Chemiresistor sensors array optimization by using the method of coupled statistical techniques and its application as an electronic nose for some organic vapors recognition

An electronic nose (EN) based on an array of chemiresistors, combined with a preconcentrator unit, for the detection of some volatile organic vapors was developed. In order to choose the proper polymers, seven potential polymers were chosen from numerous available polymers according to the principle of the linear solvation energy relationship (LSER). Different possible sensors arrays (128 arrays) composed of these seven polymers were designed by full factorial design (FFD). Principal component analysis (PCA) showed that four of seven polymers had enough ability to recognize different gas classes. By using Hierarchical cluster analysis (HCA), the tested polymers were categorized into four main groups with respect to their recognition ability. Combination of the FFD with PCA and HCA, brought to the identification of 8 proper arrays containing four polymers in each array. Precisely evaluation of predicted arrays with respect to their calculated resolution factors showed that the electronic nose containing the polymers of 75% pheny125% methylpolysiloxane (OV25), hexafluoro-2-propanolsubstituted polysiloxane (SXFA), poly bis(cyanopropyl)-siloxane (SXCN) and poly(ethylene maleate) (PEM) was the most proper design for recognition of analytes of interest. The fabricated EN was used successively for target gas recognition at three different concentrations.

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