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February 21, 2026Small Methods0 citations

Hydrophobic Nanofiber‐Reinforced Paper‐Electrode Triboelectric Nanogenerator for High‐Efficiency Mechanical Energy Acquisition and Autonomous Motion Sensing

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RCRuida CaoYHYuxiao HouWHWeiwei Hu

Key Points

  • The study aims to develop a high-performance triboelectric nanogenerator (TENG) using hydrophobic nanofibers for energy harvesting from mechanical motions.
  • Developed hydrophobic nanofiber‐reinforced paper‐based TENG using modified polyacrylonitrile/aramid nanofiber membranes.
  • Integrated a flexible conductive paper electrode for enhanced performance.
  • Tested energy output through various mechanical actions like finger tapping and wrist bending.
  • Designed a smart glove for wireless control of a car using the TENG.
  • Constructed a 3x3 sensor array for pressure distribution visualization and used convolutional neural network analysis.
  • Achieved open-circuit voltage of 384.3 V and short-circuit current of 15.1 µA.
  • Demonstrated maximum instantaneous power density of 2.1 mW/cm².
  • Maintained stable electrical output over 11,000 operation cycles.
  • Successfully recognized finger-drawn patterns with 98.32% accuracy.

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.

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Cite This Study

Cao et al. (2026) studied this question.

synapsesocial.com/papers/69994bef873532290d02014ahttps://doi.org/10.1002/smtd.202502422
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