Issue 43, 2021, Issue in Progress

3D hollow-structured hydrogels with editable macrostructure, function, and mechanical properties induced by segmented adjustments

Abstract

Currently, it is challenging to prepare uniform hollow-structured hydrogels with tailorable comprehensive properties. Herein, making full use of the different gelation routes of polyvinyl alcohol (PVA), we propose a distinctive two-stage method for preparing hollow-structured hydrogels, which is to arrange the microstructure of the hydrogel through segmented adjustment. The mechanical properties, macrostructure, and functions of the obtained hollow hydrogel can be easily designed and edited. Specifically, the mechanical properties of the hollow hydrogel can be improved from “soft” to “hard” by changing the preparation conditions. In addition, hollow hydrogels with diverse macrostructures can also be developed through different templates, such as tubes, gloves, and rings. More importantly, the hollow hydrogels can be endowed with conductive, anti-drying, anti-freezing, and photothermal-converting functions due to the great system compatibility of the gel precursor. Benefiting from the advantages of the hollow hydrogel, the conductive gel ring-based bioelectrodes and sensors were developed. Interestingly, the adaptive gel ring-based electronics can stably record the electrophysiological and strain signals of the human body without the help of adhesive tape. This study opens more opportunities for development and applications of other hydrogel-based hollow materials.

Graphical abstract: 3D hollow-structured hydrogels with editable macrostructure, function, and mechanical properties induced by segmented adjustments

Supplementary files

Article information

Article type
Paper
Submitted
11 Jul 2021
Accepted
26 Jul 2021
First published
05 Aug 2021
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2021,11, 26876-26882

3D hollow-structured hydrogels with editable macrostructure, function, and mechanical properties induced by segmented adjustments

Q. Wang, J. Yu, X. Lu, S. Cao, L. Chen, X. Pan, Y. Ni and X. Ma, RSC Adv., 2021, 11, 26876 DOI: 10.1039/D1RA05338H

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