Identification of weak transitions using moving-window two-dimensional correlation analysis: treatment with scaling techniques

Abstract

In the present study, the theory of the data treatment with scaling techniques for moving-window two-dimensional (scaling-MW2D) correlation analysis was first proposed. This new analytical method of spectroscopy can significantly enhance the resolving capacity of the moving-window two-dimensional (MW2D) correlation infrared spectroscopy in the direction of the perturbation variable. So, it strengthened the ability of MW2D to highlight the weak transitions. The in situ infrared spectra of four common polymers, including polyamide 66 (PA66), polystyrene-block-polybutadiene-block-polystyrene block copolymer (SBS), isotactic polypropylene (iPP), and polyoxymethylene (POM), were employed to illustrate the advantages of scaling-MW2D. In the applications of the present study, the conventional autocorrelation MW2D can only distinguish the melting point of PA66, the maximum crystallization temperature of POM, and the primary oxidation of SBS. However, the autocorrelation scaling-MW2D not only can more easily determine the above transitions, but also can identify PA66 brill transition, the dissociation of adsorbed water in PA66, POM secondary crystallization, the glass transition of hard blocks in SBS, and the generation of the aldehyde and hydroxyl groups during SBS oxidation. Our further study found that the selection of the scaling factor α was very important. The golden point α = 0.618 was the best value, and satisfactory application results can be achieved. The slice scaling-MW2D was also investigated. The scaling-MW2D method of spectroscopy can be used elsewhere. The application of this analytical method should not be limited to the infrared spectra, and it also should not be limited to transitions in polymers. This method can be easily extended and applied to other materials and spectra.