Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(

Multivariate Curve Resolution (MCR)methods have been widely used to resolve the spectra (instrumental responses)and concentration profiles of the unknown constituents of chemical mixtures especially when no prior information is available about the nature and composition of these mixtures. Based on t...

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Authors: Zhang, Xin, Zhang, Zhuoyong, Tauler, Romà
Format: article
Status:Versión aceptada para publicación
Publication Date:2019
Country:España
Institution:Consejo Superior de Investigaciones Científicas (CSIC)
Repository:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/201809
Online Access:http://hdl.handle.net/10261/201809
Access Level:Open access
Keyword:MCR
Constraints
FACPACK
Multivariate curve resolution
MCR-BANDS
Rotation ambiguity
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network_name_str España
spelling Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method( Zhang, Xin Zhang, Zhuoyong Tauler, Romà MCR Constraints FACPACK Multivariate curve resolution MCR-BANDS Rotation ambiguity Multivariate Curve Resolution (MCR)methods have been widely used to resolve the spectra (instrumental responses)and concentration profiles of the unknown constituents of chemical mixtures especially when no prior information is available about the nature and composition of these mixtures. Based on the fulfillment of a bilinear model, like the multivariate extension of Beer's law, MCR solutions are affected by rotation ambiguity, which means that a range of feasible solutions can explain the observed data equally well fulfilling the same constraints. The MCR-BANDS method has been proposed to provide a measure of the extension of rotation ambiguity associated to a particular MCR feasible solution. In this work, the two extreme (maximum and minimum)feasible solutions obtained by the MCR-BANDS method are investigated and projected on to the area of feasible solution (AFS)obtained by other methods like the FACPACK method, and compared under the application of different constraints. In contrast to other methods that estimate the whole set of feasible solutions (i.e. the AFS), MCR-BANDS provides a simpler and flexible way to give an estimation of the extension of rotation ambiguity associated to a particular MCR solution (for instance using the MCR-ALS method)of systems with any number of components and under any type of constraints, in the concentration and spectral domains. © 2019 Elsevier B.V. Xin Zhang and Zhuoyong Zhang acknowledge the support received by Natural Science Foundation of China (21705112), and Youth Innovative Research Team of Capital Normal University (009175301300) (China). Roma Tauler acknowledges financial support from the Ministerio de Economia y Competividad (Spain) CTQ2015-66254-C2-1-P project and from Generalitat de Catalunya 2017 SGR 753 support to research groups grant. Peer reviewed Elsevier http://hdl.handle.net/10261/201809
title Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
spellingShingle Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
Zhang, Xin
MCR
Constraints
FACPACK
Multivariate curve resolution
MCR-BANDS
Rotation ambiguity
title_short Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
title_full Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
title_fullStr Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
title_full_unstemmed Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
title_sort Evaluation of the extension of rotation ambiguity associated to multivariate curve resolution solutions by the application of the MCR-BANDS method(
author Zhang, Xin
author_facet Zhang, Xin
Zhang, Zhuoyong
Tauler, Romà
author_role author
author2 Zhang, Zhuoyong
Tauler, Romà
author2_role author
author
topic MCR
Constraints
FACPACK
Multivariate curve resolution
MCR-BANDS
Rotation ambiguity
topic_facet MCR
Constraints
FACPACK
Multivariate curve resolution
MCR-BANDS
Rotation ambiguity
description Multivariate Curve Resolution (MCR)methods have been widely used to resolve the spectra (instrumental responses)and concentration profiles of the unknown constituents of chemical mixtures especially when no prior information is available about the nature and composition of these mixtures. Based on the fulfillment of a bilinear model, like the multivariate extension of Beer's law, MCR solutions are affected by rotation ambiguity, which means that a range of feasible solutions can explain the observed data equally well fulfilling the same constraints. The MCR-BANDS method has been proposed to provide a measure of the extension of rotation ambiguity associated to a particular MCR feasible solution. In this work, the two extreme (maximum and minimum)feasible solutions obtained by the MCR-BANDS method are investigated and projected on to the area of feasible solution (AFS)obtained by other methods like the FACPACK method, and compared under the application of different constraints. In contrast to other methods that estimate the whole set of feasible solutions (i.e. the AFS), MCR-BANDS provides a simpler and flexible way to give an estimation of the extension of rotation ambiguity associated to a particular MCR solution (for instance using the MCR-ALS method)of systems with any number of components and under any type of constraints, in the concentration and spectral domains. © 2019 Elsevier B.V.
publishDate 2019
format article
status_str acceptedVersion
url http://hdl.handle.net/10261/201809
eu_rights_str_mv openAccess
publisher Elsevier
institution Consejo Superior de Investigaciones Científicas (CSIC)
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
_version_ 1878441784295555072
publishDateSort 2019
author_browse Tauler, Romà
Zhang, Xin
Zhang, Zhuoyong
publisherStr Elsevier
score 6,9303427

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