화학공학소재연구정보센터
Fluid Phase Equilibria, Vol.455, 43-53, 2018
Solubility predictions of acetanilide derivatives in water: Combining thermochemistry and thermodynamic modeling
Knowledge about solubility in water is required for crystallization processes, for the development of structure-property relationships, for the establishment of solubility scales, assessing environmental contamination, and for validating thermodynamic models. Approaches are desired that allow predicting solubility without the use of any experimental solubility data. Most methods that have been proposed to predict aqueous solubility of organic compounds face low prediction reliability and the lack of model interpretability. This work proposes the use of a thermodynamic approach for the prediction of solubility of acetanilide and its derivatives in water. This approach requires fusion enthalpy and fusion temperature as well as the activity coefficient of the respective acetanilide derivative. The latter was obtained by the equation of state PC-SAFT, which uses thermochemistry data as input for model parametrization. The thermochemical data on acetanilide and its derivatives (vapor and sublimation pressures, sublimation and fusion enthalpies) were collected from the literature and evaluated for internal consistency. In order to validate the final solubility prediction model, aqueous solubility of acetanilide and 17 derivatives were predicted and compared to experimental solubility data from literature at 298.15 K as well as to an ideal solubility model, which assumes ideal mixture behavior. The results showed that mixtures of acetanilides water are highly non-ideal, and the average deviations between solubility data and ideal solubility model could be reduced by two orders of magnitude by using PC-SAFT for the solubility predictions. More promising, PC-SAFE was found to allow predicting the temperature dependence of the aqueous solubility accurately, while ideal solubility model failed to quantitatively describe temperature dependent solubility. (C) 2017 Elsevier B.V. All rights reserved.