(126k) Hansen Solubility Parameters for the Prediction of 2,5-Furandicarboxylic Acid Solubility in Aqueous/Organic Solvent Mixtures at 293 K

Hansen solubility parameters (HSPs) are an adaptable and applicable thermodynamic model for predicting the solubility of a solute in varying solvents. In this work, HSPs are used to assess the solubility of 2,5-furandicarboxylic acid (FDCA) in nine pure, eight aqueous/organic binary, and three ternary solvent blends containing H₂O, acetonitrile, γ-valerolactone, γ-butyrolactone, ethanol, methanol, sulfolane, dimethyl sulfoxide (DMSO), and tetrahydrofuran (THF) at 293 K. FDCA is derived from biomass and can be upgraded to make useful biopolymers, but has low solubility in traditionally used solvents such as water. Thus, identifying compounds that can solubilize significant amounts of FDCA could allow for lower production costs and greater accessibility to sustainable bioplastics. Use of the derived Radius of Interaction (R_i,j) parameter allows for accurate prediction of solvent ratios for the highest FDCA solubility within a given combination of solvents. Such a predictive model addresses one of the significant challenges present in FDCA production, its low solubility, by allowing for targeted selection of high-solubility solvents.

The R_i,j parameter was found to accurately predict the solvent compositions yielding the highest FDCA solubility in over 80% of binary and ternary blends studied. Notably, mixtures containing DMSO were found to have the lowest values and the highest FDCA solubility values (30.7 wt% maximum), followed by mixtures containing THF (7.2 wt% maximum). All other binary solvent mixtures investigated had less than 2.5 wt% of FDCA solubilized. Even at these lower solubilities, maxima still correlated with the minimum R_i,j and reported higher solubilization than either pure water or pure organic. This same correlation was observed for ternary solvent blends, which saw solubilities exceeding 20 wt% at low values of R_i,j. Such solubility values are amongst the highest ever presented in the literature. Building on these trends observed in the experimental data, a MATLAB-based optimization code was developed and found successful in minimizing the R_i,j of a solvent blend to maximize FDCA solubility in binary and ternary aqueous solvents.