wang,Pengfei Li,Jiameng Sun,Zhen Zhao,Biao Yang,Xiaobing Yan
出处
期刊:Nano Today
[Elsevier BV]
日期:2024-01-11
卷期号:55: 102144-102144
被引量:3
标识
DOI:10.1016/j.nantod.2023.102144
摘要
Near-sensor analog computing systems have received a lot of attention as they can effectively reduce the large amount of redundant data transferred between sensor terminals and computing units, thereby shortening the data processing time and reducing power consumption. However, ensuring the reliability and stability of memristor devices used in the hardware circuits of near-sensor analog computing systems remains a considerable challenge. In this paper, we describe a robust ferroelectric memristor based on Pd/BaTiO3:Nd2O3/La0.67Sr0.33MnO3 grown on a silicon structure with SrTiO3 as the buffer layer. Through optimized growth temperature, the device exhibits a low coercive field voltage (−1–2 V), robust endurance characteristics (>1010 cycles), and a power consumption as low as 0.45 fJ per synaptic event. Also in this study, a near-sensor analog computing system based on an array of pressure sensors and ferroelectric memristors was constructed. It is shown that this system can accurately calculate multiple raw analog pressure signals in real time without the need for peripheral circuitry and that the system can classify object shapes and perform edge detection with a maximum deviation of only about 58.6 nA. This study highlights the great potential of ferroelectric memristors for use as fundamental components of near-sensor analog computing systems.
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