Electronic nose system with micro gas sensor array

We have fabricated an electronic nose system using a thin film oxide semiconductor micro gas sensor array which shows only 65 mW of power consumption at an operating temperature of 300 degrees C. Principal component analysis and neural network pattern recognition analysis were used to identify 12 gas samples (CH3SH, (CH3)(3)N, C2H5OH and CO gases in the concentration range of 0.1-100 ppm) or six flavor samples (carrot, green onion, woman's perfume (eau de cologne), man's perfume (eau de toilette), 25% liquor (Korean soju) and 40% liquor (whisky)). Good separation among the gases with different concentrations or flavor samples was obtained using the principal component analysis. The recognition probability of the neural network was 100% for each of the 5 trials of 12 gas samples and 93% for each of 10 trials of 6 flavor samples.