Abstract

Of the recently developed univariate and multivariate near-IR FT-Raman methods for estimating cellulose crystallinity, the former method was applied to a variety of lignocelluloses: softwoods, hardwoods, wood pulps, and agricultural residues/fibers. The effect of autofluorescence on the crystallinity estimation was minimized by solvent extraction or chemical treatment or both. Additionally, when the roles of lignin and hemicellulose in the Raman crystallinity assessment were investigated, it was found that syringyl lignin containing lignocelluloses generated somewhat higher crystallinity, whereas the presence of hemicellulose reduced the crystallinity. Overall, when autofluorescence was minimized and corrections made for hemicellulose and syringyl lignin contributions, the univariate Raman method performed well and estimated cellulose crystallinity accurately. Moreover, when the Raman and Segal-WAXS methods were compared, we observed that in the absence of significant fluorescence, the Raman method was influenced mostly by hemicellulose and syringyl lignin, whereas the Segal-WAXS was affected by various types of lignin and hemicellulose. It was concluded that the near-IR FT-Raman method with corrections for influences of syringyl lignin and hemicellulose can be used to correctly estimate cellulose crystallinity.

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