Nanocavitation reinforcement strategy for fatigue resistant eutectogels and triboelectric smart glove for sign language recognition assisted by deep learning

The fatigue resistance of flexible sensing materials under long-term cyclic loading presents a critical challenge in human-machine interaction. Although nanocavitation is a highly effective toughening mechanism widely used in elastomers, triggering it in hydrogels is difficult due to the weak interfacial interactions in aqueous media, which fail to support effective stress transfer. To overcome this thermodynamic barrier, this work exploits the unique molecular microenvironment of a deep eutectic solvent (DES) to successfully "unlock" the nanocavitation mechanism within a gel system for the first time. The DES not only achieves thermodynamically stable dispersion of nanoparticles but, more importantly, constructs reversible dynamic interfacial bonds. This design enables the material to actively trigger nanoscale cavitation under stress to dissipate energy, thereby endowing the gel with crack resistance and fatigue stability far superior to conventional hydrogels. Leveraging the superior fatigue resistance and mechanical stability of this eutectogel, we developed a triboelectric smart glove that achieved a real time sign language recognition accuracy of up to 99.9% with the help of deep learning. This study establishes a novel strategy centered on nanocavitation induced energy dissipation, providing a theoretical foundation for developing highly durable soft electronic devices.