MULTIVARIATE RESOLUTION OF RANK-DEFICIENT NIR DATA FROM THE REACTION OF CURING EPOXY RESINS, USING THE RANK AUGMENTATION STRATEGY AND SIMPLISMA APPROACH

M. GARRIDO; I. LÁZARO; M. S. LARRECHI; F. X. RIUS

Ústica

Congreso; V COLLOQUIUM CHEMIOMETRICUM MEDITERRANEUM; 2003

Sociedad Italiana de Quimiometría

<!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman";} @page Section1 {size:612.0pt 792.0pt; margin:70.85pt 3.0cm 70.85pt 3.0cm; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} --> Multivariate curve resolution (MCR) methods, specifically alternating least squares (ALS), applied to NIR data provides the concentration profiles and the spectra of all species involved in the reaction of curing epoxy resins. The model reaction between phenyl glycidyl ether (PGE) and aniline has been studied at 95 ºC. At working conditions curing reaction takes place in two steps. Five different process runs starting from different initial conditions, by modifying PGE/aniline molar ratio, are designed (2:1, 1.75:1, 1.5:1, 1.25:1, 1:1). The processes are monitored in situ by near-infrared spectroscopy and the spectra have been recordered in the range between 1100 and 2500 nm, every five minutes. The typical rank-deficiency of data set obtained by monitoring chemical reactions are succesfully eliminated by analysing an augmented column-wise matrix which contains the five different process runs. The initial estimations of spectra required by MCR-ALS adjusting are given by a SIMPLISMA approach. The obtained spectra and concentration profiles represent adequately the studied system. The similarity coefficients (r), between the recovered spectra and the pure species spectra are: PGE (r = 0.998), aniline (r = 0.994) and terciary amine (r = 0.999). Also, the maximum and minimum band boundaries of feasible solutions corresponding to the species profiles estimated is calculated.