Distributed Flexible Sensors Based on Supercapacitor Gel Materials

TL;DR

Researchers developed flexible sensors using supercapacitor gel materials, demonstrating their potential for bionics applications.

Contribution

A novel gel-based sensor design combining acrylamide-lithium chloride and ionic liquid gels with mechanical and capacitive modeling.

Findings

The capacitance of the sensor correlates linearly with load pressure despite varying gel thickness.

A constitutive model of the gel's hyperelastic properties was established using stress–strain experiments.

Experimental validation confirmed the sensor's capacitive response and model accuracy after error correction.

Abstract

Gel material sensors are lightweight, have fast response speeds and low driving voltages, and have recently become a popular research topic worldwide in the bionics field. A sensing unit is formed by pressing two kinds of gel materials together: a positioning layer gel based on acrylamide and lithium chloride and a sensing layer gel based on the ionic liquid BMIMBF4. Based on a stress–strain experiment of the sensing layer gel, a constitutive relationship model of its hyperelastic mechanical properties was established, and the elastic modulus and Poisson’s ratio of the sensing layer material were deduced. The capacitive response of the ion‒gel shunt capacitor to loading was observed to prove its ability to act as a pressure sensor. Although the gel thickness differs, the capacitance and load pressure exhibit a linear relationship. The capacitance was measured via cyclic voltammetry using the equivalent plate capacitor model for the positioning layer gel. The capacitance range of the gel sensor of a certain size was obtained via the cyclic voltammetry integral formula, which provided parameters for circuit design. A plate capacitor model of the sensing layer gel and an open four-impedance branch parallel model of the positioning layer gel were established. Two confirmatory experiments were designed for the models: first, the relationship between the sensing layer force and capacitance was measured, and the function curve relationship was established via a black box model; second, the theoretical and measured points of the positioning layer were compared, and the error was analyzed and corrected.

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