Determination of polymer blends composed of polycarbonate and rubber entities using near-infrared (NIR) spectroscopy and multivariate calibration

This paper presents an application of near-infrared NIR spectroscopy and multivariate calibration for compositional analysis of complex blends of polycarbonate (PC) and three copolymer components (C1, C2, and C3). Each of the copolymers is composed of 2-3 entities (sub-components) consisting of combinations of butadiene, styrene and acrylonitrile. The concentrations of the PC and three copolymer components were varied using a modified D-optimal design with criteria that minimized the inter-component correlations. To minimize non-chemical spectral variations, the acquired NIR spectra were pre-processed using standard normal variate (SNV and 2nd derivative Savitzky-Golay). Spectral range selection was explored in order to identify which optimal spectral regions were required to generate robust partial least-squares (PLS) models for each component. The optimal calibration models for PC, C1, C2 and C3 exhibited RMSEP values of 0.94%, 0.62%, 0.59% and 0.69% respectively. Using a set of external validation samples, the optimized calibration models for PC, C1, C2 and C3 exhibited bias values of −1.07%, 0.28%, −1.21% and −1.00%, and RMSEP of 2.43%, 1.44%, 1.51%, and 2.05%, respectively. Finally, using a set of 3 samples, the optimized model was successfully transferred to a secondary instrument located in a quality control (QC) laboratory.