Journal
SENSORS AND ACTUATORS B-CHEMICAL
Volume 222, Issue -, Pages 645-653Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2015.08.088
Keywords
Electronic tongue; Carbohydrates; Artificial neural network; Multi-walled carbon nanotubes; Metal nanoparticles; Second generation ethanol
Funding
- FAPESP [2011/19289-5, BEPE 2014/15557-3, 2012/00258-5]
- Spanish ministry MINECO [CTQ2013-41577-P]
- Research Executive Agency (REA) of the European Union [PITN-GA-2010-264772]
- Catalonia program ICREA Academia
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Second generation ethanol is produced from the carbohydrates released from the cell wall of bagasse and straw of sugarcane. The objective of this work is the characterization and application of a voltammetric electronic tongue using an array of glassy carbon electrodes modified with multi-walled carbon nanotubes containing metal (Paladium, Gold, Copper, Nickel and Cobalt) oxy-hydroxide nanoparticles (GCE/MWCNT/MetalsOOH) towards a simpler analysis of carbohydrates (glucose, xylose, galactose and mannose). The final architecture of the back-propagation Artificial Neural Network (ANN) model had 36 input neurons and a hidden layer with 5 neurons. The ANN based prediction model has provided satisfactory concentrations for all carbohydrates; the obtained response had a maximum NRMSE of 12.4% with a maximum deviation of slopes in the obtained vs. expected comparison graph of 15%. For all species, the comparison correlation coefficient was of r > 0.99 for the training subset and of r > 0.96 for the test subset. (C) 2015 Elsevier B.V. All rights reserved.
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