Quantitative Estimation of COD Values from an Array of Metal Nanoparticle Modified Electrodes and Artificial Neural Networks †
Wang, Qing (Universitat Autònoma de Barcelona. Departament de Química)
Cetó Alsedà, Xavier (Universitat Autònoma de Barcelona. Departament de Química)
Valle Zafra, Manuel del (Universitat Autònoma de Barcelona. Departament de Química)

Data:	2022
Resum:	Water quality monitoring has become critical in modern societies in multiple areas and at different stages. In this regard, chemical oxygen demand (COD) has become a key index in water testing, as it readily allows the determination of its overall quality and the presence of organic contaminants. However, conventional COD determination presents several drawbacks in view of the use of toxic reagents and possible interferences. The electrochemical determination of COD can be an alternative with many advantages, especially if using an array of sensors. Herein, the use of an electronic tongue (ET) for the estimation of COD was explored. The proposed ET was formed by an array of five voltammetric electrodes modified with different metal nanoparticles. An artificial neural network (ANN) model was built based on the responses of the array towards glucose and glycine as standards. This model was then used with real and spiked water samples, and the results compared to the electrochemical calibration and the commercial COD colorimetric methods. While the COD values of the real samples were low and outside the range of the ANN model, a satisfactory prediction for the spiked samples was achieved, showing a good agreement with the reference colorimetric method, that was better than the performance of the conventional electrochemical calibration method.
Ajuts:	Agencia Estatal de Investigación PID2019-107102RB-C21
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:	Chemical oxygen demand ; Wastewater ; Metal nanoparticles ; Voltammetric sensors ; Artificial neural networks ; Electronic tongue
Publicat a:	Chemosensors, Vol. 10, Issue 12 (December 2022) , art. 504, ISSN 2227-9040

DOI: 10.3390/chemosensors10120504

16 p, 4.8 MB

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