Ultralong-Range Sensing of Non-Contact Triboelectric Nanogenerator via Synergistic Design of Porous Microspheres and High Dielectric Properties

Traditional sensors are often limited by their dependence on external power sources, reducing their scalability and applicability in remote or complex environments. Noncontact triboelectric nanogenerator (NC-TENG), based on the synergistic mechanisms of frictional electrification and electrostatic induction, can convert low-frequency mechanical energy into electrical energy, avoiding physical contact between materials and thus enabling long-term stable self-powered operation. This represents an effective solution for constructing self-powered sensing systems. However, NC-TENGs generally suffer from bottlenecks such as low surface charge density and strong sensitivity dependence on sensing distance. In this study, a porous microsphere-structured nanofibrous membrane with modified MXene (MMX) loaded with molybdenum disulfide was prepared through the synergistic action of Plateau-Rayleigh instability and Breath Figure mechanisms. Benefiting from the synergistic enhancement effect of the MMX hybrids and the microsphere structure, the dielectric properties of the membrane were significantly enhanced, with a dielectric constant of 45 and a surface charge density of 225 μC/m 2 . In the noncontact mode, the device achieves ultralong-distance detection capabilities of up to 7 m, and outputs electrical signals of 5, 8, and 12 mV corresponding to walking, running, and jumping, respectively. In addition, with deep learning algorithms optimizing recognition, the system can accurately distinguish multiple human dynamic behaviors, such as walking, running, and jumping, within the aforementioned distances. These results indicate that the proposed NC-TENG holds broad application prospects in intelligent, self-powered, and long-distance motion monitoring, and provides a new solution for the construction of smart cities.