Design of super stretchability, rapid self-healing, and self-adhesion hydrogel based on starch for wearable strain sensors.

Since hydrogels are conductive, easily engineered, and sufficiently flexible to imitate the mechanical properties of human skin, they are seen as potential options for wearable strain sensors. However, it is still a great challenge to prepare a hydrogel through simple and straightforward methods that integrate excellent stretchability, ionic conductivity, toughness, self-adhesion, and self-healing. Herein, an acrylamide/3-acrylamide phenylboronic acid cross-linked network is modified to produce a semi-interpenetrating cross-linked hydrogel in just one easy step by adding starch. The prepared hydrogel contains dynamic boronic ester bonds and hydrogen bonds, which endow the exceptional stretchability (5769-13,976 %, 20-50 wt%), ideal transmittance (>90 %), self-adhesiveness (0.636 ± 0.060 kPa, 30 wt%), and self-healing properties. Notably, the self-healing process is completed instantly, achieving a healing strength of up to 81.21 %. Additionally, the aforementioned hydrogel exhibits a broad working strain range (≈ 500 %) and high sensitivity (gauge factor = 1.99) as a strain sensor, allowing it to record and track human actions precisely. This work provides a novel approach to synthesizing hydrogels with optimal overall mechanical characteristics, with the potential to facilitate the development of wearable strain sensing system based on hydrogels for real-world applications.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yanyan Li reports financial support was provided by Youth Science Foundation of Shanxi Province (202203021222012). Jian Zhang reports financial support was provided by Natural Science Foundation of Shanxi Province (20210302123458). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Ltd. All rights reserved.)