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.
An artificial neural network (ANN)--the Kohonen Self-Organizing Feature Map (SOM)-is used to evaluate solid-state NMR spectroscopic derived data of 72 siloxane-based phosphine and organometallic functionalized hybrid polymers. The data set consists of parameters that describe their structural features and their dynamic behavior. The ANN visualizes similarities of the investigated compounds by reducing the dimension of the data set. This allows a comparison of these polymers that was not possible beforehand because of their structural diversity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.