Smell identification of spices using nanomechanical membrane-type surface stress sensors

Abstract

Artificial olfaction, that is, a chemical sensor system that identifies samples by smell, has not been fully achieved because of the complex perceptional mechanism of olfaction. To realize an artificial olfactory system, not only an array of chemical sensors but also a valid feature extraction method is required. In this study, we achieved the identification of spices by smell using nanomechanical membrane-type surface stress sensors (MSS). Features were extracted from the sensing signals obtained from four MSS coated with different types of polymers, focusing on the chemical interactions between polymers and odor molecules. The principal component analysis (PCA) of the dataset consisting of the extracted parameters demonstrated the separation of each spice on the scatter plot. We discuss the strategy for improving odor identification based on the relationship between the results of PCA and the chemical species in the odors.