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An indirect way to achieve comprehensive performance improvement of resistive memory: when hafnium meets ITO in an electrode

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Abstract

Emerging resistive random access memory has attracted extensive research enthusiasm. In this study, an indirect way to improve resistive random access memory (RRAM) comprehensive performance through electrode material re-design without intensive switching layer engineering is presented by adopting a hafnium-indium-tin-oxide composite. Working parameters of the device can be effectively improved: not only are low operation power consumption and high working stability achieved, but the memory window is significantly enlarged, accompanied by an automatic self-current-compliance function. The correlation between hafnium incorporation and performance improvements and the corresponding current conduction mechanisms have been thoroughly investigated to clarify the resistive switching behavior and to explain the oxygen absorption buffer effect. The hafnium atom, with large atomic radius, is surrounded by soft electron clouds and has high chemical activity to attract oxygen ions. It facilitates the accumulation of more oxygen ions around the interface of the top electrode and the resistive switching layer, leading to lower current and Schottky conduction. This study presents an important strategy for designing and developing electrode materials to improve the characteristics of RRAM and offers an indirect method to modify device working behaviors, also unveiling a promising prospect for its potential future application in low-power information storage and calculation technology.

Graphical abstract: An indirect way to achieve comprehensive performance improvement of resistive memory: when hafnium meets ITO in an electrode

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Article information


Submitted
18 Oct 2019
Accepted
28 Dec 2019
First published
30 Dec 2019

Nanoscale, 2020, Advance Article
Article type
Paper

An indirect way to achieve comprehensive performance improvement of resistive memory: when hafnium meets ITO in an electrode

L. Li, K. Chang, C. Ye, X. Lin, R. Zhang, Z. Xu, Y. Zhou, W. Xiong and T. Kuo, Nanoscale, 2020, Advance Article , DOI: 10.1039/C9NR08943H

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