Triboelectric nanogenerators (TENGs) hold great promise as self-powered sensors, but their practical applications are limited by charge leakage at high filler concentrations, coupled pressure-frequency responses, and poor discrimination of materials with similar triboelectric outputs, such as fabrics. In this work, a multifunctional design integrating a double-coated multiwalled carbon nanotubes (MWCNTs)/polydimethylsiloxane (PDMS) composite film-based TENG (DMP-TENG) with a dual-TENG strategy was developed to address these challenges. To determine a suitable base layer, a single-coated MWCNTs/PDMS composite film-based TENG (SMP-TENG) was first fabricated to identify the optimal filler concentration, providing the foundation for a double-coating design. By introducing a second coating with a higher dielectric constant, the resulting DMP-TENG achieved enhanced triboelectric output by increasing the surface dielectric constant without affecting the conductive network of the base layer. Although the intrinsic signals of the DMP-TENG are coupled, highly linear and decoupled sensing of pressure and frequency was realized through open- and short-circuit configurations, with sensitivities of 0.137 V/kPa and 0.297 μA/Hz, and fast response/recovery times of 77/76 ms. Using a portable testing system, ten representative human motions-including standing, walking, running, jumping, stair climbing, and falling-were accurately recognized with a testing accuracy of 98.56% via a random forest algorithm. Moreover, a dual-TENG strategy combining the DMP-TENG with a polyethylene terephthalate (PET) film-based TENG (PET-TENG) significantly boosted fabric recognition accuracy from 68.02% to 98.76% across 12 representative textile types. These results highlight the potential of the proposed DMP-TENG and dual-TENG strategy as versatile, self-powered, and intelligent sensing platforms for next-generation wearable electronics, smart textiles, and human-machine interaction.
Liu et al. (Wed,) studied this question.