A Coaxial Triboelectric Fiber Sensor for Human Motion Recognition and Rehabilitation via Machine Learning
This work presents the fabrication of a coaxial fiber triboelectric sensor (CFTES) designed for efficient energy harvesting and gesture detection in wearable electronics. The CFTES was fabricated using a facile one-step wet-spinning approach, with PVDF-HFP/CNTs/Carbon black as the conductive electro...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Nanoenergy Advances |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-706X/4/4/22 |
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| Summary: | This work presents the fabrication of a coaxial fiber triboelectric sensor (CFTES) designed for efficient energy harvesting and gesture detection in wearable electronics. The CFTES was fabricated using a facile one-step wet-spinning approach, with PVDF-HFP/CNTs/Carbon black as the conductive electrode and PVDF-HFP/MoS<sub>2</sub> as the triboelectric layer. The incorporation of 1T phase MoS<sub>2</sub> into the PVDF-HFP matrix significantly improves the sensor’s output owing to its electron capture capabilities. The sensor’s performance was carefully optimized by varying the weight percentage of MoS<sub>2</sub>, the thickness of the fiber core, and the CNT ratio. The optimized CFTES, with a core thickness of 156 µm and 0.6 wt% MoS<sub>2</sub>, achieved a stable output voltage of ~8.2 V at a frequency of 4 Hz and 10 N applied force, exhibiting remarkable robustness over 3600 s. Furthermore, the CFTES effectively detects human finger gestures, with machine learning algorithms further enhancing its accuracy. This innovative sensor offers a sustainable solution for energy transformation and has promising applications in smart portable power sources and wearable electronic devices. |
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| ISSN: | 2673-706X |