Ultra-Elastic, Transparent, and Conductive Gelatin/Alginate-Based Bioadhesive Hydrogel for Enhanced Human-Machine Interactive Applications.

Abstract

Growing interest has focused on next-generation flexible adhesive sensors (FAS) integrated with deep learning for intelligent electronics. Existing conductive hydrogels, however, fail to concurrently achieve high stretchability, transparency, robust adhesion, and interactive precision. Here, a novel class of high-performance ionic hydrogels (AGG-Mⁿ⁺ hydrogels, with Mⁿ⁺ being Cu²⁺, Zn²⁺, Fe³⁺, and Zr⁴⁺) that synergistically combines the above features is developed. The hydrogel is fabricated by incorporating aldehyde-modified sodium alginate (Ald-alginate), gelatin methacrylate (GelMA), and glycerol into the poly(acrylic acid) network through free-radical polymerization plus an ionic coordination strategy. This endows the hydrogel with remarkable properties required for FAS applications, including excellent stretchability (1038%), optimal ionic conductivity (3.25 S/m), and high sensitivity (gauge factor = 1.932, 0%-600% strain range), accompanied by reliable long-term stability over 300 cycles. We also demonstrated its efficiency through the real-time monitoring of diverse physiological signals. Furthermore, the hydrogel was integrated with a deep learning algorithm into a wearable electronic control system, which can instantaneously recognize a diverse array of complex gestures with up to 99.4% accuracy. This work provides new insights for the future development of multifunctional hydrogels, wearable electronics, and human-machine interactions.