Robust and conductive hydrogel based on mussel adhesive chemistry for remote monitoring of body signals

Friction(2020)

引用 8|浏览12
暂无评分
摘要
There is a high demand for hydrogels with multifunctional performance (a combination of adhesive, mechanical, and electrical properties) in biological, tissue engineering, robotics, and smart device applications. However, a majority of existing hydrogels are relatively rigid and brittle, with limited stretchability; this hinders their application in the emerging field of flexible devices. In this study, cheap and abundant potato residues were used with polyacrylamide (PAM) to fabricate a multifunctional hydrogel, and chitosan was used for the design of a three-dimentional (3D) network-structured hydrogel. The as-prepared hydrogels exhibited excellent stretchability, with an extension exceeding 900% and a recovery degree of over 99%. Due to the combination of physical and chemical cross-linking properties and the introduction of dopamine, the designed hydrogel exhibits a remarkable self-healing ability (80% mechanical recovery in 2 h), high tensile strength (0.75 MPa), and ultra-stretchability (900%). The resultant products offer superior properties compared to those of previously reported tough and self-healing hydrogels for wound adhesion. Chitosan and potato residues were used as scaffold materials for the hydrogels with excellent mechanical properties. In addition, in vitro experiments show that these hydrogels feature excellent antibacterial properties, effectively hindering the reproduction of bacteria. Moreover, the ternary hydrogel can act as a strain sensor with high sensitivity and a gauge factor of 1.6. The proposed strategy is expected to serve as a reference for the development of green and recyclable conductive polymers to fabricate hydrogels. The proposed hydrogel can also act as a suitable strain sensor for bio-friendly devices such as smart wearable electronic devices and/or for health monitoring.
更多
查看译文
关键词
conductive hydrogel,mussel,adhesive chemistry,remote monitoring
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要