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

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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

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Supplementary files

Article information


Submitted
23 Oct 2019
Accepted
14 Dec 2019
First published
20 Dec 2019

J. Mater. Chem. C, 2020, Advance Article
Article type
Communication

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, Advance Article , DOI: 10.1039/C9TC05797H

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