生物粘附
明胶
自愈水凝胶
材料科学
纳米技术
化学
高分子科学
化学工程
高分子化学
药物输送
有机化学
工程类
作者
Shiqiang Zhang,Jingjing Xia,Jiyu Chen,Lei Chen,Jingjiang Qiu,Zhongwei Guo,Ronghan Wei,Wei Sun
出处
期刊:Biomacromolecules
[American Chemical Society]
日期:2025-06-26
卷期号:26 (7): 4436-4448
被引量:8
标识
DOI:10.1021/acs.biomac.5c00425
摘要
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-M n+ hydrogels, with M n+ being Cu 2+, Zn 2+, Fe 3+, and Zr 4+ ) 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.
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