Multivariate resolution of rank-deficient near-infrared spectroscopy data from the reaction of curing epoxy resins using the rank augmentation strategy and multivariate curve resolution alternating least squares approach

A model of the curing reaction between phenyl glycidyl ether (PGE) and aniline as the curing agent was studied isothermally at 95 °C and monitored in situ by near-infrared spectroscopy (NIR). The spectra were recorded every 5 min. The ubiquitous problem of rank deficiency in reaction network systems was solved by assembling an augmented column-wise matrix containing five process runs from different initial conditions. The data were analyzed using a two-way multivariate curve resolution alternating least squares method (MCR-ALS). Initial estimates of spectra required by MCR-ALS were given by a SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) approach. The reactants, product and intermediate spectra were successfully resolved and the concentration profiles properly represented the system studied. The performance of the model was evaluated by two parameters: ALS lack of fit (lof=0.88%) and explained variance (R²=99.99%). To validate the MCR-ALS results, the similarity coefficients (r) between the recovered spectra and the pure species spectra were calculated. These were: PGE (r=0.998), aniline (r=0.994) and tertiary amine (r=0.999).