Abstract
A predictive calibration model based on non-linear partial least squares (PLS) regression was developed to describe the relationship between the near-infrared (NIR) reflectance spectra and the acid value, hydroxyl value and water, content in polyesterification of dicarboxylic acids with diols. Two dicarboxylic acids and six diols were tested in different combinations with one dicarboxylic acid and one diol at a time. The polyesterifications were carried out isothermally in a laboratory scale semi-batch reactor at temperatures between 140–190 °C. NIR spectrometry offers a fast in-line method for monitoring and controlling the polyesterification reaction. A predictive model which relates all the NIR spectra and the measured acid values was developed. The calibration of the NIR spectra and the hydroxyl value succeeded in experiments where the hydroxyl value was determined. The measured water content and the NIR spectra could not be calibrated with the same model for different dicarboxylic acid and diol combinations. Principal component analysis (PCA) was used to classify the NIR spectra. The spectra could be classified according to the dicarboxylic acid and diol used in the experiment.
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