Аннотации:
This work is devoted to the new approach for the description of voltammograms with overlapped peaks of individual analytes. The prediction of individual concentration is achieved by decomposition of entire voltammogram using radial basis function approach followed by fitting the curves using linear model and artificial neural net. The analytical case study is the direct determination of three phenolic antioxidants, i.e., tert-butylhydroquinone, 3-tert-butyl-4-hydroxyanisole and propyl gallate. The artificial mixtures contained their binary and ternary solutions in the range of concentration from 0.25 to 1.00 mM. The results of decomposition were first checked on similarity of recorded and reconstructed voltammograms followed by determination of individual concentrations by least square method (linear model fitting) and feed-forward artificial net consisting of two hidden layers with 7 and 3 neurons. As was shown, the relative standard deviation of the concentration estimates of 0.03-0.07 can be obtained. The results of prediction were validated using an additional data set with the concentrations of the analytes not used in the fitting procedures. © 2014 Published by Elsevier Ltd.
