Phase Separation Manipulated Gradient Conductivity for A High‐Precision Flexible Pressure Sensor

Abstract Piezoresistive pressure sensors, analyzing and converting external pressure signals to readable electrical signals for monitoring human health, are always subjected to simultaneously possess high signal‐linearity and signal sensitivity. Analogous to the control of sophisticated microstructure for increasing active sensing area, the control of gradient conductivity should enable a linear response via regulating the formed saturation current. Here, inspired by phase separation showing the feasibility of controlling material microstructure and conductivity, a high‐performance flexible pressure sensor via the simultaneous control of microgroove structure and wide‐range gradient conductivity is demonstrated. First, a laser‐etching and dopamine (DA)‐doping synergistic approach is used to induce selective phase separation in poly(3,4‐ethylenedioxythiophene): poly(styrenesulfonic acid) (PEDOT:PSS), achieving broad conductivity modulation (from 297 to 4525 S cm −1 ) and precise microgroove pattern (15.5 µm). Then, by designing conductivity‐gradient PEDOT: PSS‐based multi‐sublayers and microgroove interlocked structure, the sensor shows extraordinarily comprehensive performance of excellent stress‐sensing sensitivity (4 × 10 5 kPa −1 ), high linear responsiveness (99.85%) and wide‐range sensing ability (up to 100 kPa). Consequently, this sensor reveals excellent capability in detecting multi‐mode pressure changes and is expected to branch out into other electronic device designs as a general strategy for the precise manipulation of material physical‐chemical properties.

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Publication Details

Journal
Advanced Functional Materials
Published
2024-09-01
DOI
https://doi.org/10.1002/adfm.202411390
Citations
32
Primary Topic
Advanced MEMS and NEMS Technologies
Type
article
Field-Weighted Citation Impact
6.68

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article

Phase Separation Manipulated Gradient Conductivity for A High‐Precision Flexible Pressure Sensor

Huabing Yin, Dan Wei, Yuan Tian, Chengheng Wu et al.
32 citations
Advanced Functional Materials
Advanced MEMS and NEMS Technologies
6.68
article

Phase Separation Manipulated Gradient Conductivity for A High‐Precision Flexible Pressure Sensor

Huabing Yin, Dan Wei, Yuan Tian, Chengheng Wu, Jie Ding, Jing Sun, Hongsong Fan, Mingze Zeng, Zhihong Chen, Yusheng Zhang, Xiaoyin Liu
article en
32 citations

Abstract

Abstract Piezoresistive pressure sensors, analyzing and converting external pressure signals to readable electrical signals for monitoring human health, are always subjected to simultaneously possess high signal‐linearity and signal sensitivity. Analogous to the control of sophisticated microstructure for increasing active sensing area, the control of gradient conductivity should enable a linear response via regulating the formed saturation current. Here, inspired by phase separation showing the feasibility of controlling material microstructure and conductivity, a high‐performance flexible pressure sensor via the simultaneous control of microgroove structure and wide‐range gradient conductivity is demonstrated. First, a laser‐etching and dopamine (DA)‐doping synergistic approach is used to induce selective phase separation in poly(3,4‐ethylenedioxythiophene): poly(styrenesulfonic acid) (PEDOT:PSS), achieving broad conductivity modulation (from 297 to 4525 S cm −1 ) and precise microgroove pattern (15.5 µm). Then, by designing conductivity‐gradient PEDOT: PSS‐based multi‐sublayers and microgroove interlocked structure, the sensor shows extraordinarily comprehensive performance of excellent stress‐sensing sensitivity (4 × 10 5 kPa −1 ), high linear responsiveness (99.85%) and wide‐range sensing ability (up to 100 kPa). Consequently, this sensor reveals excellent capability in detecting multi‐mode pressure changes and is expected to branch out into other electronic device designs as a general strategy for the precise manipulation of material physical‐chemical properties.

Advanced Functional MaterialsVol. 34(52)
Sichuan University (CN), West China Medical Center of Sichuan University (CN), University of Glasgow (GB)
National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province
Openalex Percentile: Top 3%
Advanced MEMS and NEMS Technologies
6.68
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