Spheres Multiple Physical Network‐Based Triboelectric Materials for Self‐Powered Contactless Sensing. Issue 25 (19th May 2022) - Zhang, Wanglin; Lu, Yanxu; Liu, Tao; Zhao, Jiamin; Liu, Yanhua; Fu, Qiu; Mo, Jilong; Cai, Chenchen; Nie, Shuangxi
Abstract: Non‐contact mode triboelectric nanogenerators effectively avoid physical contact between two triboelectric materials and achieve long‐term reliable operation, providing broad application prospects in the field of self‐powered sensing. However, the low surface charge density of triboelectric materials restricts application of contactless sensing. Herein, by controlling Rayleigh Instability deformation of the spinning jet and vapor‐induced phase separation during electrostatic spinning, a polyvinylidene fluoride@Mxene (Ti3 C2 T x ) composite film with spheres multiple physical network structures is prepared and utilized as the triboelectric material of a self‐powered contactless sensor. The structure of the composite film and high conductivity of Ti3 C2 T x provide triboelectric materials with high output performance (charge output and power output up to 128 µC m –2 and 200 µW cm –2 at 2 Hz) and high output stability. The self‐powered contactless sensor shows excellent speed sensitivity (1.175 Vs m –1 ). Additionally, it could accurately identify the motion states such as running (55 mV), jumping (105 mV), and walking (40 mV) within the range of 70 cm, and present the signals in different pop forms. This work lays a solid foundation for the development and application of high‐performance triboelectric materials, and has guiding significance for the research of self‐powered contactless sensing. Abstract : A facile electrostatic spinning method to fabricate PVDF@Mxene composites with spherical multiple physical networks serving as triboelectric materials for a non‐contact triboelectric nanogenerator is developed. This material's architecture exhibits high charge and power output (128 µC m –2 and 200 µW cm –2 ). In a certain range, it can effectively monitor the human movement status and position in real time.