Issue 18, 2022

Highly stretchable, self-healing and conductive silk fibroin-based double network gels via a sonication-induced and self-emulsifying green procedure

Abstract

Regenerated silk fibroin (RSF)-based hydrogels are promising biomedical materials due to their biocompatibility and biodegradability. However, the weak mechanical properties and lack of functionality limit their practical applications. Here, we developed a tough and conductive RSF-based double network (DN) gel, consisting of a sonication-induced β-sheet physically crosslinked RSF/S gel as the first network and a hydrophobically associated polyacrylamide/stearyl methacrylate (PAAm/C18) gel as the second network. In particular, the cross-linking points of the second network were micelles formed by emulsifying the hydrophobic monomer (C18M) with a natural SF- capryl glucoside co-surfactant. The reversible dynamic bonds in the DN provided good self-healing ability and an effective dissipative energy mechanism for the DN hydrogel, while the addition of calcium ions improved the self-healing ability and electrical conductivity of the hydrogel. Under optimal conditions, the RSF/S-PAAm/C18 DN gels exhibited large extensibility (1400%), high tensile strength (0.3 MPa), satisfactory self-healing capability (90%) and electrical conductivity (0.12 S·m−1). The full physically interacted DN hydrogels are expected to be applied in various fields such as tissue engineering, biosensors and artificial electronic skin.

Graphical abstract: Highly stretchable, self-healing and conductive silk fibroin-based double network gels via a sonication-induced and self-emulsifying green procedure

Supplementary files

Article information

Article type
Paper
Submitted
13 Feb 2022
Accepted
07 Apr 2022
First published
13 Apr 2022
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2022,12, 11574-11582

Highly stretchable, self-healing and conductive silk fibroin-based double network gels via a sonication-induced and self-emulsifying green procedure

T. Fang, J. Zhu, S. Xu, L. Jia and Y. Ma, RSC Adv., 2022, 12, 11574 DOI: 10.1039/D2RA00954D

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