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

Abstract 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.