Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation

Detalhes bibliográficos
Autor(a) principal: Dadamos, Tony R. L. [UNESP]
Data de Publicação: 2019
Outros Autores: Damaceno, Airton J. [UNESP], Fertonani, Fernando L. [UNESP], Bettencourt da Silva, Ricardo J. N.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.aca.2019.02.002
http://hdl.handle.net/11449/184406
Resumo: The cumulative standard addition method allows the calibration of an instrument affected by matrix effects when a small sample volume is available. Recently, it was developed and validated a metrologically sound procedure to estimate the uncertainty of these measurements based on the modelling of the uncertainty of the extrapolation of the calibration curve by the linear least squares regression model. However, this procedure is only applicable when the uncertainty of cumulative sample dilutions and analyte mass additions are negligible given the uncertainty of the total solution volume (v) times the instrumental signal (1) (i.e. v.I). This work developed a measurement uncertainty model, not limited by this assumption of the quality of calibrators preparation, based on Monte Carlo simulations. This method was successfully applied to the voltammetric measurements of uric acid in human serum, using a working nanocarbon electrode modified with Cu-nanocarbon-lignin, since the uncertainty model adapts to the uncertainty of cumulative volume additions. The validated procedure was checked through the analysis of spiked physiological serum samples and human serum samples, by assessing the metrological compatibility between estimated and reference values. The measurements are reported with an expanded uncertainty not larger than a target value of 0.56 mg dL(-1). The used spreadsheet is made available as supplementary material. (C) 2019 Elsevier B.V. All rights reserved.
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spelling Standard addition method with cumulative additions: Monte Carlo uncertainty evaluationCumulative standard additionsUncertaintyMonte Carlo methodUric acidAmperometryThe cumulative standard addition method allows the calibration of an instrument affected by matrix effects when a small sample volume is available. Recently, it was developed and validated a metrologically sound procedure to estimate the uncertainty of these measurements based on the modelling of the uncertainty of the extrapolation of the calibration curve by the linear least squares regression model. However, this procedure is only applicable when the uncertainty of cumulative sample dilutions and analyte mass additions are negligible given the uncertainty of the total solution volume (v) times the instrumental signal (1) (i.e. v.I). This work developed a measurement uncertainty model, not limited by this assumption of the quality of calibrators preparation, based on Monte Carlo simulations. This method was successfully applied to the voltammetric measurements of uric acid in human serum, using a working nanocarbon electrode modified with Cu-nanocarbon-lignin, since the uncertainty model adapts to the uncertainty of cumulative volume additions. The validated procedure was checked through the analysis of spiked physiological serum samples and human serum samples, by assessing the metrological compatibility between estimated and reference values. The measurements are reported with an expanded uncertainty not larger than a target value of 0.56 mg dL(-1). The used spreadsheet is made available as supplementary material. (C) 2019 Elsevier B.V. All rights reserved.Univ Estadual Paulista, Inst Biociencias Letras & Ciencias Exatas, Campus Sao Jose do Rio Preto,R Cristovao Colombo, Sao Jose Do Rio Preto, SP, BrazilUniv Lisbon, Fac Ciencias, Ctr Quim Estrutural, P-1749016 Lisbon, PortugalUniv Estadual Paulista, Inst Biociencias Letras & Ciencias Exatas, Campus Sao Jose do Rio Preto,R Cristovao Colombo, Sao Jose Do Rio Preto, SP, BrazilElsevier B.V.Universidade Estadual Paulista (Unesp)Univ LisbonDadamos, Tony R. L. [UNESP]Damaceno, Airton J. [UNESP]Fertonani, Fernando L. [UNESP]Bettencourt da Silva, Ricardo J. N.2019-10-04T11:57:30Z2019-10-04T11:57:30Z2019-06-20info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article28-35http://dx.doi.org/10.1016/j.aca.2019.02.002Analytica Chimica Acta. Amsterdam: Elsevier Science Bv, v. 1059, p. 28-35, 2019.0003-2670http://hdl.handle.net/11449/18440610.1016/j.aca.2019.02.002WOS:000460895700003Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengAnalytica Chimica Actainfo:eu-repo/semantics/openAccess2021-10-23T03:22:14Zoai:repositorio.unesp.br:11449/184406Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T03:22:14Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
title Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
spellingShingle Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
Dadamos, Tony R. L. [UNESP]
Cumulative standard additions
Uncertainty
Monte Carlo method
Uric acid
Amperometry
title_short Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
title_full Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
title_fullStr Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
title_full_unstemmed Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
title_sort Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
author Dadamos, Tony R. L. [UNESP]
author_facet Dadamos, Tony R. L. [UNESP]
Damaceno, Airton J. [UNESP]
Fertonani, Fernando L. [UNESP]
Bettencourt da Silva, Ricardo J. N.
author_role author
author2 Damaceno, Airton J. [UNESP]
Fertonani, Fernando L. [UNESP]
Bettencourt da Silva, Ricardo J. N.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Univ Lisbon
dc.contributor.author.fl_str_mv Dadamos, Tony R. L. [UNESP]
Damaceno, Airton J. [UNESP]
Fertonani, Fernando L. [UNESP]
Bettencourt da Silva, Ricardo J. N.
dc.subject.por.fl_str_mv Cumulative standard additions
Uncertainty
Monte Carlo method
Uric acid
Amperometry
topic Cumulative standard additions
Uncertainty
Monte Carlo method
Uric acid
Amperometry
description The cumulative standard addition method allows the calibration of an instrument affected by matrix effects when a small sample volume is available. Recently, it was developed and validated a metrologically sound procedure to estimate the uncertainty of these measurements based on the modelling of the uncertainty of the extrapolation of the calibration curve by the linear least squares regression model. However, this procedure is only applicable when the uncertainty of cumulative sample dilutions and analyte mass additions are negligible given the uncertainty of the total solution volume (v) times the instrumental signal (1) (i.e. v.I). This work developed a measurement uncertainty model, not limited by this assumption of the quality of calibrators preparation, based on Monte Carlo simulations. This method was successfully applied to the voltammetric measurements of uric acid in human serum, using a working nanocarbon electrode modified with Cu-nanocarbon-lignin, since the uncertainty model adapts to the uncertainty of cumulative volume additions. The validated procedure was checked through the analysis of spiked physiological serum samples and human serum samples, by assessing the metrological compatibility between estimated and reference values. The measurements are reported with an expanded uncertainty not larger than a target value of 0.56 mg dL(-1). The used spreadsheet is made available as supplementary material. (C) 2019 Elsevier B.V. All rights reserved.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-04T11:57:30Z
2019-10-04T11:57:30Z
2019-06-20
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.aca.2019.02.002
Analytica Chimica Acta. Amsterdam: Elsevier Science Bv, v. 1059, p. 28-35, 2019.
0003-2670
http://hdl.handle.net/11449/184406
10.1016/j.aca.2019.02.002
WOS:000460895700003
url http://dx.doi.org/10.1016/j.aca.2019.02.002
http://hdl.handle.net/11449/184406
identifier_str_mv Analytica Chimica Acta. Amsterdam: Elsevier Science Bv, v. 1059, p. 28-35, 2019.
0003-2670
10.1016/j.aca.2019.02.002
WOS:000460895700003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Analytica Chimica Acta
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 28-35
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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