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Model‐free multivariate curve resolution combined with model‐based kinetics: algorithm and applications
Author(s) -
Sawall Mathias,
Börner Armin,
Kubis Christoph,
Selent Detlef,
Ludwig Ralf,
Neymeyr Klaus
Publication year - 2012
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2463
Subject(s) - multivariate statistics , kinetic energy , resolution (logic) , uniqueness , curve fitting , algorithm , consistency (knowledge bases) , range (aeronautics) , biological system , mathematics , computer science , materials science , statistics , physics , mathematical analysis , artificial intelligence , quantum mechanics , composite material , biology
Multivariate curve resolution techniques are powerful tools to extract from sequences of spectra of a chemical reaction system the number of independent chemical components, their associated spectra, and the concentration profiles in time. Usually, these solutions are not unique because of the so‐called rotational ambiguity. In the present work, we reduce the non‐uniqueness by enforcing the consistency of the computed concentration profiles with a given kinetic model. Traditionally, the kinetic modeling is realized in a separate step, which follows the multivariate curve resolution procedure. In contrast to this, we consider a hybrid approach that combines the model‐free curve resolution technique with the model‐based kinetic modeling in an overall optimization. For a two‐component model problem, the range of possible solutions is analyzed, and its reduction to a single, unique solution by means of the hybrid kinetic modeling is shown. The algorithm reduces the rotational ambiguity and improves the quality of the kinetic fitting. Numerical results are also presented for a multi‐component catalytic reaction system that obeys the Michaelis–Menten kinetics. Copyright © 2012 John Wiley & Sons, Ltd.