Stability and Repeatability of a Karst-like Hierarchical Porous Silicon Oxide-Based Memristor

作者：Qin Gao, Anping Huang, Qi Hu, Xinjiang Zhang, Yu Chi, Runmiao Li, Yuhang Ji, Xueliang Chen, Rumeng Zhao, Meng Wang, Hongliang Shi, Mei Wang, Yimin Cui, Zhisong Xiao, Paul K. Chu · 发表于：ACS Applied Materials & Interfaces · 年份：2019 · DOI：10.1021/acsami.9b06855 · 被引用次数：32 · 研究领域：Advanced Memory and Neural Computing、Transition Metal Oxide Nanomaterials、Neuroscience and Neural Engineering

A memristor architecture based on porous oxide materials has the potential to be used in artificial synaptic devices. Herein, we present a memristor system employing a karst-like hierarchically porous (KLHP) silicon oxide structure with good stability and repeatability. The KLHP structure prepared by an electrochemical process and thermal oxidation exhibits high ON-OFF ratios up to 10 5 during the endurance test, and the data can be maintained for 10 5 s at a small read voltage 0.1 V. The mechanism of lithium ion migration in the porous silicon oxide structure has been discussed by a simulated model. The porous silicon oxide-based memristor is very promising because of the enhanced performance as well as easily accessed neuromorphic computing.