Self‐Powered Triboelectric–Piezoelectric Hybrid Acoustic Sensor with Microcone Patterned Film Based on Poly(Vinylidene Fluoride)/ LNKNTS‐Mn Nanorods Composite

Abstract Hybrid piezoelectric/triboelectric nanogenerators combine the merits of piezoelectric and triboelectric nanogenerators, possessing enhanced electrical output and sensitivity. The growth of the Internet of Things has focused attention on acoustic sensors as a key technology. However, it remains challenging to achieve high sensing accuracy and self‐power capability, and the structures of the majority of hybrid nanogenerators are complex in integrating both functions, which limits their practical application in wearable electronics. Here, constructing a self‐powered triboelectric‐piezoelectric hybrid acoustic sensor (TPAS) is proposed with a simple structure based on a poly(vinylidene fluoride)/LNKNTS‐Mn nanorods composite film to simultaneously achieve coupling of piezoelectric charge generation and triboelectrification, thereby improving energy conversion efficiency. TPAS demonstrates outstanding acoustic sensing capabilities, achieving sensitivity and figure of merit sensitivity (FOM sens ) of 162.5 mV Pa −1 and 42.33 mV·Pa −1 ·cm −2 , respectively, at 200 Hz and 94 dB, a broad frequency range (100 Hz–3 kHz). Leveraging machine learning and deep learning algorithms, the system achieves classification accuracies of 95% during training and 98% during testing across 300 voice samples spanning six distinct categories. These results underscore the potential of triboelectric–piezoelectric hybrid sensors as a foundational platform for the next generation of intelligent bioelectronic systems, offering a universal approach to advanced human–machine interaction.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-08-22
DOI
https://doi.org/10.1002/adfm.202514004
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.67

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article

Self‐Powered Triboelectric–Piezoelectric Hybrid Acoustic Sensor with Microcone Patterned Film Based on Poly(Vinylidene Fluoride)/ LNKNTS‐Mn Nanorods Composite

SUMBUL REHMAN, Zhiyu Yao, Jinxia Deng, Iqra Shahbaz et al.
1 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
0.67
article

Self‐Powered Triboelectric–Piezoelectric Hybrid Acoustic Sensor with Microcone Patterned Film Based on Poly(Vinylidene Fluoride)/ LNKNTS‐Mn Nanorods Composite

SUMBUL REHMAN, Zhiyu Yao, Jinxia Deng, Iqra Shahbaz, Lihong Li, Yanlin Song
article en
1 citations

Abstract

Abstract Hybrid piezoelectric/triboelectric nanogenerators combine the merits of piezoelectric and triboelectric nanogenerators, possessing enhanced electrical output and sensitivity. The growth of the Internet of Things has focused attention on acoustic sensors as a key technology. However, it remains challenging to achieve high sensing accuracy and self‐power capability, and the structures of the majority of hybrid nanogenerators are complex in integrating both functions, which limits their practical application in wearable electronics. Here, constructing a self‐powered triboelectric‐piezoelectric hybrid acoustic sensor (TPAS) is proposed with a simple structure based on a poly(vinylidene fluoride)/LNKNTS‐Mn nanorods composite film to simultaneously achieve coupling of piezoelectric charge generation and triboelectrification, thereby improving energy conversion efficiency. TPAS demonstrates outstanding acoustic sensing capabilities, achieving sensitivity and figure of merit sensitivity (FOM sens ) of 162.5 mV Pa −1 and 42.33 mV·Pa −1 ·cm −2 , respectively, at 200 Hz and 94 dB, a broad frequency range (100 Hz–3 kHz). Leveraging machine learning and deep learning algorithms, the system achieves classification accuracies of 95% during training and 98% during testing across 300 voice samples spanning six distinct categories. These results underscore the potential of triboelectric–piezoelectric hybrid sensors as a foundational platform for the next generation of intelligent bioelectronic systems, offering a universal approach to advanced human–machine interaction.

Advanced Functional MaterialsVol. 36(9)
Beijing National Laboratory for Molecular Sciences (CN), University of Chinese Academy of Sciences (CN), University of Science and Technology Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 28%
Advanced Sensor and Energy Harvesting Materials
0.67
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