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High‐Performance Pressure and Temperature Dual‐Mode Sensor Based on Thermoelectric Aerogels for Multimodal Intellectual Panel Application
Author(s) -
Jiang Saihua,
Wang Zubin,
Li Shun,
Huang Yubing,
Lan Yang,
Li Guohui
Publication year - 2025
Publication title -
advanced materials technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.184
H-Index - 42
ISSN - 2365-709X
DOI - 10.1002/admt.202401891
Subject(s) - thermoelectric effect , dual mode , materials science , dual (grammatical number) , optoelectronics , mode (computer interface) , engineering physics , composite material , electronic engineering , computer science , engineering , physics , thermodynamics , art , literature , operating system
Abstract Developing sensors with multi‐sensory detection capabilities will streamline integrated systems and simplify the integration process. Herein, dual‐mode temperature and pressure sensors based on PEDOT: PSS/CNTs/CNF/MXene (PCCM) is established. In terms of temperature sensing, the aerogel structure and introduction of MXene provide ultra‐low thermal conductivity, ensuring a stable temperature gradient. The addition of CNTs forms an excellent conductive network, significantly enhancing temperature sensing performance and achieving a maximum Seebeck coefficient of 28.2 µV K −1 , the introduction of MXene ensures PCCM the output electrical signal has ultra‐low noise and a high signal‐to‐noise ratio, allowing the detection of temperature differences as small as 0.05 K. Regarding pressure sensing, the sensitivity exhibited in the low‐pressure range (0–4 kPa) is −11.44% kPa −1 . Additionally, MXene significantly increases the sensor's electrical conductivity, reducing electron scattering and obstacles, shortening the response and recovery times (120 ms) for pressure measurements, and combining with CNTs/CNF increasing the hardness of the PCCM sensor, thereby expanding the pressure measurement range (0–20 kPa). It also highlights its promising potential for skin‐like sensing and human–computer interaction applications by developing a multimodal intellectual panel. This work provides a simple and scalable fabrication method to design high‐performance multifunctional sensors for various applications, such as e‐skin and robotics.

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