Issue 17, 2024

Affective computing for human–machine interaction via a bionic organic memristor exhibiting selective in situ activation

Abstract

Affective computing, representing the forefront of human–machine interaction, is confronted with the pressing challenges of the execution speed and power consumption brought by the transmission of massive data. Herein, we introduce a bionic organic memristor inspired by the ligand-gated ion channels (LGICs) to facilitate near-sensor affective computing based on electroencephalography (EEG). It is constructed from a coordination polymer comprising Co ions and benzothiadiazole (Co–BTA), featuring multiple switching sites for redox reactions. Through advanced characterizations and theoretical calculations, we demonstrate that when subjected to a bias voltage, only the site where Co ions bind with N atoms from four BTA molecules becomes activated, while others remain inert. This remarkable phenomenon resembles the selective in situ activation of LGICs on the postsynaptic membrane for neural signal regulation. Consequently, the bionic organic memristor network exhibits outstanding reliability (200 000 cycles), exceptional integration level (210 pixels), ultra-low energy consumption (4.05 pJ), and fast switching speed (94 ns). Moreover, the built near-sensor system based on it achieves emotion recognition with an accuracy exceeding 95%. This research substantively adds to the ambition of realizing empathetic interaction and presents an appealing bionic approach for the development of novel electronic devices.

Graphical abstract: Affective computing for human–machine interaction via a bionic organic memristor exhibiting selective in situ activation

Associated articles

Supplementary files

Article information

Article type
Communication
Submitted
18 נוב 2023
Accepted
24 יונ 2024
First published
25 יונ 2024

Mater. Horiz., 2024,11, 4075-4085

Affective computing for human–machine interaction via a bionic organic memristor exhibiting selective in situ activation

B. Guo, X. Zhong, Z. Yu, Z. He, S. Liu, Z. Wu, S. Liu, Y. Guo, W. Chen, H. Duan, J. Zeng, P. Gao, B. Zhang, Q. Chen, H. He, Y. Chen and G. Liu, Mater. Horiz., 2024, 11, 4075 DOI: 10.1039/D3MH01950K

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