Issue 10, 2024

Hyper strength, high sensitivity integrated wearable signal sensor based on non-covalent interaction of an ionic liquid and bacterial cellulose for human behavior monitoring

Abstract

Ion-sensing hydrogels exhibit electrical conductivity, softness, and mechanical and sensory properties akin to human tissue, rendering them an ideal material for mimicking human skin. In the realm of fabricating sensors for detecting human physiological activities, they present an ideal alternative to traditional rigid metal conductors. Nevertheless, achieving ionic hydrogels with outstanding tensile properties, toughness, ionic conductivity, and transport stability poses a significant challenge. This paper describes a simple method of forming a basic network by free radical polymerization of acrylamide, and then bacterial cellulose (BC) and 1-ethyl-3-methylimidazolium chloride ([EMIM]Cl) were introduced into the basic network. The polyhydrogen bonds and electrostatic interactions in the system gave the hydrogel notable tensile properties (3271 ± 37%), toughness (7.39 ± 0.13 MJ m−3), and high ultimate tensile stress (385.1 ± 7.2 kPa). In addition, the combination of BC and [EMIM]Cl collaboratively enhanced the mechanical properties and electrical conductivity. Ion sensing hydrogels have a wide operating strain range (≈1000%) and high sensitivity (gage factor (GF) = 11.85), and are therefore considered promising candidates for next-generation gel-based strain sensor platforms.

Graphical abstract: Hyper strength, high sensitivity integrated wearable signal sensor based on non-covalent interaction of an ionic liquid and bacterial cellulose for human behavior monitoring

Supplementary files

Article information

Article type
Communication
Submitted
14 Oct 2023
Accepted
15 Jan 2024
First published
27 Jan 2024

Mater. Horiz., 2024,11, 2420-2427

Hyper strength, high sensitivity integrated wearable signal sensor based on non-covalent interaction of an ionic liquid and bacterial cellulose for human behavior monitoring

X. Rong, Q. Ding, L. Chen, S. Yang, J. Lou, Z. Liu, X. Li, Y. Jiang, X. Wang and W. Han, Mater. Horiz., 2024, 11, 2420 DOI: 10.1039/D3MH01696J

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