Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration

Detalhes bibliográficos
Autor(a) principal: Campos,Alessandra T.
Data de Publicação: 2018
Outros Autores: Quintella,Cristina M., Meira,Marilena, Luna,Saionara
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Journal of the Brazilian Chemical Society (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532018000701367
Resumo: The present paper concerns to predict the sulfur concentration in biodiesel/diesel blends in the range of 5-100 mg L-1 of sulfur using spectrofluorimetry and partial least squares multivariate calibration (PLS). The calibration set consisted of samples with 10 and 20% (B10 and B20) of biodiesel in diesel with sulfur addition of 5-100 mg L-1. Two PLS models were constructed, one to predict the concentrations of sulfur in B10 blends that presented coefficient of determination (R2) values of 0.9867377 and 0.9801064, respectively, for calibration and validation. The other PLS model predict the concentrations of sulfur in B20 that presented R2 values of 0.9949219 and 0.8573713, respectively, for calibration and validation. Therefore, the models showed adequate efficiency to predict changes in the concentration of sulfur in biodiesel/diesel blends B10 and B20.
id SBQ-2_4a3c1d3ca8666b6edd092a40927a42db
oai_identifier_str oai:scielo:S0103-50532018000701367
network_acronym_str SBQ-2
network_name_str Journal of the Brazilian Chemical Society (Online)
repository_id_str
spelling Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibrationbiodieselmultivariate analysisspectrofluorimetrysulfurdieselThe present paper concerns to predict the sulfur concentration in biodiesel/diesel blends in the range of 5-100 mg L-1 of sulfur using spectrofluorimetry and partial least squares multivariate calibration (PLS). The calibration set consisted of samples with 10 and 20% (B10 and B20) of biodiesel in diesel with sulfur addition of 5-100 mg L-1. Two PLS models were constructed, one to predict the concentrations of sulfur in B10 blends that presented coefficient of determination (R2) values of 0.9867377 and 0.9801064, respectively, for calibration and validation. The other PLS model predict the concentrations of sulfur in B20 that presented R2 values of 0.9949219 and 0.8573713, respectively, for calibration and validation. Therefore, the models showed adequate efficiency to predict changes in the concentration of sulfur in biodiesel/diesel blends B10 and B20.Sociedade Brasileira de Química2018-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532018000701367Journal of the Brazilian Chemical Society v.29 n.7 2018reponame:Journal of the Brazilian Chemical Society (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.21577/0103-5053.20170236info:eu-repo/semantics/openAccessCampos,Alessandra T.Quintella,Cristina M.Meira,MarilenaLuna,Saionaraeng2018-06-20T00:00:00Zoai:scielo:S0103-50532018000701367Revistahttp://jbcs.sbq.org.brONGhttps://old.scielo.br/oai/scielo-oai.php||office@jbcs.sbq.org.br1678-47900103-5053opendoar:2018-06-20T00:00Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)false
dc.title.none.fl_str_mv Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
title Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
spellingShingle Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
Campos,Alessandra T.
biodiesel
multivariate analysis
spectrofluorimetry
sulfur
diesel
title_short Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
title_full Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
title_fullStr Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
title_full_unstemmed Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
title_sort Prediction of Sulfur Content in Diesel/Biodiesel Blends Using LED-Induced Fluorescence Associated with Multivariate Calibration
author Campos,Alessandra T.
author_facet Campos,Alessandra T.
Quintella,Cristina M.
Meira,Marilena
Luna,Saionara
author_role author
author2 Quintella,Cristina M.
Meira,Marilena
Luna,Saionara
author2_role author
author
author
dc.contributor.author.fl_str_mv Campos,Alessandra T.
Quintella,Cristina M.
Meira,Marilena
Luna,Saionara
dc.subject.por.fl_str_mv biodiesel
multivariate analysis
spectrofluorimetry
sulfur
diesel
topic biodiesel
multivariate analysis
spectrofluorimetry
sulfur
diesel
description The present paper concerns to predict the sulfur concentration in biodiesel/diesel blends in the range of 5-100 mg L-1 of sulfur using spectrofluorimetry and partial least squares multivariate calibration (PLS). The calibration set consisted of samples with 10 and 20% (B10 and B20) of biodiesel in diesel with sulfur addition of 5-100 mg L-1. Two PLS models were constructed, one to predict the concentrations of sulfur in B10 blends that presented coefficient of determination (R2) values of 0.9867377 and 0.9801064, respectively, for calibration and validation. The other PLS model predict the concentrations of sulfur in B20 that presented R2 values of 0.9949219 and 0.8573713, respectively, for calibration and validation. Therefore, the models showed adequate efficiency to predict changes in the concentration of sulfur in biodiesel/diesel blends B10 and B20.
publishDate 2018
dc.date.none.fl_str_mv 2018-07-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532018000701367
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532018000701367
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.21577/0103-5053.20170236
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Química
publisher.none.fl_str_mv Sociedade Brasileira de Química
dc.source.none.fl_str_mv Journal of the Brazilian Chemical Society v.29 n.7 2018
reponame:Journal of the Brazilian Chemical Society (Online)
instname:Sociedade Brasileira de Química (SBQ)
instacron:SBQ
instname_str Sociedade Brasileira de Química (SBQ)
instacron_str SBQ
institution SBQ
reponame_str Journal of the Brazilian Chemical Society (Online)
collection Journal of the Brazilian Chemical Society (Online)
repository.name.fl_str_mv Journal of the Brazilian Chemical Society (Online) - Sociedade Brasileira de Química (SBQ)
repository.mail.fl_str_mv ||office@jbcs.sbq.org.br
_version_ 1750318180830543872

Registros relacionados