A Degradable, Highly Tough, and Resilient Nanocomposite Hydrogel for Self-Powered Wearable Sensors and a Deep Learning-assisted Recognition System
writer:Xiang Di a,b, Weiqiang Ran a,b, Yi Wang a,b, Ruotong Zhang a,b, Bo Yu a,b, Baohui Li a,b, Jiawen Hou
keywords:High resilience, Toughness, Deep learning, Multifunctional sensing, Morse code
source:期刊
Issue time:2026年
The conductive hydrogels always suffered from large hysteresis, low toughness and poor capability of accurately predicting physical deformation, which seriously restricted their application in smart wearable devices. Herein, a novel conductive hydrogel was fabricated using water-soluble chitosan-modified halloysite nanotubes (CS@HNTs) as an organic-inorganic hybrid crosslinker, which imparts high resilience, superior toughness, and excellent fatigue resistance to the resulting material. Through abundant multiple hydrogen bonds, electrostatic interactions between polymer chains and CS@HNTs, and coordination between aluminum ions and carboxyl groups, this system effectively organizes the polymer network without significantly increasing crosslinking density, thereby conferring remarkable mechanical properties (91.4% resilience and a toughness of 1.25 MJ/m3). The hierarchical energy dissipation mechanisms, dynamic mechanical response behavior, and network structure evolution of the materials were systematically characterized by rheology and low-field (LF) nuclear magnetic resonance (NMR) spectroscopy. Concurrently, the fully physically crosslinked network facilitates efficient ionic conduction and enables rapid degradation under alkaline conditions. The hydrogel-based sensor also demonstrates a notable thermal response, with a temperature coefficient of resistance of ?1.95%?C?1, allowing for precise monitoring of ambient temperature. Furthermore, we constructed a self-powered sensing system for identifying various human motions and, separately, developed an information security system that integrates deep learning algorithm to achieve highly efficient and accurate (98%) information encryption and decryption based on Morse code. This work provides a promising strategy for constructing high-performance, sustainable, and intelligent flexible wearable platforms.