Simultaneous and automated monitoring of the multimetal biosorption processes by potentiometric sensor array and artificial neural network
Autor: | Deivy Wilson, César Valderrama, Antonio Florido, M. del Valle, Salvador Alegret |
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Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Enginyeria Química, Universitat Politècnica de Catalunya. SETRI - Grup de Tècniques de Separació i Tractament de Residus Industrials |
Rok vydání: | 2013 |
Předmět: |
Electronic tongue
Grape stalk wastes Analytical chemistry Industrial Waste Wine Analytical Chemistry Ion Metal Enginyeria química [Àrees temàtiques de la UPC] Adsorption Plasticizers Metals Heavy Ion-selective electrodes Food Industry Potentiometric sensor Vitis Polyvinyl Chloride Electrodes Metalls pesants -- Absorció i adsorció Fourier Analysis Ionophores Plant Stems Chemistry Biosorption On-line monitoring Membranes Artificial Heavy metals -- Absorption and adsorption visual_art Electrode Potentiometry Fourier transform visual_art.visual_art_medium Calcium Environmental Pollutants Neural Networks Computer Ternary operation Heavy metals sorption Environmental Monitoring |
Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya Universitat Jaume I |
ISSN: | 0039-9140 |
Popis: | In this communication, a new methodology for the simultaneous and automated monitoring of biosorption processes of multimetal mixtures of polluting heavy metals on vegetable wastes based on flow-injection potentiometry (FIP) and electronic tongue detection (ET) is presented. A fixed-bed column filled with grape stalks from wine industry wastes is used as the biosorption setup to remove the metal mixtures from the influent solution. The monitoring system consists in a computer controlled-FIP prototype with the ET based on an array of 9 flow-through ion-selective electrodes and electrodes with generic response to divalent ions placed in series, plus an artificial neural network response model. The cross-response to Cu(2+), Cd(2+), Zn(2+), Pb(2+) and Ca(2+) (as target ions) is used, and only when dynamic treatment of the kinetic components of the transient signal is incorporated, a correct operation of the system is achieved. For this purpose, the FIA peaks are transformed via use of Fourier treatment, and selected coefficients are used to feed an artificial neural network response model. Real-time monitoring of different binary (Cu(2+)/ Pb(2+)), (Cu(2+)/ Zn(2+)) and ternary mixtures (Cu(2+)/ Pb(2+)/ Zn(2+)), (Cu(2+)/ Zn(2+)/ Cd(2+)), simultaneous to the release of Ca(2+) in the effluent solution, are achieved satisfactorily using the reported system, obtaining the corresponding breakthrough curves, and showing the ion-exchange mechanism among the different metals. Analytical performance is verified against conventional spectroscopic techniques, with good concordance of the obtained breakthrough curves and modeled adsorption parameters. |
Databáze: | OpenAIRE |
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