Multivariate curve resolution methods and the design of experiments

A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the question how a chemical experiment should be designed so that the solution ambiguity is as small as possible. Changes of the reaction conditions belong to t...

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Published inJournal of chemometrics Vol. 34; no. 2
Main Authors Sawall, Mathias, Kubis, Christoph, Schröder, Henning, Meinhardt, Denise, Selent, Detlef, Franke, Robert, Brächer, Alexander, Börner, Armin, Neymeyr, Klaus
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LanguageEnglish
Published Chichester Wiley Subscription Services, Inc 01.02.2020
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Abstract A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the question how a chemical experiment should be designed so that the solution ambiguity is as small as possible. Changes of the reaction conditions belong to the possible variations whereas for a fixed chemical reaction system, the pure component spectra appear to be unchangeable. The paper investigates and discusses the possibility to design a chemical experiment in a way that minimizes the ambiguity of the factorization. The analysis identifies regions of the spectra that are responsible for a small ambiguity. Certain sources are identified that are responsible for an increased ambiguity by means of an a posteriori analysis. This results in recommendations how to construct spectral measurements incorporating a reduced factorization ambiguity. Furthermore, lower bounds on an unavoidable base level of ambiguity are specified under the constraint of fixed reactants. The problem analysis is accompanied by investigations of several experimental data sets.
AbstractList A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the question how a chemical experiment should be designed so that the solution ambiguity is as small as possible. Changes of the reaction conditions belong to the possible variations whereas for a fixed chemical reaction system, the pure component spectra appear to be unchangeable.The paper investigates and discusses the possibility to design a chemical experiment in a way that minimizes the ambiguity of the factorization. The analysis identifies regions of the spectra that are responsible for a small ambiguity. Certain sources are identified that are responsible for an increased ambiguity by means of an a posteriori analysis. This results in recommendations how to construct spectral measurements incorporating a reduced factorization ambiguity. Furthermore, lower bounds on an unavoidable base level of ambiguity are specified under the constraint of fixed reactants. The problem analysis is accompanied by investigations of several experimental data sets.
A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the question how a chemical experiment should be designed so that the solution ambiguity is as small as possible. Changes of the reaction conditions belong to the possible variations whereas for a fixed chemical reaction system, the pure component spectra appear to be unchangeable. The paper investigates and discusses the possibility to design a chemical experiment in a way that minimizes the ambiguity of the factorization. The analysis identifies regions of the spectra that are responsible for a small ambiguity. Certain sources are identified that are responsible for an increased ambiguity by means of an a posteriori analysis. This results in recommendations how to construct spectral measurements incorporating a reduced factorization ambiguity. Furthermore, lower bounds on an unavoidable base level of ambiguity are specified under the constraint of fixed reactants. The problem analysis is accompanied by investigations of several experimental data sets.
Abstract A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the question how a chemical experiment should be designed so that the solution ambiguity is as small as possible. Changes of the reaction conditions belong to the possible variations whereas for a fixed chemical reaction system, the pure component spectra appear to be unchangeable. The paper investigates and discusses the possibility to design a chemical experiment in a way that minimizes the ambiguity of the factorization. The analysis identifies regions of the spectra that are responsible for a small ambiguity. Certain sources are identified that are responsible for an increased ambiguity by means of an a posteriori analysis. This results in recommendations how to construct spectral measurements incorporating a reduced factorization ambiguity. Furthermore, lower bounds on an unavoidable base level of ambiguity are specified under the constraint of fixed reactants. The problem analysis is accompanied by investigations of several experimental data sets.
Author Kubis, Christoph
Brächer, Alexander
Neymeyr, Klaus
Meinhardt, Denise
Sawall, Mathias
Schröder, Henning
Selent, Detlef
Franke, Robert
Börner, Armin
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Snippet A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the question how a...
Abstract A major problem of multivariate curve resolution methods is the underlying non‐uniqueness of the pure component decompositions. This raises the...
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wiley
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SubjectTerms Ambiguity
Chemical reactions
Design of experiments
Factorization
Lower bounds
Multivariate analysis
multivariate curve resolution
Organic chemistry
Spectra
Title Multivariate curve resolution methods and the design of experiments
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fcem.3159
https://www.proquest.com/docview/2350003443
Volume 34
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