Resolution of Glycerol, Ethanol and Methanol Employing a Voltammetric Electronic Tongue

被引:0
|
作者
de Oliveira, Joao Pedro Jenson [1 ,2 ,3 ]
Bonet-San-Emeterio, Marta [3 ]
de Sa, Acelino Cardoso [4 ]
Ceto, Xavier [3 ]
Paim, Leonardo Lataro [2 ]
del Valle, Manel [3 ]
机构
[1] Univ Campinas UNICAMP, Sch Elect & Comp Engn, BR-13083852 Campinas, SP, Brazil
[2] Sao Paulo State Univ UNESP, Dept Energy Engn, BR-19274000 Sao Paulo, Brazil
[3] Univ Autonoma Barcelona UAB, Dept Chem, Sensors & Biosensors Grp, Edif Cn, Barcelona 08193, Spain
[4] Univ Sao Paulo, Dept Phys & Mat Sci, BR-13566590 Sao Carlos, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
electronic tongue; nanoparticles modifiers; glycerol; biodiesel; artificial neural networks; ELECTROCHEMICAL SENSOR; ELECTROOXIDATION; COPPER; TRENDS;
D O I
10.3390/chemosensors12090173
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
This paper reports the use of nanoparticles (NPs)-modified voltammetric sensors for the rapid determination of glycerol in the presence of ethanol and methanol, which are used in the transesterification reaction of biodiesel production. Two different modified electrodes have been prepared to form the electronic tongue (ET): copper hexacyanoferrate NPs obtained by chemical synthesis and mixed into graphite/epoxy (GEC) electrode, and nickel hydroxide NPs electrodeposited in reduced graphene oxide onto a GEC electrode. The response characteristics of these electrodes were first evaluated by building the respective calibration against glycerol, ethanol, and methanol. The electrodes demonstrated good stability during their analytical characterization, while principal component analysis confirmed the differentiated response against the different alcohols. Finally, the quantification of mixtures of these substances was achieved by a genetic algorithm-artificial neural networks (GA-ANNs) model, showing satisfactory agreement between expected and obtained values.
引用
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页数:12
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