Near-infrared spectroscopy and multivariate analysis as real-time monitoring strategy of TEMPO-mediated oxidation of cellulose fibers from different feedstocks

Abstract

The regioselective oxidation of the primary hydroxyl groups of cellulose, usually mediated by the (2,2,6,6-tetramethylpiperidin-1-yl)oxyl radical (TEMPO), is highly popular in the scientific literature. However, the lack of efficient monitoring techniques imposes a severe limitation to its upscaling. This work involves a portable, user-friendly near-infrared spectroscopy device, optimized preprocessing techniques, and multivariate calibration to quickly estimate the carboxyl group content of modified cellulose (i.e., the extent of the oxidation). For that, bleached pulps from eucalyptus, pine, hemp, and sisal were submitted to TEMPO-mediated oxidation, varying the dosage of spent oxidizer (NaClO) and thus attaining samples of different values of carboxyl group content. These values were related to near-infrared spectra (908–1676 nm) by Partial Least Squares regression, yielding cross-validation coefficients (RCV2) above 0.97 for wood pulps, 0.95 for sisal pulp, and 0.91 for hemp pulp. Based on the residual prediction deviation, the model for each pulp was found to show good predictability. Nonetheless, the overall regression model, comprising the four different materials, was unreliable. In light of this, spectra were submitted to principal components analysis (PCA), hinting that pulps could be classified in terms of their hemicellulose to cellulose ratio. Considering all the statistical parameters, the overall proposal presented here begins with a PCA—Linear Discriminant Analysis model to classify the sample by its fiber type, subsequently selecting a specific regression model for that class. Overall, the presented models in this work allow the determination of the extent of oxidation of different cellulosic feedstocks, expressed as carboxyl content, in a fast and simple approach using a benchtop near-infrared equipment.