Class specific discrimination of volatile organic compounds using a quartz crystal microbalance based multisensor array

The use of quartz crystal microbalance (QCM) sensor arrays for analyses of volatile organic compounds (VOC) has attracted significant interest in recent years. In this regard, a group of uniformed materials based on organic salts (GUMBOS) has proven to be promising recognition elements in QCM based sensor arrays due to diverse properties afforded by this class of tunable materials. Herein, we examine the application of four novel phthalocyanine based GUMBOS as recognition elements for VOC sensing using a QCM based multisensor array (MSA). These synthesized GUMBOS are composed of copper (II) phthalocyaninetetrasulfonate (CuPcS4) anions coupled with ammonium or phosphonium cations respectively (tetrabutylammonium (TBA), tetrabutylphosphonium (P4444), 3-(dodecyldimethyl-ammonio)propanesulfonate (DDMA), and tributyl-n-octylphosphonium (P4448)). These materials were characterized using ESI-MS and FTIR, while thermal properties were investigated using TGA. Vapor sensing properties of these GUMBOS towards a set of common VOCs at three sample flow rate ratios were examined. Upon exposure to VOCs, each sensor generated analyte specific response patterns that were recorded and analyzed using principal component and discriminant analyses. Use of this MSA allowed discrimination of analytes into different functional group classes (alcohols, chlorohydrocarbons, aromatic hydrocarbons, and hydrocarbons) with 98.6% accuracy. Evaluation of these results provides further insight into the use of phthalocyanine GUMBOS as recognition elements for QCM-based MSAs for VOC discrimination. [Display omitted] •Four novel GUMBOS using copper (II) phthalocyanine tetrasulfonate were synthesized.•GUMBOS showed good thermal stability and cross-reactive responses.•Class specificity of ten analytes was achieved with 98.6% accuracy.•High accuracy was achieved using original data set as predictor variables in QDA.