Gel-based materials are promising candidates for flexible sensors in wearable health monitoring owing to their inherent flexibility, conductivity, and biocompatibility. However, integrating rapid fabrication, robust mechanical properties, and strong interfacial adhesion into a single gel system remains a significant challenge. Here, we report a liquid metal nanoparticle-initiated rapid polymerization strategy to fabricate organic-ionogels without external initiators or cross-linkers. The resulting gels exhibit ultrafast gelation (∼3 min), remarkable toughness (∼27 MJ m-3), high lap shear strength (∼2.4 MPa), and reliable strain sensing performance. Density functional theory (DFT) calculations reveal that strong intermolecular interactions, including hydrogen bonding and electrostatic forces, underpin the enhanced mechanical and adhesive properties. Furthermore, we demonstrate the practical utility of these liquid metal-organic-ionogels (LM-AHG) in a wearable health monitoring device (WHMD) integrated with machine learning algorithms. The system enables real-time, high-precision classification of joint rehabilitation stages based on strain signals, achieving 100% accuracy in stage identification. This work provides a rapid and scalable fabrication route for high-performance organic-ionogels and establishes a material-algorithm codesign paradigm for next-generation personalized rehabilitation and smart wearable electronics.
Bi et al. (2026) studied this question.