Estimation of multicomponent organic solvent vapor mixture composition with electroconducting polymer chemiresistors

An approach to quantitative analysis of multicomponent gaseous mixtures with an array of cross-selective sensors is proposed, and experimentally tested with the mixtures of four organic solvent vapors (acetone, chloroform, isopropanol and toluene) in atmospheric air and conducting polymer based chemiresistive sensors with three different sensitive coatings - polyaniline, polypyrrole and poly-3-methyltiophene doped with phosphotungstic and perchloric acid ions. The proposed method employs simplified semi-parametric model for prediction of the sensor responses, with emphasis on direct use of the information contained in the reference calibration data. Analysis algorithm is based on the matching between predicted and observed responses with additional regularization of the optimal prediction search procedure. Potential possibility of utilization of the presented approach for quantitative analysis of selected components, albeit with limited accuracy, is demonstrated, with the best case relative error of about 30% achieved for the studied sample data. The ways to further improvement of the analysis quality are discussed.