Self-powered sensor based on compressible ionic gel electrolyte for simultaneous determination of temperature and pressure

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.

Keywords

e-skin / gel electrolyte / machine learning / self-powered dual-mode sensor

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