Issue 3, 2020

Development of high-strength, tough, and self-healing carboxymethyl guar gum-based hydrogels for human motion detection

Abstract

Self-healing hydrogels have attracted intense attention because of their potential applications in ionic strain sensors. However, most self-healing hydrogel sensors exhibit poor mechanical properties due to the inherent compromise between the dynamic interactions for healing and steady interactions for mechanical strength. Here, strong, tough and self-healing ionic conductive hydrogel sensors were prepared based on synergistic multiple noncovalent bonds among carboxymethyl guar gum (CMGG), poly(acrylic acid) (PAA), and ferric metal ions (Fe3+) in a covalent polymer network. The incorporated CMGG, mediated by metal–ligand interactions, acts as dynamic cross-linkers, endowing the ionic hydrogels with superior mechanical properties. In addition, the reversible and dynamic nature of the multiple metal–ligand interactions accounts for the good self-recovery capabilities, remarkable mechanical properties, and high self-healing efficiencies. Furthermore, the ionic conductive hydrogels displayed good strain sensitivity with repeatable, reliable, and precise changes of resistance signals. Based on these merits, the hydrogel could be assembled as a flexible strain sensor to monitor and distinguish various human motions. We expect that this facile method of incorporating the biocompatible and biodegradable CMGG for the design of strong, tough, self-healing and ionic conductive hydrogels may have promising potential for flexible strain sensors for human motion monitoring.

Graphical abstract: Development of high-strength, tough, and self-healing carboxymethyl guar gum-based hydrogels for human motion detection

Supplementary files

Article information

Article type
Communication
Submitted
23 Oct 2019
Accepted
14 Dec 2019
First published
20 Dec 2019

J. Mater. Chem. C, 2020,8, 900-908

Development of high-strength, tough, and self-healing carboxymethyl guar gum-based hydrogels for human motion detection

W. Chen, Y. Bu, D. Li, Y. Liu, G. Chen, X. Wan and N. Li, J. Mater. Chem. C, 2020, 8, 900 DOI: 10.1039/C9TC05797H

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