Quantifying the Abundance of Alkane Moieties in Lignins with FTIR Spectroscopy and PLS Regression; Estimating...

As society is rapidly converting from fossil-based materials to greener alternatives, the valorization of lignin through chemical modification has been given considerable attention. Characterizing this highly heterogeneous biopolymer is a constant challenge, and an emerging strategy for dealing with variations in material characteristics is combining traditional analytical techniques with chemometrics, such as Fourier-transform infrared (FTIR) spectroscopy with partial least squares regression (PLSR). Here, a calibration data set was built based on FTIR spectra and the total carbon-hydrogen bond (CHB) content of mixtures of technical lignins and alkanes, meant to emulate esterified samples. From this data, a PLSR model was built which predicted the CHB content of esterified lignin reaction products with an RMSE_CV=5.685 mmol/g and RMSE_Pred=5.827 mmol/g, and from which the weight percentage of ester-to-lignin was determined. When compared to wet-chemical analysis, good agreement between the techniques was found with an obtained RMSE_Pred=8.3 % and a R² _Train=0.9752 for the degree of esterification. This indicates high model predictability and goodness of fit, and that the calibration data set successfully emulated esterified lignin samples.