Abstract
AbstractMid and near infrared (MIR and NIR) spectroscopy associated with the partial least squares (PLS) method makes it possible to rapidly characterize the composition of linear low‐density polyethylene (LLDPE) in a large range of 1‐hexene content from 0 to 21 mol%. LLDPEs are produced using zirconocene catalysts activated with methylaluminoxane. PLS regression methods for MIR and NIR are constructed from this series of LLDPEs to quantify the 1‐hexene content in unknown copolymers. In this case, the PLS regression method aims to correlate the 1‐hexene content in the copolymers with their IR spectra. Multivariate calibration models are constructed by the PLS algorithm on pretreated data of MIR and NIR analyses. They are tested and validated by comparing results obtained by nuclear magnetic resonance and the PLS analyses for four unknown ethylene‐1‐hexene copolymers.
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