A voltammetric electronic tongue for the resolution of ternary nitrophenol mixtures
González-Calabuig, Andreu (Universitat Autònoma de Barcelona. Departament de Química)
Cetó Alsedà, Xavier (University of South Australia)
Valle Zafra, Manuel del (Universitat Autònoma de Barcelona. Departament de Química)

Data:	2018
Resum:	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, 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.
Ajuts:	Ministerio de Economía y Competitividad CTQ2016-80170-P Ministerio de Economía y Competitividad CTQ2013-41577-P
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Artificial neural networks ; Electronic tongue ; Nitrophenols ; Persistent pollutants
Publicat a:	Sensors (Basel, Switzerland), Vol. 18, Issue 1 (January 2018) , art. 216, ISSN 1424-8220

DOI: 10.3390/s18010216
PMID: 29342848

11 p, 2.1 MB

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