Issue 42, 2025

Multifunctional ZnO-based optical memristors for synapse–neuron integration and neuromorphic vision systems

Abstract

This work presents a comprehensive analysis of ZnO-based memristive devices integrated with ITO electrodes, focusing on optical and neuromorphic properties. The precise layered structure and chemical composition of the ITO/ZnO/ITO stack were identified by cross-sectional Transmission Electron Microscopy (TEM) and energy-dispersive X-ray (EDX) analyses. Synaptic properties were investigated using light stimulation at 405 nm. The device exhibited distinct functionalities depending on the light intensity. At a high light intensity, the device exhibited short-term memory (STM) behavior and paired-pulse facilitation (PPF), which are critical for mimicking biological synaptic plasticity. This study also reproduced key features such as threshold, non-adaptation, relaxation, and nociceptive sensitization with respect to nociceptors. These results demonstrate the potential of ZnO-based devices as visual nociceptors (VNs) that augment neuromorphic vision with a danger-signaling pathway, enabling self-protection and adaptability to harmful optical stimuli. Additionally, reservoir computing (RC) for MNIST image classification reached an accuracy of 97.35%, showing that the device is capable of handling real-time tasks like image recognition and processing. At a low light intensity, the device exhibited computational capability at the neuron level through implementation of the Restricted Boltzmann Machine (RBM) model. By integrating neuromorphic, nociceptive and computational features, this work paves the way for the development of biological system-inspired multifunctional devices.

Graphical abstract: Multifunctional ZnO-based optical memristors for synapse–neuron integration and neuromorphic vision systems

Supplementary files

Article information

Article type
Paper
Submitted
28 Jun 2025
Accepted
14 Sep 2025
First published
16 Sep 2025

Nanoscale, 2025,17, 24566-24577

Multifunctional ZnO-based optical memristors for synapse–neuron integration and neuromorphic vision systems

H. Jang, S. Kim, S. Ju, S. Park, S. Kim and M. Kim, Nanoscale, 2025, 17, 24566 DOI: 10.1039/D5NR02736E

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements