Principal component analysis of FT-IR spectra for cationic photopolymerization of mixtures of two monomers
Principal component analysis (PCA) is used to analyze real-time FT-TR spectral data for cationic photopolymerizations of tri(ethylene glycol) methyl vinyl ether (TEGMVE), 3,4-epoxycyclohexylmetliyl-3',4'-epoxycyclohexane carboxylate (ECH) and their mixtures. PCA performed on different parts of the very large data set is able to extract information on subtle effects occurring in the polymerization reactions. Many of these effects are not readily apparent even from a detailed analysis of the raw spectra. The objectives of this paper are two-fold: to present important new results on the photopolymerization reaction between ECH and TEGMVE, and to illustrate the use of general PCA models to uncover subtle reaction effects occurring in time evolving reaction spectra. PCA models of the overall data set for different compositions are able to clearly separate compositional effects from time varying conversion effects. Multivariate curve resolution (MCR) on individual runs was found to provide no additional information due to rotational and intensity ambiguities that remain in spite of the imposition of different constraints. For PCA models built on runs with the same initial monomer composition ratios, loading plots and contribution plots are used to obtain a much clearer interpretation of the reactions involved in the polymerization. Furthermore, important structural differences occurring among "replicate" runs are uncovered providing further insight into the reaction mechanisms, and into reasons for batch-to-batch inconsistencies that may occur in a manufacturing process. (C) 2004 Elsevier B.V. All rights reserved.
principal component analysis photopolymerization multivariate curve resolution