Enhanced Positive Charge Performance in Triboelectric Series: Molecular Engineering of Conjugated Mesoporous Fibers for Machine Learning-Based Wearable Sensors

AbstractWith the increasing focus on triboelectric‐based sensors, research on synthesizing dielectric layers from specific substances is gradually emerging. Despite numerous negatively‐charged triboelectric materials, there is a scarcity of synthesizable positively‐charged materials, creating a research gap. This study demonstrates the molecular design of a conjugated, mesoporous, self‐assembled sheet via bottom‐up synthesis. The synthesized sheet is functionalized to create a triboelectric nanogenerator. Its large specific surface area, softness, and internal space increase the actual contact area and provide adsorption sites for polypyrrole nanoparticles. The incorporation of ‐COO functional group enhances positive triboelectric performance, forming a dielectric layer with charge‐trapping capabilities. When contact with polytetrafluoroethylene (PTFE), this structure boosts the output voltage, showing significant amplification after charge injection with minimal decay. As a demonstration, the bilayer structure is applied as a touchpad on the experimenter's arm to write symbols. The signals are input into an innovative machine‐learning model to interpret the writer's intent. Additionally, the device connects to a terminal for real‐time medical services, suggesting practical applications for wearable triboelectric sensors with artificial intelligence.