Amorphous LiNbO 3 memristors for nonvolatile memory and neuromorphic computing with metaplasticity-enabled learning

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Authors: Mengting Dong, Ruirui Hu, Yi-Xiang Wang, Junnan Han, Zhangting Wu, Dongke Li, De Yang, Xiaodong Pi
Cited by: 1
References: 41

Abstract

Abstract This work presents a comprehensive study on amorphous LiNbO 3 (LNO)-based memristors and their application in nonvolatile memory and neuromorphic computing. We demonstrate the fabrication of Ti/LNO/Au memristors exhibiting robust bipolar analog switching, excellent cycle-to-cycle uniformity, and long-term retention. These devices retain full switching functionality up to 400 °C, emphasizing the intrinsic thermal resilience of the amorphous LNO matrix and the stability of oxygen-vacancy-mediated filament dynamics. The devices further display a range of synaptic behaviors such as long-term potentiation, long-term depression, paired-pulse facilitation, and spike-timing-dependent plasticity, which are essential for biologically plausible learning rules in neuromorphic systems. The history-dependent conductance evolution of the memristors enables metaplasticity, which adaptively regulates learning rates and mitigates catastrophic forgetting in sequential MNIST tasks while maintaining high accuracy even at 200 °C. These findings position amorphous LNO as a promising material for next-generation memristive hardware, uniquely combining thermal endurance, analog plasticity, and metaplastic learning regulation.

Fields of Study & Subjects

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

Publication details

Journal / source
Neuromorphic Computing and Engineering
Publisher
IOP Publishing
Volume
6
Issue
2
Pages
024020–024020
Publication date
18 May 2026
Language
EN