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In this study a biobased polyurethane (PU) thermoset is investigated due to its turbidity. In contrary to the expectations, the turbidity increases with a higher amount of a low molecular weight crosslinker. Morphological aspects are investigated with SEM imaging and measurement of the effective scattering coefficient μ’s. FTIR spectroscopy is applied to study the influence of the chemical structure. This is combined with multivariate data analysis to identify the relevant peaks. SEM images show spherical precipitations with increasing turbidity and a simultaneous increase in the μ’s values. FTIR analysis shows a significant amount of unreacted isocyanate‐(NCO)groups and a low level of hydrogen bonding. No formation of typical hard and soft segments is detectable. Therefore, it can be concluded that the increase in polarity differences with increasing crosslinker amount disabled the mixture of the polyol and isocyanate components, resulting in the precipitation of the isocyanate. At the same time, the low molecular weight crosslinker (~200 g mol−1) can react with the NCO quickly, reducing the mobility of the polymer chain, with remaining, non‐reacted isocyanate. A proof for the correlation of the differences in the FTIR and the μ’s values was found by a regression analysis with an R2 of 0.94.
Polyurethane thermosets have a wide range of applications. In this study, alternative raw materials were used to enhance sustainability. In two newly developed biobased polyurethanes (PUs), the cross-linker content was varied, which caused phase separation and therefore affected the turbidity. To investigate this phenomenon, UV–Vis–NIR spectroscopy was utilized. Spectra were recorded from 200 to 2500 nm in transmittance mode, and multivariate data analysis was applied to the three UV, Vis, and NIR sections separately. For the two different PU classes, each with five different cross-linker contents, classification by principal component analysis combined with linear or quadratic discriminant analysis was possible with an accuracy between 93% and nearly 100%. The best separation was achieved in the NIR range. Partial least-squares regression models were determined to predict the cross-linker content. As mentioned, the model for the NIR range is the most suitable, with the highest R2 (validation) of 0.99 for PU1 and 0.98 for PU2. The corresponding root-mean-square error of prediction values of the external validation was the lowest, with 0.82% (PU1) and 1.25% (PU2). Therefore, UV–Vis–NIR absorbance spectroscopy, especially NIR, is a suitable tool for monitoring the appropriate material composition of turbid PU thermosets in line.