The Application of Hierarchical Cluster Analysis to Lignins Classification Based on Data of High-Resolution NMR and Solid-State NMR Spectra on 13C Nuclei

Abstract

Lignin is the second most abundant biological polymer on Earth with a complex chemical structure. A large amount of different technical lignins are produced as a waste product of the pulp and paper industry and are not used rationally. The study of the structure of such lignins is relevant due to their potential applications. It is important to obtain comprehensive knowledge about the structure of lignin macromolecule and to classify lignins based on it. High-resolution nuclear magnetic resonance (NMR) experiments for dissolved samples are widely used to study this biopolymer. However, this approach does not allow researching insoluble technical lignins. Solid-state NMR spectroscopy may become a solution to this problem. In this paper, we propose an approach to classify the degree of lignin alteration by clustering of solid-state spectra with hierarchical cluster analysis method. This approach is important because of the lack of direct correlations between the NMR spectra of lignins in the dissolved and solid states, which is based on experimental data.