Multi-Bit Resistive Random-Access Memory Based on Two-Dimensional MoO3 Layers

TL;DR

This paper presents a 2D material-based RRAM device with improved performance and multi-bit storage for advanced memory applications.

Contribution

A novel Pd-MoO3-Ag RRAM device with multi-bit storage and improved retention using 2D materials is developed.

Findings

The Pd-MoO3-Ag RRAM device achieved low write voltage (~0.5 V) and high switching ratio (>106).

The Gr-MoO3-Ag heterostructure improved retention time by fivefold (>104 s).

2D materials enable high On/Off ratios and long-term data retention in RRAM devices.

Abstract

Two-dimensional (2D) material-based resistive random-access memory (RRAM) has emerged as a promising solution for neuromorphic computing and computing-in-memory architectures. Compared to conventional metal-oxide-based RRAM, the novel 2D material-based RRAM devices demonstrate lower power consumption, higher integration density, and reduced performance variability, benefiting from their atomic-scale thickness and ultra-flat surfaces. Remarkably, 2D layered metal oxides retain these advantages while preserving the merits of traditional metal oxides, including their low cost and high environmental stability. Through a multi-step dry transfer process, we fabricated a Pd-MoO3-Ag RRAM device featuring 2D α-MoO3 as the resistive switching layer, with Pd and Ag serving as inert and active electrodes, respectively. Resistive switching tests revealed an excellent operational stability, low write voltage (~0.5 V), high switching ratio (>106), and multi-bit storage capability (≥3 bits). Nevertheless, the device exhibited a limited retention time (~2000 s). To overcome this limitation, we developed a Gr-MoO3-Ag heterostructure by substituting the Pd electrode with graphene (Gr). This modification achieved a fivefold improvement in the retention time (>104 s). These findings demonstrate that by controlling the type and thickness of 2D materials and resistive switching layers, RRAM devices with both high On/Off ratios and long-term data retention may be developed.

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