Self-Powered Etiquette Training Systems Based on High-Performance ZnO Nanowire-Doped Polyvinylidene Fluoride Piezoelectric Nanogenerator

作者：Haixin Li, Yudong Wang, Xiongxin Luo, Dengzhou Jia, Wen G. Jiang, Jiandan Liang, Shounian Cheng, Xia Cao · 发表于：ACS Nano · 年份：2025 · DOI：10.1021/acsnano.5c14116 · 被引用次数：4 · 研究领域：Advanced Sensor and Energy Harvesting Materials、Tactile and Sensory Interactions、Electrospun Nanofibers in Biomedical Applications

Etiquette plays a fundamental role in daily life and socioeconomic development, necessitating its continual advancement toward professionalization and standardization. However, traditional etiquette training methods, which rely primarily on subjective manual instruction, suffer from low efficiency and lack standardized evaluation criteria. Addressing these limitations, this study presents a real-time etiquette training monitoring platform integrating self-powered piezoelectric sensors, signal acquisition and processing modules, and a LabVIEW-based monitoring program. The platform employs flexible ZnO nanowire-doped polyvinylidene fluoride (ZnO NWs/PVDF) fiber film fabricated via oriented electrospinning, achieving a high β-phase content of 94% and an ultrahigh piezoelectric coefficient (d 33 ) of 369.4 pm/V. The corresponding piezoelectric nanogenerator (ZP-PENG) outputs an open-circuit voltage up to 39 V and demonstrates excellent human motion capture capabilities, accurately monitoring joint movements such as elbow, neck, and waist in a range of 0–70°. Integrated with a multinode sensor network and LabVIEW software, the system effectively provides real-time, quantitative evaluation and standardized feedback on key etiquette behaviors, including handshake strength and duration, standing, and sitting postures. This data-driven, technologically empowered approach advances etiquette training from experience-based methods to a precise, scientific paradigm, promoting modernizatio...