Enhanced selectivity of MOSFET gas sensors by systematical analysis of transient parameters

Transient response curves from Pt-MOSFET gas sensors exposed to mixtures of hydrogen and ethanol were studied. Parameters of two types were extracted from the response curves: simple parameters like pulse heights, derivatives and integrals, and coefficients from different curve fitting algorithms. All parameters were evaluated with respect to their signal to standard deviation ratio, the correlations in a principal component analysis, and the parameters ability to predict the concentration levels using an artificial neural network. Combining these three evaluation methods it was possible to select transient parameters that with good accuracy could simultaneously predict the levels of hydrogen and ethanol in the test gas using information from only one sensor.