Semiconductor sensors are often used to solve an important practical problem – the determination of the concentration of carbon monoxide in the air. Their disadvantage is the low selectivity, which can lead to false alarm when other reducing gases such as ammonia or ethanol vapor appear in the air. To increase the selectivity, we used pulsed temperature modulation in combination with a special composition of the gas sensitive layer of the sensor. The use of pulse temperature modulation has revealed the features of the analyte associated with the sorption kinetics at the surface of the sensor, with the kinetics of the chemical interaction between reductant analytes and chemisorbed oxygen, and the kinetics of desorption of chemical interaction products. However, information on the qualitative composition of the medium is contained in the experimental data in an implicit form, because the qualitative analysis procedure with the use of low selectivity sensors has so far remained undeveloped. In this paper, we proposed a qualitative analysis method based on the power-law regression model that relates the concentration of analyte gas to the electrical resistance of the sensor at various times during the measurement cycle. The experimental procedure shown in our work leads to an increase in the sensitivity of the quantitative analysis by one or two orders of magnitude depending on the concentration of carbon monoxide.
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