Standard addition method with cumulative additions: Monte Carlo uncertainty evaluation
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
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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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 |
|
_version_ |
1803046753421754368 |