神经形态工程学
记忆电阻器
电阻随机存取存储器
材料科学
非易失性存储器
纳米技术
氮化硼
计算机科学
光电子学
电子工程
电压
电气工程
人工神经网络
工程类
人工智能
作者
Gong Wang,Xiaobing Yan,Jingsheng Chen,Deliang Ren
标识
DOI:10.1002/pssr.201900539
摘要
Resistance random access memory (RRAM) based on a solid‐electrolyte insulator is an indispensable nanoscale device with promising potential in nonvolatile memory, multilevel switching, and neuromorphic applications. However, the random nature of the nucleation and growth of the conductive filaments (CFs) leads to instability of the switching parameter, which is the main obstacle to improving the performance of the RRAM. Herein, a novel approach to resolve this challenge by inserting boron nitride nanosheets (BNNSs) into the ZnO‐based device structure is reported. The hybrid structure with double switching layer device can combine memristive functions—nonvolatile bipolar memory, multilevel switching, and neuromorphic functionalities—simulating biological sensory systems in response to external stimuli. The overall device performance of the ZnO/BNNSs‐based memristor opens up a new path to improve the stability of oxide‐based RRAM, enabling hardware implementation of the nervous system.
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