Design and Simulation of SAW Sensor in COMSOL Multiphysics for Detection of Hexanal in Exhaled Breath

Lung cancer remains a widespread health problem worldwide and maintains a dismal position as the leading cause of cancer deaths. The disease continues to claim significant lives, surpassing other cancers in mortality in both men and women. Considering this alarming reality, it is urgent to explore innovative diagnostic methods that can detect lung cancer in its early stages. The study of volatile organic compounds (VOCs) present in exhaled breath (EX) has emerged as a promising avenue to demonstrate their potential as biomarkers for various lung diseases. One particularly notable metabolic process contributing to this area is the peroxidation of unsaturated fatty acids, which results in the formation of a variety of volatile organic compounds, including aldehydes. Cancer cells, especially lung cancer, exhibit elevated levels of reactive oxygen species, which promote random lipid peroxidation and subsequent formation of various aldehydes. It is important to note that a significant portion of these volatile aldehydes are excreted from the body, which is why they are of interest as potential markers for early disease detection. Gas evaluation, especially the detection of low-concentration compounds such as hexanal, requires the development of highly accurate sensors. Therefore, we chose surface acoustic wave (SAW) sensors, which are known for their gas detection accuracy. The complex process involves designing and modeling the SAW sensor using COMSOL Multiphysics 6.2. The adsorption rate and conductivity of the gas sensor are determined based on the electric potential and the frequency response is examined at various eigen frequencies. Based on the results obtained, subsequent steps include further characterization and fabrication of a biosensor designed to detect volatile organic compounds (VOCs), which will enable the analysis of human exhaled air.