Stability and Repeatability of a Karst-like Hierarchical Porous Silicon Oxide-Based Memristor
Source abstract
Abstract
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 105 during the endurance test, and the data can be maintained for 105 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.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Transition Metal Oxide Nanomaterials · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physics, Beihang University, Beijing 100191, China
Department of Physics and Department of Materials Science and Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon 999077, Hong Kong, China
Funding
City University of Hong Kong · National Natural Science Foundation of China · Beijing Municipal Science and Technology Commission
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