No abstract

Resistive gas sensors are very popular and reliable but suffer from low selectivity and sensitivity. Various methods have been suggested to improve both features without increasing the number of sensors in gas detection systems. Fluctuation enhanced gas sensing was proposed to improve gas detection efficiency by analyzing low-frequency resistance fluctuations, and noise parameters can be more informative than the single DC resistance and can advance gas detection systems by improving detection and limiting energy consumption. Gas sensor temperature can be modulated as well to further increase selectivity and sensitivity. Finally, some gas sensing layers exhibit a photo-catalytic effect, which can be applied to improve detection and yield lower operating temperatures of the gas sensing materials.

No abstract

Resistance noise data from a single gas sensor can be utilized to identify gas mixtures. We calculated the power spectral density, higher order probability densities and the bispectrum function of the recorded noise samples; these functions are sensitive to different natural vapors and can be employed to select a proper detection criterion for gas composites and odors.