Chiral discrimination of limonene by use of beta-cyclodextrin-coated quartz-crystal-microbalances (QCMs) and data evaluation by artificial neuronal networks.

The enantiomeric composition of the chiral flavoring agent limonene was analyzed by means of a quartz-crystal microbalance (QCM) sensor. As chiral selectors three different modified beta-cyclodextrins were investigated. The selector molecules were applied as mixtures in different polysiloxane matrices. The chiral separation factors alpha for limonene obtained at 30 degrees C by gas chromatography and by use of the QCM sensor were comparable. Evaluation of sensor data was performed by use of an artificial neuronal network (ANN); this enabled prediction of the enantiomeric composition of the gas mixtures.