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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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González-Calabuig, Andreu
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (6/6 displayed)
- 2018Bioelectronic tongue using MIP sensors for the resolution of volatile phenolic compounds
- 2018Multivariate Determination of Total Sugar Content and Ethanol in Bioethanol Production Using Carbon Electrodes Modified with MWCNT/MeOOH and Chemometric Data Treatment
- 2016Analysis of Amino Acid Mixtures by Voltammetric Electronic Tongues and Artificial Neural Networks
- 2016Simultaneous Voltammetric Determination of Heavy Metals by Use of Crown Ether-modified Electrodes and Chemometricscitations
- 2016Resolution of galactose, glucose, xylose and mannose in sugarcane bagasse employing a voltammetric electronic tongue formed by metals oxy-hydroxide/MWCNT modified electrodescitations
- 2015Crown ether-modified electrodes for the simultaneous stripping voltammetric determination of Cd(II), Pb(II) and Cu(II)citations
Places of action
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article
Multivariate Determination of Total Sugar Content and Ethanol in Bioethanol Production Using Carbon Electrodes Modified with MWCNT/MeOOH and Chemometric Data Treatment
Abstract
© 2018 Wiley-VCH Verlag GmbH&Co. KGaA, Weinheim This work reports the characterization and application of a voltammetric electronic tongue using an array of glassy carbon electrodes modified with multi-walled carbon nanotubes containing metal (Pd, Au, Cu) and oxy-hydroxide nanoparticles (MetalsOOH of Ni, Co) towards the determination of total sugar content in products related with sugarcane-bioethanol production. The prediction model based on Artificial Neural Networks (ANN) has given satisfactory results for the carbohydrate sum and the obtained response had shown an adequate accuracy. Voltammetric data was first adapted for the computation using the Fast Fourier transform, and results from the electronic tongue approach were compared with use of different electrodes alone. Final performance was better using uniquely the Ni oxy-hydroxide modified electrode, especially in the quantification of ethanol, a side-effect of counter-balancing its interference.