Crown ether-modified electrodes for the simultaneous stripping voltammetric determination of Cd(II), Pb(II) and Cu(II)

This work describes the immobilization of 4-carboxybenzo-18-crown-6 (CB-18-crown-6) and 4-carboxybenzo-15-crown-5 (CB-15-crown-5) assisted by lysine on aryl diazonium salt monolayers anchored to the surface of graphite-epoxy composite electrodes (GEC), and their use for the simultaneous determinatio...

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Bibliographic Details
Authors: Serrano i Plana, Núria, González-Calabuig, Andreu, Valle, Manel del
Format: article
Status:Versión aceptada para publicación
Publication Date:2015
Country:España
Institution:Universidad de Barcelona
Repository:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/128281
Online Access:https://hdl.handle.net/2445/128281
Access Level:Open access
Keyword:Electroquímica
Ions metàl·lics
Xarxes neuronals (Informàtica)
Voltametria
Electrochemistry
Metal ions
Neural networks (Computer science)
Voltammetry
Description
Summary:This work describes the immobilization of 4-carboxybenzo-18-crown-6 (CB-18-crown-6) and 4-carboxybenzo-15-crown-5 (CB-15-crown-5) assisted by lysine on aryl diazonium salt monolayers anchored to the surface of graphite-epoxy composite electrodes (GEC), and their use for the simultaneous determination of Cd(II), Pb(II) and Cu(II) by differential pulse anodic stripping voltammetry (DPASV). These modified electrodes display a good repeatability and reproducibility with detection and quantification limits at levels of µg L(-1) (ppb), confirming their suitability for the determination of Cd(II), Pb(II) and Cu(II) ions in environmental samples. The overlapped nature of the multimetal stripping measurements was resolved by employing the two-sensor array CB-15-crown-5-GEC and CB-18-crown-6-GEC, since the metal complex selectivity exhibited by the considered ligands could add some discrimination power. For the processing of the voltammograms, Discrete Wavelet Transform and Causal Index were selected as preprocessing tools for data compression coupled with an artificial neural network for the modeling of the obtained responses, allowing the resolution of mixtures of these metals with good prediction of their concentrations (correlation with expected values for an external test subset better than 0.942).