共形矩阵
记忆电阻器
数码产品
可穿戴技术
可穿戴计算机
纳米技术
突触
神经形态工程学
可伸缩电子设备
材料科学
电气工程
计算机科学
工程类
神经科学
嵌入式系统
人工神经网络
人工智能
复合材料
生物
作者
Mihua Yang,Xiaoli Zhao,Qingxin Tang,Nan Cui,Zhongqiang Wang,Yanhong Tong,Yichun Liu
出处
期刊:Nanoscale
[Royal Society of Chemistry]
日期:2018-01-01
卷期号:10 (38): 18135-18144
被引量:110
摘要
Stretchable and conformable synapse memristors that can emulate the behaviour of the biological neural system and well adhere onto the curved surfaces simultaneously are desirable for the development of imperceptible wearable and implantable neuromorphic computing systems. Previous synapse memristors have been mainly limited to rigid substrates. Herein, a stretchable and conformable memristor with fundamental synaptic functions including potentiation/depression characteristics, long/short-term plasticity (STP and LTP), "learning-forgetting-relearning" behaviour, and spike-rate-dependent and spike-amplitude-dependent plasticity is demonstrated based on highly elastic Ag nanoparticle-doped thermoplastic polyurethanes (TPU : Ag NPs) and polydimethylsiloxane (PDMS). The memristor can be well operated even at 60% strain and can be well conformed onto the curved surfaces. The formed conductive filament (CF) obtained from the movement of Ag nanoparticle clusters under the locally enhanced electric field gives rise to resistance switching of our memristor. These results indicate a feasible strategy to realize stretchable and conformable synaptic devices for the development of new-generation artificial intelligence computers.
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