Microcrack-Structured Visualizable Hydrogel Sensor for Machine Learning-Assisted Handwriting Recognition

Flexible wearable electronic devices based on conductive hydrogels have attracted considerable attention in recent years. However, there still remains a huge challenge to achieve a balance between the mutually exclusive sensing performance of stretchable conductive hydrogels. Inspired by the slit organs of spiders, a microcrack-structured visualizable hydrogel sensor (MVHS) based on Ti 3 C 2 T x (MXene)/carbon nanotube (CNT) synergistic interaction is developed. Benefiting from the strain-dependent microcrack structure design and the incorporation of fluorescent nitrogen-doped carbon quantum dots (N-CQDs), the MVHS possesses tunable mechanoluminescence (ML) properties and outstanding sensing performances including low detection limit (0.2% strain), exceptional sensitivity (gauge factor, GF = 10.92), large strain detection range (up to 2050%), as well as outstanding stability. Meanwhile, the strong hydrogen bonding between glycerol and water molecules imparts the MVHS with remarkable water retention and anti-freezing capabilities, significantly broadening its operational temperature range. Additionally, the MVHS can be employed as a stretchable flexible electrode for fabricating high-performance soft triboelectric nanogenerator (TENG). When combined with advanced machine learning algorithms, the sensor enables accurate handwriting recognition, demonstrating significant potential for applications in intelligent human–machine communication.