APPLICATION OF NEURAL NETWORKS FOR INTERPRETATION OF ION MOBILITY ANDX-RAY-FLUORESCENCE SPECTRA

Neural networks (NN) have been successfully used to interpret spectral data, and to derive qualitative and quantitative information from ion mobility spectrometry (IMS) and x-ray fluorescence (XRF). It is shown that components of complex mixtures of up to six aliphatic amines may be automatically identified by NN methods from their ion mobility spe ctra with reasonable accuracy. The ability of NN to identify compounds even under low signal-to-noise conditions of IMS spectra is demonstra ted. The use of XRF technique for quantitative determination of parts per million (ppm) amounts of mixtures of Re, Os, Ir and Pt in a polyet hylene matrix, which could not be done successfully by conventional me thods, was made possible by application of NN, with a root mean square error of a few ppm. The networks could be trained on a personal compu ter, in less than 10 min, from a surprisingly small data set of traini ng samples to perform these tasks.