Design and development of selfpowered pressure sensors based on triboelectric principle

Goh, Qi Lun (2022) Design and development of selfpowered pressure sensors based on triboelectric principle. Master dissertation/thesis, UTAR.

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Abstract

Triboelectric nanogenerator (TENG) achieving a selfis a promising approach in powered pressure sensing application. However, most reported TENG is usually developed using solid and rigid materials which do not comply with soft and irregular surfaces such as human skin and soft robotic, obstructing it from performing conformal s ensing for a wearable device and soft robotic application. One of the methods to resolve the problems mentioned above is to develop the TENG with stretchable materials. To explore triboelectric based pressure sensing on soft and irregular surfaces , this dissertation reported selfpowered pressure sensors fabricated from soft and stretchable materials and evaluated their performance for both human pressure sensing and soft robotic application for pickandplace operation. Polydimethylsiloxane (PDMS) elastomer and deionised water are proposed as triboelectric materials to develop our first soft and wearable self powered pressure sensor. The sensorachieved a sensitivity of 0.20 mV/kPa for fingertip pressure sensing and was successfully used for humanm achine interface (HMI) application as a proof of principle in demonstrating the sensor’s sensitivity. It is also highly compressible and flexible, preventing cracking compared to the traditional solidstate triboelectric sensors. However, we found that t he output voltage highly relies on compression stroke at the water chamber in our first sensor design, limiting the sensor from detecting larger pressure input such as hand tapping motion. Therefore, in our second approach, we introduced a spongelike stru cture in the elastomer to increase the contacted surface area of the triboelectric materials. With this modification, the sensing performance of the pressure sensor has been improved by an increased factor of 40 times when harvesting energy from the human hand tapping motion. This improvement allows the TENG sensor to generate a momentary power density of 99.47 μW/cm Furthermore, eutectic galliumindium ( EGAIn 2 and light up several LEDs. ) was mixed in the elastomer to make it a conductive medium. Thus, the eliminated. necessity for solid electrodes can be Upon exploring the capability of the eutectic gallium made sponge-- indium ( EGAIn ) like pressure sensor in human pressure sensing, we further leveraged it to a pneumatic actuated soft robotic gripper to per form object recognition in pick and place operation. The pressure sensor is characterised with a sensitivity of 43 mV/kPa. To detect the bending angle of the fingers in the soft gripper, we develop bending sensors using the same material and principle as t he pressure sensor. The collected signals were then used to recognize objects through the support vector machine (SVM) learning approach. The accuracy of the soft gripper can be achieved up to 91.6%. The developed selfpowered and soft sensor has successfu lly proven its ability to detect pressure with different magnitudes and operating frequencies for soft robotic applications.

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