Abstract
This paper describes the first in-depth attempt to characterize thermally induced aging of polypropylene (PP) samples by near infrared (NIR) spectroscopy. Significant levels of variation in NIR bands associated with short (amorphous-dominated) and long (crystalline-dominated) helices was readily captured when PP samples were subjected to thermal aging treatment. Partial least squares (PLS) regression models derived from the NIR spectra indicated significant level of correlation between the actual and predicted elongations of the samples. Analysis of PLS scores and two-dimensional (2D) correlation spectra derived from the aged PP samples revealed inner working mechanism of the regression model. Namely, the aging treatment essentially induces compositional change in crystalline and amorphous structures of the PP samples, which eventually affect the variation of the PLS scores. Thus, by utilizing the scores, it becomes possible to predict the change in the elongation property of the aged PP sample.
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