Self‐powered sensor based on compressible ionic gel electrolyte for simultaneous determination of temperature and pressure
Junjie Zou,
Yanan Ma,
Chenxu Liu,
Yimei Xie,
Xingyao Dai,
Xinhui Li,
Shuxuan Li,
Shaohui Peng,
Yang Yue,
Shuo Wang,
Ce‐Wen Nan,
Xin Zhang
Affiliations
Junjie Zou
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Yanan Ma
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Chenxu Liu
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Yimei Xie
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Xingyao Dai
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Xinhui Li
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Shuxuan Li
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Shaohui Peng
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Yang Yue
Information Materials and Intelligent Sensing Laboratory of Anhui Province, Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of Education, Institutes of Physical Science and Information Technology Anhui University Hefei the People's Republic of China
Shuo Wang
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Ce‐Wen Nan
State Key Lab of New Ceramics and Fine Processing, School of Materials Science and Engineering Tsinghua University Beijing the People's Republic of China
Xin Zhang
State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center of Smart Materials and Devices & International School of Materials Science and Engineering Wuhan University of Technology Wuhan the People's Republic of China
Abstract The simultaneous detection of multiple stimuli, such as pressure and temperature, has long been a persistent challenge for developing electronic skin (e‐skin) to emulate the functionality of human skin. Meanwhile, the demand for integrated power supply units is an additional pressing concern to achieve its lightweightness and flexibility. Herein, we propose a self‐powered dual temperature–pressure (SPDM) sensor, which utilizes a compressible ionic gel electrolyte driven by the potential difference between MXene and Al electrodes. The SPDM sensor exhibits a rapid and timely response to changes in pressure‐induced deformation, while exhibiting a slow and hysteretic response to temperature variations. These distinct response characteristics enable the differentiation of current signals generated by different stimuli through machine learning, resulting in an impressive accuracy rate of 99.1%. Furthermore, the developed SPDM sensor exhibits a wide pressure detection range of 0–800 kPa and a broad temperature detection range of 5–75°C, encompassing the environmental conditions encountered in daily human life. The dual‐mode coupled strategy by machine learning provides an effective approach for temperature and pressure detection and discrimination, showcasing its potential applications in wearable electronics, intelligent robots, human–machine interactions, and so on.
