Hybrid nanogenerator with dual-mode sensing capability for intelligent material recognition and energy harvesting

Abstract

The hybrid nanogenerator (HNG) represents a transformative dual-mode sensing platform enabling concurrent material identification and temperature detection. This study fabricated electrospun polyvinylidene fluoride/barium titanate (PVDF/BTO) composite films as core functional components, where the PVDF matrix demonstrated exceptional ferroelectric responsiveness to ambient thermal fluctuations, while perovskite-structured BTO nanoparticles provided enhanced piezoelectric and dielectric characteristics essential for hybrid energy harvesting. Building upon this composite architecture, we engineered a triboelectric nanogenerator (Z-TENG) featuring two breakthrough capabilities: (i) quantitative characterization of contact materials through output voltage signatures, and (ii) intrinsic temperature sensing via PVDF's pyroelectric response. Synergistic BTO integration boosted the Z-TENG's voltage output by 157.7 % compared to pristine PVDF-based counterparts. Furthermore, the HNG system achieved 96 % material classification accuracy through machine learning-enhanced multimodal signal analysis, demonstrating a statistically significant improvement over conventional single-mode triboelectric systems (83.6 %). This study not only highlights the significant advantages of HNG in the field of object recognition, but also provides a new perspective and path for exploring more intelligent and efficient energy collection and object recognition technology.