Simultaneous determination of phenol isomers in binary mixtures by differential pulse voltammetry using carbon fibre electrode and neural network with pruning as a multivariate calibration tool

Neural networks with pruning were applied to model overlapped peaks obtaine d in differential pulse voltammetry (DPV) with modified carbon fibre electr ode with TiO2 of binary mixtures of catechol and hydroquinone. The best con dition for electrochemical response was obtained with 0.05 mol l(-1) Tris-H Cl buffer at pH 6.0 and T-800 sized carbon fibre electrode. Initially the v oltammograms were processed using Fourier transform filter and principal co mponent analysis (PCA) to noise reduction and data compression, respectivel y. The scores of these principal components were the input into the neural network and the optimal brain surgeon (OBS) was the procedure employed for pruning the neural network. The results obtained with pruning procedure wer e slightly better in relation to hydroquinone in comparison to the PLS1 and PLS2. However, the similar errors were obtained to catechol when using PLS or neural networks models. Using neural networks with pruning was possible to determine catechol and hydroquinone by DPV using carbon fibre electrode , in concentration range of 1.0 x 10(-4) up to 6.0x 10(-4) mol l(-1) with r oot mean square errors of predictions (%RMSEP) of 7.42 and 8.02, respective ly. The good results show that the proposed methodology is a good alternati ve to simultaneous determination of catechol and hydroquinone in binary mix tures. (C) 2000 Elsevier Science B.V. All rights reserved.