From materials to applications: a review of research on artificial olfactory memory

Abstract

Olfactory memory forms the basis for biological perception and environmental adaptation. Advancing artificial intelligence to replicate this biological perception as artificial olfactory memory is essential. The widespread use of various robotic systems, intelligent wearable devices, and artificial olfactory memories modeled after biological olfactory memory is anticipated. This review paper highlights current developments in the design and application of artificial olfactory memory, using examples from materials science, gas sensing, and storage systems. These innovations in gas sensing and neuromorphic technology represent the cutting edge of the field. They provide a robust scientific foundation for the study of intelligent bionic devices and the development of hardware architectures for artificial intelligence. Artificial olfaction will pave the way for future advancements in intelligent recognition by progressively enhancing the level of integration, understanding of mechanisms, and application techniques of machine learning algorithms.

Graphical abstract: From materials to applications: a review of research on artificial olfactory memory

Transparent peer review

To support increased transparency, we offer authors the option to publish the peer review history alongside their article.

View this article’s peer review history

Article information

Article type
Review Article
Submitted
28 Sep 2024
Accepted
28 Nov 2024
First published
29 Nov 2024

Mater. Horiz., 2025, Advance Article

From materials to applications: a review of research on artificial olfactory memory

L. Guo, H. Han, C. Du, X. Ji, M. Dai, S. Dosta, Y. Zhou and C. Zhang, Mater. Horiz., 2025, Advance Article , DOI: 10.1039/D4MH01348D

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