Tracking the curing process of automotive paint by moving-window two-dimensional infrared correlation spectroscopy and principal component analysis

• MW2DCOS and PCA were combined for the first time to interpret time serial spectra.
• Three stages of the curing process of a paint sample were found by MW2DCOS and PCA.
• Time-resolved spectral changes are shown in AP-MW2D correlation spectra.
• The time-resolved relationship of spectral peaks is revealed by PP- and PL-MW2DCOS.

Moving-window two-dimensional correlation spectroscopy (MW2DCOS) and principal component analysis (PCA) were combined to interpret the time serial infrared spectra. The curing process of an automotive paint sample was tracked by attenuated total reflection Fourier transform infrared spectroscopy. Score plots of the first and second principal components showed that the curing process contained three stages. Meanwhile, the loading spectra indicated that the solvent was a mixture of aromatic compounds. Absorption peaks which changed significantly in each stage were revealed by auto-peak MW2DCOS. Furthermore, point-line and point-point MW2DCOS demonstrated the time-resolved relationship between absorption peaks from toluene, xylene and resin. In summary, the evaporation of toluene was the first stage of the curing process of this automotive paint sample. Next, the mixture of o-xylene, m-xylene and p-xylene began to evaporate in the second stage. After the evaporation of the solvent, the solid paint membrane was formed. For the interpretation of the time serial spectra, PCA is useful to estimate the number of significant chemical components and to find out the important turning points of the process, while MW2DCOS can show the changes of the spectral peaks and the relationship between them step by step. The combination of PCA and MW2DCOS is very interesting to extract and display the time-resolved information in the time serial spectra.

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