Femtosecond laser-induced graphene-based green wood gas sensor

Abstract

In recent years, air pollution has emerged as a major environmental issue worldwide, posing a serious threat to human health and ecosystems. As a result, there is a growing demand for gas monitoring systems that can effectively monitor air pollution. However, most of the gas sensors used to monitor air pollution in this way are a type of electronic device, which generates e-waste, which is a significant environmental pollution problem that must be addressed. Therefore, there is a need for green gas sensors that do not generate e-waste by fabricating them with eco-friendly materials and methods. In this study, we fabricated an eco-friendly gas sensor based on laser-induced graphene (LIG) generated by patterning on wood. LIG was generated by a one-step process of irradiating wood with a femtosecond laser to fabricate an eco-friendly gas sensor with precision and efficiency. We confirmed that the fabricated gas sensor has a three-dimensional porous structure and responds to carbon monoxide, ammonia, and methane gases. We also fabricated a gas sensor array by doping CuO and CoO, which are different sensing materials, and developed a system that can selectively predict four gases (air, carbon monoxide, ammonia, and methane) in real-time by using the measured gas experimental data as training data for a convolutional neural network (CNN) algorithm. In the developed system, gas species classification of the four gases in real time was achieved with an accuracy of about 98%, and concentration prediction was also realized with an error range of about 12%. In addition, we measured the gases generated during forest fires and confirmed that it effectively detects forest fires. Thus, the femtosecond laser-induced graphene-based gas sensor developed in this study using a femtosecond laser and wood, combined with a deep learning algorithm, can effectively detect multiple types of gases selectively and within a short time, showing its potential as an eco-friendly gas sensor.