A Self‐Powered, Highly Sensitive, and Frequency‐Tunable Triboelectric Acoustic Sensor Inspired by the Human Cochlea

Abstract Conventional acoustic sensors used in human–machine interfaces often face challenges such as power supply requirements, limited sensitivity, and inability to tune their frequency response. A self‐powered, highly sensitive, and frequency‐tunable triboelectric acoustic sensor inspired by the human cochlea is introduced. By mimicking hair cells in the organ of Corti, a tapered microhair‐structured ferroelectric poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP) and barium titanate nanoparticle (BTNP) composite film is proposed, which demonstrates a 16‐fold increase in triboelectric output voltage (1.3 V) compared to a planar one at 2.8 Pa. Furthermore, inspired by the frequency selectivity of the basilar membrane with gradient structural variations, integrating a mass‐beam diaphragm is proposed with varying kirigami length and circular mass diameter that enables precise tuning of the resonance frequency of the sensor, resulting in a 32 times improvement in sensitivity (860 mV Pa −1 ) compared to a nonbiomimetic sensor (28 mV Pa −1 ) and an expanded dynamic range. The proposed sensor differentiates between human voices with different frequencies. A robotic hand integrated with the sensor responds to acoustic stimuli with programmed hand gestures, which highlights its potential in acoustic human–machine interfaces. The biomimetic approach to developing a self‐powered, highly sensitive, and frequency‐tunable acoustic sensor offers new possibilities for intuitive and immersive human–machine interfaces.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2024-09-30
DOI
https://doi.org/10.1002/adfm.202408344
Citations
18
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
3.32

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Self‐Powered, Highly Sensitive, and Frequency‐Tunable Triboelectric Acoustic Sensor Inspired by the Human Cochlea

Jae Joon Kim, Young‐Ryul Kim, Donghee Kang, Yun Goo Ro et al.
18 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
3.32
article

A Self‐Powered, Highly Sensitive, and Frequency‐Tunable Triboelectric Acoustic Sensor Inspired by the Human Cochlea

Jae Joon Kim, Young‐Ryul Kim, Donghee Kang, Yun Goo Ro, Hyunhyub Ko, Jonghwa Park, Min Sub Kwak, Jin‐Young Kim, Hyejin Lee, Minseop Song, Jiin Lee, Geonyoung Jung
article en
18 citations

Abstract

Abstract Conventional acoustic sensors used in human–machine interfaces often face challenges such as power supply requirements, limited sensitivity, and inability to tune their frequency response. A self‐powered, highly sensitive, and frequency‐tunable triboelectric acoustic sensor inspired by the human cochlea is introduced. By mimicking hair cells in the organ of Corti, a tapered microhair‐structured ferroelectric poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP) and barium titanate nanoparticle (BTNP) composite film is proposed, which demonstrates a 16‐fold increase in triboelectric output voltage (1.3 V) compared to a planar one at 2.8 Pa. Furthermore, inspired by the frequency selectivity of the basilar membrane with gradient structural variations, integrating a mass‐beam diaphragm is proposed with varying kirigami length and circular mass diameter that enables precise tuning of the resonance frequency of the sensor, resulting in a 32 times improvement in sensitivity (860 mV Pa −1 ) compared to a nonbiomimetic sensor (28 mV Pa −1 ) and an expanded dynamic range. The proposed sensor differentiates between human voices with different frequencies. A robotic hand integrated with the sensor responds to acoustic stimuli with programmed hand gestures, which highlights its potential in acoustic human–machine interfaces. The biomimetic approach to developing a self‐powered, highly sensitive, and frequency‐tunable acoustic sensor offers new possibilities for intuitive and immersive human–machine interfaces.

Advanced Functional MaterialsVol. 34(48)
Ulsan National Institute of Science and Technology (KR)
National Research Foundation
Openalex Percentile: Top 7%
Advanced Sensor and Energy Harvesting Materials
3.32
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.