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Electric Field-Induced Area Scalability toward the Multilevel Resistive Switching
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Publication Year
2021-09-01
Journal
Advanced Materials Interfaces
Publisher
John Wiley and Sons Inc
Citation
Advanced Materials Interfaces, Vol.8 No.17
Keyword
area scalabilityconductive atomic force microscopymultilevel memory storageRRAM
Mesh Keyword
Charge trapping/detrappingConductive atomic force microscopyElectric field inducedKelvin probe force microscopyMultilevel resistive switchingNeuromorphic computingNonvolatile memory devicesResistive random access memory (rram)
All Science Classification Codes (ASJC)
Mechanics of MaterialsMechanical Engineering
Abstract
Nonvolatile memory devices based on resistive switching with fast switching speed and high density have driven extensive research that is potentially ideal for data-centric applications such as neuromorphic computing. However, due to uncontrolled filament formation, resistive random access memories (RRAM) still suffer from instability and reproducibility. In this study, NiO layer is added to the WO3-based RRAM layer to confine the conducting path for multilevel resistive switching. The current-voltage characteristics show the multilevel resistive switching, which is further confirmed by conductive atomic force microscopy measurements at nanoscale. At low voltages, few localized conducting channels are formed (in small area) within the oxide film while at the higher voltages they are distributed throughout the film and the active surface area increases from 4.5 to 75%. Kelvin probe force microscopy was employed to confirm nanoscale variations in surface potential, which are responsible for spatial current variation. Furthermore, it is found that the charge trapping/detrapping is the main governing mechanism and the conducting paths are formed gradually with increasing applied bias. We propose a strategy to achieve stable and reproducible electric field-induced multilevel memory storage which will be utilized for the development of ultrahigh density multilevel nonvolatile storage and neuromorphic computing.
ISSN
2196-7350
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/32201
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85112681364&origin=inward
DOI
https://doi.org/10.1002/admi.202100664
Type
Article
Funding
This work was supported by Brain Pool Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT, Republic of Korea (Nos. NRF\u20102019H1D3A1A01102524, NRF\u20102019M3F3A1A03079739, and NRF\u20102019R1A2C2003804). This work was also supported by Ajou University.
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Park, Ji-Yong 박지용
Department of Physics
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