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A catalyst-free organosolv pulping process was applied to cup plant (Silphium perfoliatum, S), Miscanthus grass (Miscanthus x giganteus, M), and the Paulownia tree (Paulownia tomentosa, P), resulting in high-purity lignins with no signals for cellulose, hemicellulose, or other impurities in two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra. Different biomass particle sizes used for the organosolv pulping (1.6–2.0 mm (1); 0.5–1.0 mm (2); <0.25 mm (3)) influenced the molecular weight and chemical structure of the isolated lignins. Principal component analysis (PCA) of 1H NMR data revealed a high intergroup variance of Miscanthus and Paulownia lignins, separating the small particle fraction from the larger ones. Furthermore, monolignol ratios identified via HSQC NMR differ significantly: Miscanthus lignins were composed of all three monolignols (guaiacyl (G), p-hydroxyphenyl (H), syringyl (S)), while for Paulownia and Silphium lignins only G and S units were observed (except for P3).

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The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (M w and M n) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7–9 and 14–16% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography.

When optimizing the process parameters of the acidic ethanolic organosolv process, the aim is usually to maximize the delignification and/or lignin purity. However, process parameters such as temperature, time, ethanol and catalyst concentration, respectively, can also be used to vary the structural properties of the obtained organosolv lignin, including the molecular weight and the ratio of aliphatic versus phenolic hydroxyl groups, among others. This review particularly focuses on these influencing factors and establishes a trend analysis between the variation of the process parameters and the effect on lignin structure. Especially when larger data sets are available, as for process temperature and time, correlations between the distribution of depolymerization and condensation reactions are found, which allow direct conclusions on the proportion of lignin's structural features, independent of the diversity of the biomass used. The newfound insights gained from this review can be used to tailor organosolv lignins isolated for a specific application.