A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures
AbstractThis 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
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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.
González-Calabuig A, Cetó X, del Valle M. A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures. Sensors. 2018; 18(1):216.Chicago/Turabian Style
González-Calabuig, Andreu; Cetó, Xavier; del Valle, Manel. 2018. "A Voltammetric Electronic Tongue for the Resolution of Ternary Nitrophenol Mixtures." Sensors 18, no. 1: 216.
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