Modelling the effects of ethanol on the solubility of the proteinogenic amino acids with the NRTL, Gude and Jouyban-Acree models

Abstract

The addition of organic solvents, such as ethanol, to molecules in solution is an effective process for crystallization and is used in industrial settings (i.e. pharmaceutical production, downstream processing, etc.). In this study, we use solubility data of all proteinogenic α-amino acids in binary ethanol/water systems to model their excess solubility. We use the empirical and regressive models of Gude and NRTL and the predictive Jouyban-Acree model. Based on the results, we hypothesize that amino acids that are spherical and lack a reactive side chain show little or no excess solubility. Being rod-like and/or having a reactive side chain leads to a positive excess solubility in a mixed solvent of ethanol and water. The empirical and regressed models, NRTL and Gude, fit the data well and the predictive Jouyban-Acree model, not originally intended to be used for small molecules, is less accurate but offers insights into the thermodynamic properties of the amino acids.