An investigation of the sensitivity of polymer-coated surface acoustic wave-based gas sensors in the detection of volatile organic compounds

Surface acoustic wave sensors (SAWs) are excellent at detecting volatile organic compounds (VOCs) since a sensing layer can be created by spreading a thin film of material across the delay line. This critically enhances performance as it is sensitive to the physical phenomena of interest. This study aims to provide a thorough investigation of the sensitivity of polymer-coated SAW-based gas sensors to VOCs using simulations via the finite element method (FEM). As such, quartz was chosen as the piezoelectric substrate while polymeric materials were chosen as the sensing layers due to their high sensitivity, low energy consumption, short response time, performance at room temperature, and reversibility after exposure to an analyte. The polymeric materials chosen were: (1) polyisobutylene (PIB), (2) polydimethylsiloxane (PDMS), (3) polyisoprene (PIP), (4) polyimide (PI), and (5) phenylmethyldiphenylsilicone (OV25). The VOCs chosen for investigation were: (1) dichloromethane (DCM), (2) trichloroethylene (TCE), (3) 1,2-dichloroethylene (DCE), and (4) carbon tetrachloride (CCl4). The performance of each polymer-coated SAW sensor was evaluated in terms of frequency shift and sensitivity to each VOC in FEM simulations. Our study found that the PIB-coated sensor had the highest sensitivity (4.0571 kHz/ppm) to DCM vapor and good sensitivity (45.257 kHz/ppm) to TCE vapor. However, the performance of each polymer-coated sensor varied depending on the type of VOC being tested. As an example, while the OV25-coated sensor was more sensitive (52.57 kHz/ppm) than the PIB-coated sensor (53.54 kHz/ppm) to TCE vapor regardless of the concentration, the PIB-coated sensor was more sensitive to DCM vapor at both low (4.06 kHz/ppm) and high (3.54 kHz/ppm) concentrations than the OV25-coated sensor. Therefore, the results of our FEM simulations indicate that polymer-coated SAW-based gas sensors are highly capable of self-powered VOC detection