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Sensors 2018, 18(1), 216;

A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures

Sensors and Biosensors Group, Department of Chemistry, Universitat Autònoma de Barcelona, Edifici Cn, 08193 Bellaterra, Barcelona, Spain
Future Industries Institute, University of South Australia, SA 5095 Adelaide, Australia
Author to whom correspondence should be addressed.
Received: 15 December 2017 / Revised: 10 January 2018 / Accepted: 11 January 2018 / Published: 13 January 2018
(This article belongs to the Special Issue Electronic Tongues and Electronic Noses)
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This work reports the applicability of a voltammetric sensor array able to quantify the content of 2,4-dinitrophenol, 4-nitrophenol, and picric acid in artificial samples using the electronic tongue (ET) principles. The ET is based on cyclic voltammetry signals, obtained from an array of metal disk electrodes and a graphite epoxy composite electrode, compressed using discrete wavelet transform with chemometric tools such as artificial neural networks (ANNs). ANNs were employed to build the quantitative prediction model. In this manner, a set of standards based on a full factorial design, ranging from 0 to 300 mg·L−1, was prepared to build the model; afterward, the model was validated with a completely independent set of standards. The model successfully predicted the concentration of the three considered phenols with a normalized root mean square error of 0.030 and 0.076 for the training and test subsets, respectively, and r ≥ 0.948. View Full-Text
Keywords: electronic tongue; artificial neural networks; persistent pollutants; nitrophenols electronic tongue; artificial neural networks; persistent pollutants; nitrophenols

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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González-Calabuig, A.; Cetó, X.; del Valle, M. A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures. Sensors 2018, 18, 216.

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