神经形态工程学
冯·诺依曼建筑
计算机科学
瓶颈
晶体管
计算机体系结构
人工智能
人工神经网络
纳米技术
材料科学
电气工程
电压
工程类
嵌入式系统
操作系统
作者
Heyi Huang,Chen Ge,Zhuohui Liu,Hai Zhong,Er‐Jia Guo,Meng He,Can Wang,Guozhen Yang,Kuijuan Jin
出处
期刊:Journal of Semiconductors
[IOP Publishing]
日期:2021-01-01
卷期号:42 (1): 013103-013103
被引量:31
标识
DOI:10.1088/1674-4926/42/1/013103
摘要
Abstract Von Neumann computers are currently failing to follow Moore’s law and are limited by the von Neumann bottleneck. To enhance computing performance, neuromorphic computing systems that can simulate the function of the human brain are being developed. Artificial synapses are essential electronic devices for neuromorphic architectures, which have the ability to perform signal processing and storage between neighboring artificial neurons. In recent years, electrolyte-gated transistors (EGTs) have been seen as promising devices in imitating synaptic dynamic plasticity and neuromorphic applications. Among the various electronic devices, EGT-based artificial synapses offer the benefits of good stability, ultra-high linearity and repeated cyclic symmetry, and can be constructed from a variety of materials. They also spatially separate “read” and “write” operations. In this article, we provide a review of the recent progress and major trends in the field of electrolyte-gated transistors for neuromorphic applications. We introduce the operation mechanisms of electric-double-layer and the structure of EGT-based artificial synapses. Then, we review different types of channels and electrolyte materials for EGT-based artificial synapses. Finally, we review the potential applications in biological functions.
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