Conductive double network hydrogel composed of sodium alginate, polyacrylamide, and graphene oxide

Abstract

Hydrogels are widely used in medical applications, such as tissue implants and scaffolds, due to their hydrophilic properties and tissue-like softness. Because hydrogels are crosslinked form of hydrophilic polymers, they do not dissolve in water. Various hydrophilic polymers have been used for hydrogel production including natural polymers (e.g., proteins (gelatin, collagen), polysaccharides (alginic acid, cellulose, hyaluronic acid, chitosan), nucleic acids (DNA, RNA)) and synthetic polymers (e.g., polyacrylamide, polyacrylic acid, polyethylene glycol, PVA, PMMA, and PHEMA). Compare to synthetic polymers, natural polymer-based hydrogels generally have limitations, including low mechanical strength. Recently, conductive hydrogels have garnered great attention to mediate electrical signals with biological system. Accordingly, various composites and manufacturing techniques have been developed to improve the mechanical properties and electrical properties of hydrogels. In order to introduce electrical conductivity to a hydrogel, extensive efforts have been made to form hydrogel composites with graphene or carbon nanotubes. In addition, various methods to improve mechanical properties of hydrogels have been studied; in particular, a double network system composed of two hydrophilic polymers is recently in the spotlight as a double network hydrogel can show a greatly improved increase in elasticity, toughness, and mechanical strength by efficiently dissipating external stress energy. In this study, the double network hydrogel was fabricated by composing sodium alginate, polyacrylamide, and graphene oxide. Then, the hydrogels were chemically reduced to convert graphene oxide to more conductive reduced graphene oxide in the hydrogels to improve the electrical conductivity of the composite hydrogels. In addition, the mechanical and electrical properties of the prepared hydrogel were characterized to examine their potentials for various biomedical fields, such as strain sensors and tissue scaffolds.