• Title of article

    Sequential injection system with higher dimensional electrochemical sensor signals: Part 1. Voltammetric e-tongue for the determination of oxidizable compounds

  • Author/Authors

    Gutés، نويسنده , , A. and Céspedes، نويسنده , , F. and Alegret، نويسنده , , S. Ortega del Valle، نويسنده , , M.، نويسنده ,

  • Issue Information
    ماهنامه با شماره پیاپی سال 2005
  • Pages
    10
  • From page
    1187
  • To page
    1196
  • Abstract
    A sequential injection analysis (SIA) system was developed with the aim of obtaining an automatic and versatile way to prepare standards needed in the study of systems with higher dimensional sensor signals. To illustrate this, different analytical techniques were used in determinations of several analytes. Automated potentiometric calibrations of different potentiometric sensors, with and without interference, were carried out. Useful determinations of selectivity coefficients with two degrees of freedom were obtained. Simultaneous voltammetric determinations have also been done. Firstly, simultaneous determinations of lead and cadmium, using epoxy-graphite composite as the working electrode, have enabled a separate calibration for each metal to be obtained. Next, a voltammetric electronic tongue was designed and applied to the determination of oxidizable species. The use of artificial neural networks has solved the overlapped signal of ascorbic acid, 4-aminophenol and 4-acetamidophenol (paracetamol). A set of 63 data points was prepared automatically and has facilitated the training of an electronic tongue for these three analytes. Accurate predictions of test solutions, in the range of 12–410 μM for ascorbic acid, 17–530 μM for 4-aminophenol and 10–420 μM for paracetamol, have been achieved with RMSEs lower than 0.10 μM.
  • Keywords
    Sequential injection analysis , Artificial neural networks , Potentiometric sensors , Electronic tongue , Voltammetric sensors
  • Journal title
    Talanta
  • Serial Year
    2005
  • Journal title
    Talanta
  • Record number

    1674417