The effect of data matrix augmentation and constraints in extended multivariate curve resolution–alternating least squares

The reliability of results obtained by multivariate curve resolution (MCR) methods is strongly dependent on the absence or presence of a small degree of rotational ambiguity associated to them. In this work, the effect of rotational ambiguities on the profiles resolved by MCR methods is examined in...

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Detalles Bibliográficos
Autores: Olivieri, Alejandro Cesar, Tauler, Romà
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/63828
Acceso en línea:http://hdl.handle.net/11336/63828
Access Level:acceso abierto
Palabra clave:Data Matrix Augmentation
Mixture Analysis with Extended Mcr
Multivariate Curve Resolution
Rotational Ambiguity And Feasible Solutions
https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
Descripción
Sumario:The reliability of results obtained by multivariate curve resolution (MCR) methods is strongly dependent on the absence or presence of a small degree of rotational ambiguity associated to them. In this work, the effect of rotational ambiguities on the profiles resolved by MCR methods is examined in detail for cases of interest to analytical chemistry, where a number of calibration samples are usually prepared containing analyte standards, while test samples may contain additional uncalibrated constituents. These multiple chemical data sets having common constituents are simultaneously analyzed using matrix augmentation strategies. In these cases, conditions for better resolution and improved profiles are more easily achieved. To evaluate the extension of rotational ambiguities and to quantify their reduction after matrix augmentation, we applied the MCR-BANDS procedure. Results obtained by the application of this procedure confirmed that the simultaneous analysis of multiple data sets decreased considerably the extension of rotational ambiguities compared with those obtained when only a single data set is analyzed. Simulated and experimental data sets of interest to second-order analytical calibration are discussed.