Point-contact enabled reliable and low-voltage memristive switching and artificial synapse from highly transparent all-oxide-integration

Mimicking brain-like functionality for enabling higher-level artificial intelligence is one of the ultimate goals in neuromorphic computing, which could be achieved by two-terminal memristors. However, conventional memristors are suffering from severe shortcomings such as temporal (cycle-to-cycle) a...

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Bibliographic Details
Published in:Journal of alloys and compounds 2021-03, Vol.857, p.157593, Article 157593
Main Authors: Kumar, Mohit, Shin, Heecheol, Choi, Hyobin, Park, Ji-Yong, Kim, Sangwan, Seo, Hyungtak
Format: Article
Language:English
Subjects:
Artificial intelligence
Artificial synapse
Atomic force microscopy
Channels
Conducting atomic force microscopy
Conduction
Data processing
Electric contacts
Electric fields
Electric potential
Finite element method
Finite element simulation
Memristor
Memristors
Reproducibility
Switching
Ultralow
Voltage
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Summary:Mimicking brain-like functionality for enabling higher-level artificial intelligence is one of the ultimate goals in neuromorphic computing, which could be achieved by two-terminal memristors. However, conventional memristors are suffering from severe shortcomings such as temporal (cycle-to-cycle) and spatial (device-to-device) reproducibility along with high operative voltage, albeit all these are crucial for accurate and quick information processing. Here, we demonstrate point-contact enabled reproducible and reliable bipolar resistive switching from all-oxide-based highly transparent memristors with low operating voltage (
ISSN:0925-8388
1873-4669
DOI:10.1016/j.jallcom.2020.157593