神经形态工程学
记忆电阻器
计算机科学
钙钛矿(结构)
能源消耗
计算机体系结构
记忆
过程(计算)
人工智能
材料科学
纳米技术
电子工程
人工神经网络
工程类
电气工程
操作系统
数学教育
化学工程
数学
作者
Hea‐Lim Park,Tae‐Woo Lee
标识
DOI:10.1016/j.orgel.2021.106301
摘要
Organic and perovskite memristors have superior characteristics both in material and structural perspectives, and therefore have been evaluated for possible integration as bio-realistic components of artificial intelligent hardware systems. This application will require the brain-inspired integrated systems that can process and memorize large amounts of complex information; requirements include highly uniform and reliable memristors that can be operated at low energy and integrated at high density. Here, we review the progress in development of organic and perovskite memristors to obtain various synaptic behaviors, with focus on material and underlying mechanism aspects. Then we address various approaches to meet the needs for constructing applications of neuromorphic computing, including low energy consumption, high uniformity and reliability of the memristors, and high-density integration. Lastly, we suggest future research directions toward realizing neuromorphic computing.
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