Quantitative prediction of the solvent fractionation of lignin

Lignin is the most abundant and sustainable source of aromatics on earth. However, its heterogeneous structure and hard-to-predict physicochemical properties complicate its valorization potential in many applications. We present a combined experimental and theoretical approach to quantify and predict the fractionation of lignin in binary solvent blends. This serves as an important way to reduce feedstock heterogeneity, obtaining lignin fractions with better defined molecular features. Our model predicts how the yield, in terms of amount of dissolved lignin, varies with the solvent composition. To explain the experimental results, it is essential that we invoke the physical and chemical polydispersity of lignin in our model. We obtain quantitative agreement with experimental results on various molecular features of the dissolved lignin fractions, including the yield, molecular mass, and the number of functional hydroxyl groups. This work shows that the amount and nature of dissolved lignin can be tuned predictably using a combination of solvents, which paves the way for a broader applicability of lignin as a bio-based material.