Detection and identification of toxic environmental gases have assumed paramount importance precisely in the defense, industrial and civilian security sector. Numerous methods have been developed for the sensing of toxic gases in the environment ever since surface acoustic wave (SAW) technology came into existence. Such SAW sensors called electronic nose (E-Nose) sensor use the frequency response of a delay line/resonator. SAW device is focused and given importance. The selective coating between input and output interdigital transducers (IDTs) in the SAW device is responsible for corresponding changes in operating frequency of the device for a specific gas/vapour absorbed from the environment. A suitable combination of well-designed SAW delay lines with selective coatings not only help to improve sensor sensitivity and selectivity but also leads to the minimization of false frequency alarms in the E-Nose sensor. This article presents a comprehensive review of design, development, simulation and modelling of a SAW sensor for potential sensing of toxic environmental gases.
The paper presents the results of numerical analysis of the SAW gas sensor in the steady and non-steady states. The effect of SAW velocity changes vs surface electrical conductivity of the sensing layer is predicted. The conductivity of the porous sensing layer above the piezoelectric waveguide depends on the profile of the diffused gas molecule concentration inside the layer. The Knudsen’s model of gas diffusion was used. Numerical results for the effect of gas CH4 on layers: WO3, TiO2, NiO, SnO2 in the steady state and CH4 in the non-steady state in recovery step in the WO3 sensing layer have been shown. The main aim of the investigation was to study thin film interaction with target gases in the SAW sensor configuration based on simple reaction-diffusion equation. The results of the numerical analysis allow to select the sensor design conditions, including the morphology of the sensor layer, its thickness, operating temperature, and layer type. The numerical results basing on the code elaborated numerical system (written in Python language), were analysed. The theoretical results were verified and confirmed experimentally.