Resolution of two-way data from on-line Fourier-transform Raman spectroscopic monitoring of the anionic dispersion polymerization of styrene and 1,3-butadiene by parallel vector analysis (PVA) and window factor analysis (WFA)

On-line Fourier-transform Raman spectroscopic monitoring of the anionic dispersion polymerization of styrene and 1,3-butadiene has been implemented with a noninvasive optic fiber Raman probe. After suitable pretreatment of the Raman spectra obtained, the resulting two-way data are analyzed using two self-modeling curve resolution (SMCR) techniques, parallel vector analysis (PVA) proposed in the preceding paper, as well as window factor analysis (WFA), coupled with a slightly modified principal component analysis (PCA) procedure. The idea of PVA is to construct a set of subspaces comprising only one common (spectral) component, and then find a vector that is in parallel with a series of vectors coming from different subspaces. This procedure offers a versatile avenue to approach the unique resolution of spectral profiles. The modified PCA procedure is a useful approach to eliminate the interference from nonreacting species and extract the spectral information concerning only the active reactions. The results reveal that there are three Raman spectrally active species in the system, i.e., styrene, 1,3-butadiene and poly(butadiene), and the product, poly(styrene), turns out to have no Raman signals in the investigated spectral region. The spectral and the concentration profiles of the three species are resolved uniquely using the SMCR methods. The resolved spectral profiles exhibit only small discrepancies compared to the spectra measured for pure species, and the estimated concentration profiles coincide with the results predicted by previous copolymerization theory. These results demonstrate that the proposed PVA method and the modified PCA procedure are competitive approaches for the resolution of two-way data from multivariate spectroscopic monitoring of reactions.