Use of Sequential Injection Analysis to construct a Potentiometric Electronic Tongue: Application to the Multidetermination of Heavy Metals

摘要

An automated potentiometric electronic tongue (ET) was developed for the quantitative determination of heavy metal mixtures. The Sequential Injection Analysis (SIA) technique was used in order to automate the obtaining of input data, and the combined response was modeled by means of Artificial Neural Networks (ANN). The sensor array was formed by four sensors: two based on chalcogenide glasses Cd sensor and Cu sensor, and the rest on poly(vinyl chloride) membranes Pb sensor and Zn sensor. The Ion Selective Electrode (ISE) sensors were first characterized with respect to one and two analytes, by means of high-dimensionality calibrations, thanks to the use of the automated flow system; this characterization enabled an interference study of great practical utility. To take profit of the dynamic nature of the sensor's response, the kinetic profile of each sensor was compacted by Fast Fourier Transform (FFT) and the extracted coefficients were used as inputs for the ANN in the multidetermination applications. In order to identify the ANN which provided the best model of the electrode responses, some of the network parameters were optimized. Finally analyses were performed employing synthetic samples and water samples of the river Ebro; obtained results were compared with reference methods.