神经形态工程学
记忆电阻器
材料科学
电阻随机存取存储器
CMOS芯片
计算机体系结构
电压
电气工程
计算机科学
电子工程
人工智能
光电子学
工程类
人工神经网络
作者
Yu Chen,Gang Liu,Cheng Wang,Wenbin Zhang,Run‐Wei Li,Luxing Wang
出处
期刊:Materials horizons
[Royal Society of Chemistry]
日期:2014-06-02
卷期号:1 (5): 489-489
被引量:270
摘要
Polymer materials have been considered as promising candidates for the implementation of memristor devices due to their low-cost, easy solution processability, mechanical flexibility and ductibility, tunable electronic performance through innovative molecular design cum synthesis strategy and compatibility with complementary metal oxide semiconductor (CMOS) technology as well. The digital-type polymer memristor behaves as resistive random access memory with non-volatility, high density, more speed, low power consumption, large ON/OFF ratio, high endurance and long retention, and is recognized as an appealing candidate for the next generation "universal memory". As a logic component, the analog-type memristor, with the ability to emulate the fundamental synaptic functions of short-term/long-term plasticity (STP/LTP), spike-timing dependent-plasticity (STDP), spike-rate dependent plasticity (SRDP) and "learning-experience" behaviors, can be used to construct artificial neural networks for neuromorphic computation. In this review, we shall attempt to summarize the recent progress in research on the materials, switching characteristics and mechanism aspects of two terminal polymer memristors, for both information storage and neuromorphic applications that inspire great interest in the industrial and academic communities.
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