Accuracy of Molar Solubility Prediction from Hansen Parameters. An Exemplified Treatment of the Bioantioxidant <span style="font-variant: small-caps">l</span>-Ascorbic Acid

• Main Authors: Ralph J. Lehnert, Richard Schilling
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Applied Sciences
• Subjects: molar solubility estimation; ascorbic acid solubility; ascorbic acid Hansen parameter
• Online Access: https://www.mdpi.com/2076-3417/10/12/4266

Estimating molar solubility from the Hildebrand-Scott relation employing Hansen solubility parameters (HSP) is widely presumed a valid semi-quantitative approach. To test this presumption and to determine quantitatively the inherent accuracy of such a solubility prognosis, <span style="font-variant: small-caps;">l</span>-ascorbic acid (LAA) was treated as an example of a commercially important solute. Analytical calculus and Monte Carlo (MC) simulation were performed for 20 common solvents with total HSP ranging from 14.5 to 33.0 (MPa)^0.5 utilizing validated material data. It was found that, due to the uncertainty of the material data used in the calculations, the solubility prediction had a large scattering and, thus, a low precision. Prediction power is most adversely affected by the uncertainty of the HSP estimates (solvent and solute), followed by the solute heat of fusion. The solute melting temperature and molar volume have minor effects. Computed and experimental solubilities show the same qualitative behavior, while quantitative discrepancies reach one to three orders of magnitude. Solubility estimates were found to provide, at best, rough guiding information but, with the quality of material data on LAA available, they cannot be rated semi-quantitative. It is assumed that these results generally apply at least to solute-solvent systems with a material data quality and solubility similar to LAA.