Reset-First and Multibit-Level Resistive-Switching Behavior of Lanthanum Nickel Oxide (LaNiO<sub>3−x</sub>) Thin Films

The resistive random-access memory (RRAM) with multi-level storage capability has been considered one of the most promising emerging devices to mimic synaptic behavior and accelerate analog computations. In this study, we investigated the reset-first bipolar resistive switching (RS) and multi-level...

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Bibliographic Details
Main Authors: Daewoo Kim, Jeongwoo Lee, Jaeyeon Kim, Hyunchul Sohn
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Materials
Subjects:
Online Access:https://www.mdpi.com/1996-1944/16/14/4992
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Summary:The resistive random-access memory (RRAM) with multi-level storage capability has been considered one of the most promising emerging devices to mimic synaptic behavior and accelerate analog computations. In this study, we investigated the reset-first bipolar resistive switching (RS) and multi-level characteristics of a LaNiO<sub>3−x</sub> thin film deposited using a reactive magnetron co-sputtering method. Polycrystalline phases of LaNiO<sub>3</sub> (LNO), without La<sub>2</sub>O<sub>3</sub> and NiO phases, were observed at similar fractions of Ni and La at a constant partial pressure of oxygen. The relative chemical proportions of Ni<sup>3+</sup> and Ni<sup>2+</sup> ions in LaNiO<sub>3−x</sub> indicated that it was an oxygen-deficient LaNiO<sub>3−x</sub> thin film, exhibiting RS behavior, compared to LNO without Ni<sup>2+</sup> ions. The TiN/LaNiO<sub>3−x</sub>/Pt devices exhibited gradual resistance changes under various DC/AC voltage sweeps and consecutive pulse modes. The nonlinearity values of the conductance, measured via constant-pulse programming, were 0.15 for potentiation and 0.35 for depression, indicating the potential of the as-fabricated devices as analog computing devices. The LaNiO<sub>3−x</sub>-based device could reach multi-level states without an electroforming step and is a promising candidate for state-of-the-art RS memory and synaptic devices for neuromorphic computing.
ISSN:1996-1944