An energy-efficient NbO x /ZrO 2 bilayer memristor enabling low-voltage multilevel switching for neuromorphic computing

Journal of Materials Chemistry C 2026 Open access

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Authors: Muhammad Zulfiqar, Sobia Nisar, Rimsha Zulfiqar, Muneeb Ahmad, Muhammad Rabeel, Hammad Ghazanfar, Saikh Mohammad Wabaidur, Aamir Rasheed, Honggyun Kim, Ghulam Dastgeer, Deok-kee Kim
DOI: 10.1039/d5tc04061b
Cited by: 4
References: 49

Abstract

The rapid growth of artificial intelligence (AI) and edge computing has intensified an urgent demand for energy-efficient hardware capable of mimicking the parallel processing and adaptive learning functions of the human brain.

Fields of Study & Subjects

Advanced Memory and Neural Computing Ferroelectric and Negative Capacitance Devices Transition Metal Oxide Nanomaterials

Publication details

Journal / source
Journal of Materials Chemistry C
Publisher
Royal Society of Chemistry (RSC)
Volume
14
Issue
15
Pages
6458–6469
Publication date
1 January 2026
Language
EN