Mechanism and Experimental Research on Flexible Sensing using Ionic Conductive Gels

Abstract

Flexible sensors, as an emerging type of sensors, have been widely applied in intelligent systems such as the Internet of Things, wearable devices, health monitoring, and robotics. Among flexible sensors, tactile sensing and non-contact sensing cover most application scenarios. Researchers have proposed a series of methods for the development of flexible sensors, ranging from sensing materials to sensing structures. Although these methods exhibit unique advantages and cater to specific application scenarios, they also suffer from notable limitations that hinder the further application and widespread adoption of flexible sensors. These limitations include poor consistency and short service life of flexible sensing materials, complex designs of flexible sensing structures, and insufficient stability. Therefore, developing ionic conductive gels with tunable and controllable material properties as sensing materials, investigating their flexible sensing mechanisms, and developing the flexible sensors with simple structures, high sensing sensitivity, strong stability, and diverse detection capabilities, holds significant importance. Considering these challenges, this thesis studies the following topics:

Starting with the flexible sensing material, the solvent displacement method was verified to improve the conductivity stability, mechanical stability and service life of the ionic conductive gel. The effects of solvent displacement conditions on the conductivity and service life of the ionic conductive gel were systematically studied from three aspects: ionic content, solvent displacement solution composition and solvent displacement duration. Based on this, a method for preparing durable ionic conductive gel with controllable conductivity was proposed. Finally, from the aspect of material processing, the feasibility of the application of ionic conductive gel based on the solvent displacement method in the field of flexible sensing was demonstrated. This study provides a new solution for the development of flexible sensor sensing materials.

In the field of tactile flexible sensing, the tactile flexible sensing mechanism of ionic conductive gel was explained based on the tactile signal response experiment, and the corresponding sensing model was established. Based on the sensing model, one-dimensional and two-dimensional stress-insensitive flexible touchpads were developed, which realized the real-time and accurate recognition of single-finger and two-finger touch points and completed the application in the field of human-machine interaction. By adjusting the conductivity of the ionic conductive gel, the influence of conductivity on the sensitivity of the tactile flexible sensing model was revealed. Based on this, a topology optimization method for tactile flexible sensing structure was proposed, and a flexible wearable authenticator was constructed using handwritten digit detection as an example, equipped with corresponding control circuits and convolutional neural network algorithms, to achieve accurate recognition of multiple encrypted handwritten digits. This study provides a new strategy for the structural design and optimization of tactile flexible sensors.

In the field of non-contact flexible sensing, the mechanism of non-contact flexible sensing of ionic conductive gel was explained, and the corresponding signal response formula was proposed. A non-contact flexible sensing model was established, which improved the responsivity of the existing non-contact sensing model. Based on the signal response formula, an asymmetric sensor array structure was proposed, and a non-contact gesture recognition flexible human-machine interface and its supporting control circuit were developed. By combining with the neural network algorithm, accurate recognition of six non-contact gestures and continuous real-time control of external devices were achieved. This study provides theoretical support for the development of non-contact flexible sensor arrays.

Date of Award	31 Jul 2025
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Lishuai JIN (Supervisor), Jun LIU (Supervisor), Hongyuan JIANG (External Supervisor) & Zuankai Wang (External Co-Supervisor)