Advances in Ga2O3-based memristor devices, modeling, properties, and applications for low power neuromorphic computing

Abstract

About a decade ago, gallium oxide (Ga2O3) was found to be a very attractive ultrawide-bandgap (4.6–4.9 eV) semiconductor for next-generation low-power devices. Ga2O3 materials have attracted a lot of scientific and technical interest because of their outstanding properties and numerous application opportunities in the field of semiconductor based memristor technology. This review is focused on Ga2O3 thin-film memristors for smart technologies. The capacitance behavior of memristors is very important for adapting nonlinear memristor responses. Also, this comprehensive review explores in depth the ideas, device construction, and manufacturing procedures for Ga2O3-based memristor devices. To improve the device's behavior and performance improvement, a detailed analysis of many modeling and simulation techniques is given. Also, advanced characterization techniques, such as electrical, structural, and thermal evaluations, for studying artificial optoelectronic synaptic characteristics, which are important for use in computational neuroscience, are discussed in detail. The synaptic activities revealed that learning and memory processes were aided by potentiation and depression similar to those found in biological synapses. The most notable accomplishment is the realization of quaternary memory storage in a single device. This idea is supported by empirical evidence and simulations, which demonstrate the possibility of storing and maintaining multiple memory states. This study establishes oxide semiconductor memristors as a doorway to quaternary memory storage and improved synaptic functioning, paving the way for optoelectronic synaptic devices with greater memory capacity.

Graphical abstract: Advances in Ga2O3-based memristor devices, modeling, properties, and applications for low power neuromorphic computing

Article information

Article type
Review Article
Submitted
19 Du 2024
Accepted
10 Meu 2025
First published
15 Ebr 2025

Nanoscale, 2025, Advance Article

Advances in Ga2O3-based memristor devices, modeling, properties, and applications for low power neuromorphic computing

R. Khan, N. U. Rehman, R. Thangappan, A. Saritha and S. Sangaraju, Nanoscale, 2025, Advance Article , DOI: 10.1039/D4NR04865B

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