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Focus on the potential of hybrid hard‐ and soft‐MCR–ALS in time resolved spectroscopy
Author(s) -
Blanchet Lionel,
Ruckebusch Cyril,
Huvenne JeanPierre,
de Juan Anna
Publication year - 2008
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.1144
Subject(s) - femtosecond , multivariate statistics , focus (optics) , spectroscopy , field (mathematics) , least squares function approximation , resolution (logic) , biological system , rank (graph theory) , kinetic energy , chemistry , computer science , algorithm , artificial intelligence , machine learning , optics , physics , statistics , mathematics , laser , quantum mechanics , combinatorics , estimator , pure mathematics , biology
This work presents some strategies to obtain time‐dependent concentration profiles and spectra from time resolved spectroscopic data of complex systems. Multivariate curve resolution–alternating least squares (MCR–ALS) has been of particular interest in this field because of the possibility to implement simultaneously soft‐modeling constraints and kinetic models on a multibatch resolution. This approach allows circumventing a rank deficiency inherent to time resolved difference data, even in presence of interferent species. The methodology is illustrated using examples from femtosecond photochemistry and biochemistry. Copyright © 2008 John Wiley & Sons, Ltd.