Hydrophobic Nanofiber‐Reinforced Paper‐Electrode Triboelectric Nanogenerator for High‐Efficiency Mechanical Energy Acquisition and Autonomous Motion Sensing
Ruida Cao, Yuxiao Hou, Weiwei Hu, Chencheng Hu +4
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75% confidenceThis MEC study investigates neural network, membrane. Key performance metrics include voltage output.
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Abstract
ABSTRACT Flexible and wearable triboelectric nanogenerators (TENGs) are considered promising candidates for mechanical energy harvesting and self‐powered sensing, yet simultaneously achieving high output performance together with environmental adaptability remains challenging. In this study, a hydrophobic nanofiber‐reinforced paper‐based TENG (HF‐PTENG) was developed by integrating (3‐aminopropyl)triethoxysilane (APTES)‐modified polyacrylonitrile/aramid nanofiber (PANA) membranes and a flexible conductive paper electrode (FCPE). The HF‐PTENG delivered an open‐circuit voltage of 384.3 V, a short‐circuit current of 15.1 µA, and a transferred charge of 149.5 nC, achieving a maximum instantaneous power destiny of 2.1 mW/cm 2 . Stable electrical output was maintained over 11 000 operation cycles, and efficient biomechanical energy harvesting was demonstrated from finger tapping, wrist bending, and knee motions to power capacitors, commercial LEDs, and sensors. A smart glove integrated with the HF‐PTENG was designed to achieve wireless control of a miniature car via WiFi communication. In addition, a 3×3 TENG sensor array was constructed to visualize planar pressure distribution. Separately, convolutional neural network (CNN) analysis enabled the recognition of six finger‐drawn patterns with an accuracy of 98.32%. This study offers a practical and scalable strategy for constructing high‐performance, flexible TENGs with board potential for applications in wearable electronics, human–machine interfaces, and intelligent motion sensing.
Keywords
Identifiers
- Journal
- Small Methods
- Year
- 2026