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The mammalian olfactory system is able to detect many more odorants than the number of receptors it has by utilizing cross-reactive odorant receptors that generate unique response patterns for each odorant. Mimicking the mammalian system, artificial noses combine cross-reactive sensor arrays with pattern recognition algorithms to create robust odor-discrimination systems. The first artificial nose reported in 1982 utilized a tin-oxide sensor array. Since then, however, a wide range of sensor technologies have been developed and commercialized. This review highlights the most commonly employed sensor types in artificial noses: electrical, gravimetric, and optical sensors. The applications of nose systems are also reviewed, covering areas such as food and beverage quality control, chemical warfare agent detection, and medical diagnostics. A brief discussion of future trends for the technology is also provided.

This paper describes the use of a microsphere sensor technology that allows simple fabrication of vapor sensor arrays with reproducible response patterns. Microsphere sensor fabrication protocols are uncomplicated and yield billions of highly reproducible sensors. Microsphere sensor arrays combined with a generalized Whitney-Mann-Wilcoxen (GWMW) classifier were used to discriminate between the presence and absence of nitroaromatic compounds in high background vapor mixtures. The classifier was trained on one sensor array and then used to obtain 98.2 and 93.7% correct classification rates with data collected using two subsequent arrays made up to six months after the initial training was performed. These results represent an advance in the ability to transfer training data between multiple sensor arrays with a fluorescence-based artificial nose.