Discrimination and quantification of volatile organic compounds in the ppb-range with gas sensitive SiC-FETs using multivariate statistics

•Detection of typical VOCs in the ppb-range using SiC-FETs.•Discrimination of VOCs using Linear Discriminant and Partial Least Squares – Discriminant Analysis.•Quantification of naphthalene using Partial Least Squares Regression.•Discrimination and quantification independent of background humidity. Gas sensitive field effect transistors based on silicon carbide, SiC-FETs, have been studied for indoor air quality applications. The selectivity of the sensors was increased by temperature cycled operation, TCO, and data evaluation based on multivariate statistics. Discrimination of benzene, naphthalene, and formaldehyde independent of the level of background humidity is possible by using shape describing features as input for Linear Discriminant Analysis, LDA, or Partial Least Squares – Discriminant Analysis, PLS-DA. Leave-one-out cross-validation leads to a correct classification rate of 90% for LDA, and for PLS-DA a classification rate of 83% is achieved. Quantification of naphthalene in the relevant concentration range, i.e., 0–40ppb, was performed by Partial Least Squares Regression and a combination of LDA with a second order polynomial fit function. The resolution of the model based on a calibration with three concentrations was approximately 8ppb at 40ppb naphthalene for both algorithms. Hence, the suggested strategy is suitable for on demand ventilation control in indoor air quality application systems.