神经形态工程学
记忆电阻器
横杆开关
计算机科学
电阻随机存取存储器
材料科学
光电子学
电阻式触摸屏
电子工程
电气工程
人工神经网络
纳米技术
电压
工程类
人工智能
电信
计算机视觉
作者
Jiewen Chen,Qian Xu,Yang Li,Jie Cao,Xusheng Liu,Jie Qiu,Yan Chen,Meng-Yang Liu,Jie Yu,Xumeng Zhang,Zhi-Wei Zheng,Ming Wang
标识
DOI:10.1109/led.2024.3387455
摘要
In this letter, we report a fully printed metal-oxide memristor crossbar array based on the Ag/ZnO/Ag structure, and extend its neuromorphic computing application as artificial synapses. The wurtzite-type ZnO is printed as an active layer, which is sandwiched between two printed Ag electrodes, forming a memristor unit. The printed memristor exhibits volatile resistive switching behaviors under a low compliance current of 1 μA, and can emulate the short-term synaptic plasticity and biological “learning-relearning” processes. More importantly, the image learning and forgetting function is successfully demonstrated in a 3 × 3 printable memristor array. These results show that the printing technique offers a promising path towards large-scale and low-cost neuromorphic computing electronics.
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