AN INTEGRATED ARRAY OF MULTIPLE THIN-FILM METAL-OXIDE SENSORS FOR QUANTIFICATION OF INDIVIDUAL COMPONENTS IN ORGANIC VAPOR MIXTURES

This paper presents an integrated array consisting of eight thin-film metal oxide sensors and demonstrates its functional performance in analyzing mixtures of methanol and acetone. The sensors are fabricated into a 3.1 mm X 2.9 mm silicon chip in an eleven-mask process sequence. The sensing elements are constituted using single layers and bilayers of reactively sputtered thin films of SnO2, ZnO, TiO2, and WO3 with and without Pd catalyst. Elevated sensor temperature is achieved through on-chip boron-diffused heating elements. The sensor responses are processed by an artificial neural network for calibrating the sensor array and predicting the unknown vapor concentrations. The results show that the concentrations of acetone and methanol corresponding to the sensor responses can be quantitatively discriminated at a low cost of precision.