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

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Autor(es): dc.contributorUniversidade Estadual de Campinas (UNICAMP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversitat Autònoma de Barcelona (UAB)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorde Oliveira, João Pedro Jenson-
Autor(es): dc.creatorBonet-San-Emeterio, Marta-
Autor(es): dc.creatorde Sá, Acelino Cardoso-
Autor(es): dc.creatorCetó, Xavier-
Autor(es): dc.creatorPaim, Leonardo Lataro-
Autor(es): dc.creatordel Valle, Manel-
Data de aceite: dc.date.accessioned2025-08-21T17:36:50Z-
Data de disponibilização: dc.date.available2025-08-21T17:36:50Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-09-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/chemosensors12090173-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/306525-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/306525-
Descrição: dc.descriptionThis 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.-
Descrição: dc.descriptionMinisterio de Ciencia e Innovación-
Descrição: dc.descriptionSchool of Electrical and Computer Engineering University of Campinas (UNICAMP), São Paulo-
Descrição: dc.descriptionDepartment of Energy Engineering São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionSensors and Biosensors Group Department of Chemistry Universitat Autònoma de Barcelona (UAB), Edifici CnBarcelona-
Descrição: dc.descriptionDepartment of Physics and Materials Science University of São Paulo (USP), São Paulo-
Descrição: dc.descriptionDepartment of Energy Engineering São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionMinisterio de Ciencia e Innovación: MCIN/AEI/10.1303/501100011033-
Descrição: dc.descriptionMinisterio de Ciencia e Innovación: PID2022-136709OB-C21-
Idioma: dc.languageen-
Relação: dc.relationChemosensors-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectartificial neural networks-
Palavras-chave: dc.subjectbiodiesel-
Palavras-chave: dc.subjectelectronic tongue-
Palavras-chave: dc.subjectglycerol-
Palavras-chave: dc.subjectnanoparticles modifiers-
Título: dc.titleResolution of Glycerol, Ethanol and Methanol Employing a Voltammetric Electronic Tongue-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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