Data-Centric Development of Lignin Structure–Solubility Relationships in Deep Eutectic Solvents Using Molecular Simulations

Abstract

Lignin is a natural source of aromatic chemicals with significant potential as an abundant, renewable feedstock for value-added products. Deep eutectic solvents (DES)�solvents composed of a hydrogen bond donor (HBD) and acceptor (HBA) in varying ratios�have emerged as a highly tunable class of solvents for lignin solubilization. However, the variety of possible DES compositions and limited molecular-scale understanding of lignin solubility makes solvent selection a challenge without laborious trial-and-error experimentation. To address these challenges, we use classical molecular dynamics (MD) simulations to study the interactions of lignin model compounds with various DES−water systems. Quantitative parameters (descriptors) were calculated by postprocessing the MD results and used to train a regression model that predicts experimentally determined solubilities of lignin model compounds. This approach revealed that the most important descriptors of solubility are the system temperature, solute hydrophilicity, and metrics quantifying hydrogen bonding. Maximizing the interactions between solute−HBD (hydrophobic group), water−HBD (hydrophilic group), and water−HBA molecules led to the highest model compound solubility. Our results support a hydrotropic mechanism in which extensive DES− water hydrogen bonding and favorable HBD interactions with the solute promote high solubility. We applied the regression model derived using model compounds to predict the solubility of representative lignin oligomers. The model predicted lignin oligomers' solubilities in good agreement with experiments, indicating that the simulations of model compounds can be extended to predict the solubility of larger lignin compounds across a range of solvent compositions and temperatures. These findings provide new molecular-scale insight into lignin solubilization mechanisms and a new method for computationally screening potential solvent systems for lignin valorization.

Large-scale computational polymer solubility predictions and applications to dissolution-based plastic recycling

“…Finally, we envision further expanding the database to consider new classes of green or designer solvents with potential value in polymer dissolution, such as ionic liquids or deep eutectic solvents. 62,63…”

Heuristic Computational Model for Predicting Lignin Solubility in Tailored Organic Solvents

“…Future work will investigate variations in molecular weight and how this influences predictions. Similarly, future work will extend this approach more explicitly to solvent mixtures, particularly for ionic liquids or deep eutectic solvents, − to explore whether preferential solvation effects manifest in these systems, which may not be captured by our current framework and may require additional descriptors to quantify. ,,, …”

“…Several studies have used empirical parameters, such as Hansen solubility parameters, − to guide solvent selection for fractionation, but these parameters do not capture variations in lignin composition. Recent computational studies using conductor-like screening model for realistic solvents (COSMO-RS) calculations or molecular dynamics (MD) simulations have also explored the molecular basis of lignin solubility but generally for a small range of lignin structures/solvents due to their computational expense. − There, thus, remains a need for methods to efficiently guide solvent selection for lignin solubilization while accounting for the heterogeneous population of possible lignin structures.…”

Compatibility analysis between natural rubber/polybutadiene rubber and protective waxes based on experiments and materials studio simulations

“…Thus, the minimal size representing the actual size becomes important for calculating thermodynamic parameters 21 . It has been shown that the solubility parameter (δ) and density of polymers stabilize and converge to a constant value with the increasing molecular chain length 13,18,22 . The solubility parameter (δ) and density of NR and BR at different molecular weights need to be calculated to determine the minimum size.…”

“…21 It has been shown that the solubility parameter (δ) and density of polymers stabilize and converge to a constant value with the increasing molecular chain length. 13,18,22 The solubility parameter (δ) and density of NR and BR at different molecular weights need to be calculated to determine the minimum size. Figure 2 shows the relationship of repeating units and the solubility parameter and density.…”