神经形态工程学
冯·诺依曼建筑
铁电性
记忆电阻器
计算机科学
瓶颈
灵活性(工程)
计算机体系结构
材料科学
纳米技术
光电子学
人工智能
人工神经网络
电气工程
嵌入式系统
工程类
电介质
统计
数学
操作系统
作者
Xuezhong Niu,Bobo Tian,Qiuxiang Zhu,Brahim Dkhil,Chun‐Gang Duan
出处
期刊:Applied physics reviews
[American Institute of Physics]
日期:2022-05-23
卷期号:9 (2)
被引量:48
摘要
The last few decades have witnessed the rapid development of electronic computers relying on von Neumann architecture. However, due to the spatial separation of the memory unit from the computing processor, continuous data movements between them result in intensive time and energy consumptions, which unfortunately hinder the further development of modern computers. Inspired by biological brain, the in situ computing of memristor architectures, which has long been considered to hold unprecedented potential to solve the von Neumann bottleneck, provides an alternative network paradigm for the next-generation electronics. Among the materials for designing memristors, i.e., nonvolatile memories with multistate tunable resistances, ferroelectric polymers have drawn much research interest due to intrinsic analog switching property and excellent flexibility. In this review, recent advances on artificial synapses based on solution-processed ferroelectric polymers are discussed. The relationship between materials' properties, structural design, switching mechanisms, and systematic applications is revealed. We first introduce the commonly used ferroelectric polymers. Afterward, device structures and the switching mechanisms underlying ferroelectric synapse are discussed. The current applications of organic ferroelectric synapses in advanced neuromorphic systems are also summarized. Eventually, the remaining challenges and some strategies to eliminate non-ideality of synaptic devices are analyzed.
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