A population balance model for lignin: Tracking molecular weights, S/G ratio, and bond compositions

Lignin, a major component of lignocellulosic biomass, presents significant opportunities for sustainable applications. However, lignin remains underutilized due to its structural complexity and feedstock variability. To address these challenges, we developed a population balance equation (PBE)-based model to simulate lignin fractionation dynamics, focusing on depolymerization, condensation, and demethoxylation reactions. The model captures key transformations in lignin chains, including changes in molecular weight distribution, bond composition, and monomeric ratios, while requiring far fewer computational resources than kinetic Monte Carlo (kMC) methods. The estimated kinetic parameters showed strong agreement with experimental data across different temperatures, validating the model’s accuracy. Furthermore, the results highlighted the temperature sensitivity of demethoxylation and its impact on the S/G ratio, offering valuable insights for optimizing reaction conditions. This scalable and versatile framework provides a robust tool for lignin valorization and paves the way for improved biomass pretreatment strategies. • A PBE-based model simulates lignin fractionation with high accuracy. • Model captures depolymerization, condensation, and demethoxylation dynamics. • Various lignin properties are tracked and validated with the experiments. • Kinetic parameters for experimental data across multiple temperatures. • Model efficiently handles feedstock variability with low computational cost.