Discrimination of Nylon Polymers Using Attenuated Total Reflection Mid-Infrared Spectra and Multivariate Statistical Techniques

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Abstract
Nylons are an important class of synthetic polymers, from an industrial, as well as forensic, perspective. A spectroscopic method, such as Fourier transform infrared (FT-IR) spectroscopy, is necessary to determine the nylon subclasses (e.g., nylon 6 or nylon 6,6). Library searching using absolute difference and absolute derivative difference algorithms gives inconsistent results for identifying nylon subclasses. The objective of this study was to evaluate the usefulness of peak ratio analysis and multivariate statistics for the identification of nylon subclasses using attenuated total reflection (ATR) spectral data. Many nylon subclasses could not be distinguished by the peak ratio of the N–H vibrational stretch to the sp3 C–H2 vibrational stretch intensities. Linear discriminant analysis, however, provided a graphical visualization of differences between nylon subclasses and was able to correctly classify a set of 270 spectra from eight different subclasses with 98.5% cross-validated accuracy.