AI-based Liquid Classification with Laser-Induced Graphene Flex-Sensor

Abstract

Flexible sensors have a great impact in removing the barriers of the electronic components caused by their rigid shape. This study introduces optimal artificial intelligence algorithms for the classification of high precision flex-sensor outputs in sensing various liquids. The composite-based sensor was realized by combining polydimethylsiloxane (PDMS) and laser-induced graphene formed on polyimide (PI). PI substrate was engraved by blue laser to produce graphene sheets over the surface, while this approach decreases cost of sensor production, reliability of mass production was improved with less process steps. The recorded capacitance values were used to classify various liquids dropped over the sensor, then more than 90% accuracy, precision, and recall results were obtained under the scope of this study.