Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results

In order to achieve the second-order advantage, second-order data per sample is usually required, e.g., kinetic-spectrophotometric data. In this study, instead of monitoring the time evolution of spectra (and collecting the kinetic-spectrophotometric data) replicate spectra are used to build a virtu...

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Detalles Bibliográficos
Autores principales: Mohseni, Naimeh, Bahram, Morteza, Olivieri, Alejandro César, Farhadi, Khalil
Lenguaje:Inglés
Publicado: Elsevier 2018
Materias:
MCR-ALS
Second-order Advantage
First-order Data
Standard Addition
Feasible Solutions
Acceso en línea:http://hdl.handle.net/2133/10501
http://hdl.handle.net/2133/10501
Aporte de:
Repositorio Hipermedial de la Universidad Nacional de Rosario (UNR) de Universidad Nacional de Rosario
id I15-R121-2133-10501
record_format dspace
institution Universidad Nacional de Rosario
institution_str I-15
repository_str R-121
collection Repositorio Hipermedial de la Universidad Nacional de Rosario (UNR)
language Inglés
orig_language_str_mv eng
topic MCR-ALS
Second-order Advantage
First-order Data
Standard Addition
Feasible Solutions
spellingShingle MCR-ALS
Second-order Advantage
First-order Data
Standard Addition
Feasible Solutions
Mohseni, Naimeh
Bahram, Morteza
Olivieri, Alejandro César
Farhadi, Khalil
Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
topic_facet MCR-ALS
Second-order Advantage
First-order Data
Standard Addition
Feasible Solutions
description In order to achieve the second-order advantage, second-order data per sample is usually required, e.g., kinetic-spectrophotometric data. In this study, instead of monitoring the time evolution of spectra (and collecting the kinetic-spectrophotometric data) replicate spectra are used to build a virtual second order data. This data matrix (replicate mode k) is rank deficient. Augmentation of these data with standard addition data [or standard sample(s)] will break the rank deficiency, making the quantification of the analyte of interest possible. The MCR-ALS algorithm was applied for the resolution and quantitation of the analyte in both simulated and experimental data sets. In order to evaluate the rotational ambiguityin the retrieved solutions, the MCR-BANDS algorithm was employed. It has been shown that the reliability of the quantitative results significantly depends on the amount of spectral overlap in the spectral region of occurrence of the compound of interest and the remaining constituent(s).
author Mohseni, Naimeh
Bahram, Morteza
Olivieri, Alejandro César
Farhadi, Khalil
author_facet Mohseni, Naimeh
Bahram, Morteza
Olivieri, Alejandro César
Farhadi, Khalil
author_sort Mohseni, Naimeh
title Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
title_short Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
title_full Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
title_fullStr Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
title_full_unstemmed Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
title_sort second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares : calculation of the feasible bands of results
publisher Elsevier
publishDate 2018
url http://hdl.handle.net/2133/10501
http://hdl.handle.net/2133/10501
work_keys_str_mv AT mohseninaimeh secondorderadvantageobtainedfromstandardadditionfirstorderinstrumentaldataandmultivariatecurveresolutionalternatingleastsquarescalculationofthefeasiblebandsofresults
AT bahrammorteza secondorderadvantageobtainedfromstandardadditionfirstorderinstrumentaldataandmultivariatecurveresolutionalternatingleastsquarescalculationofthefeasiblebandsofresults
AT olivierialejandrocesar secondorderadvantageobtainedfromstandardadditionfirstorderinstrumentaldataandmultivariatecurveresolutionalternatingleastsquarescalculationofthefeasiblebandsofresults
AT farhadikhalil secondorderadvantageobtainedfromstandardadditionfirstorderinstrumentaldataandmultivariatecurveresolutionalternatingleastsquarescalculationofthefeasiblebandsofresults
bdutipo_str Repositorios
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