Numerical Analysis of Oxygen Adsorption on SnO 2

Oxidation of thin film SnO2 layer was simulated. In particular, the evolution of depletion layer was investigated by solving Poisson-Boltzmann equation for SnO2 slab geometry grains. On this basis, the surface energy barrier dependence on layer thickness (30–500 nm) was obtained. The effect of the donor mobility (oxygen vacancies in the bulk) and degree of donor ionization on electric potential inside layer with different thicknesses was discussed. Furthermore, the dependence of per-square conductance on temperature (from 400 K to 700 K) has been computed. It was assumed that the bulk oxygen vacancies (donors) are singly or doubly ionized and mobile. The temperature variations in the carrier mobility were also taken into account

A Robust and Low-Complexity Gas Recognition Technique for On-Chip Tin-Oxide Gas Sensor Array

Gas recognition is a new emerging research area with many civil, military, and industrial applications. The success of any gas recognition system depends on its computational complexity and its robustness. In this work, we propose a new low-complexity recognition method which is tested and successfully validated for tin-oxide gas sensor array chip. The recognition system is based on a vector angle similarity measure between the query gas and the representatives of the different gas classes. The latter are obtained using a clustering algorithm based on the same measure within the training data set. Experimented results on our in-house gas sensors array show more than 98% of correct recognition. The robustness of the proposed method is tested by recognizing gas measurements with simulated drift. Less than 1% of performance degradation is noted at the worst case scenario which represents a significant improvement when compared to the current state-of-the-art