Accurate correlation and robust prediction for complex molecule solubility or solid-liquid equilibrium (SLE) in solvents and solvent mixtures have drawn much interest recently1
. Solubility models such as the Non-Random Two Liquid Segment Activity Coefficient (NRTL-SAC) model2
and its variations such as UNIQUAC-SAC3
and COSMO-SAC with apparent sigma profiles4
are now routinely used in the industry. This paper presents a refinement to the successful NRTL-SAC model in several perspectives. Specifically, the model is refined by modifying the Flory-Huggins expression in the entropy calculation. Additionally, a new conceptual segment has been proposed to better characterize polar components. At last, temperature dependency of activity coefficient is addressed in the refined model. We present the rationale for the refined model, along with the updated conceptual segment numbers for common solvents. Both the original and the refined NRTL-SAC models are employed to calculate vapor-liquid and liquid-liquid equilibrium for binary solvent systems and solubility of several drug molecules in solvents and solvent mixtures. The refined model provides improved prediction performance when compared with the original model, especially for systems containing larger size molecules. The refined NRTL-SAC model will be further extended to provide predictive capability for complex molecule solubility in excipients and polymers.
1. Tanveer, S.; Hao, Y.; Chen, C.-C., Introduction to solid-fluid equilibrium modeling. Chemical Engineering Progress 2014, 110 (9), 37-47.
2. Chen, C.-C.; Song, Y., Solubility Modeling with a nonrandom two-liquid segment activity coefficient model. Industrial & Engineering Chemistry Research 2004, 43 (26), 8354-8362.
3. Haghtalab, A.; Yousefi Seyf, J., Vaporâliquid and solidâliquid modeling with a universal quasichemical segment-based activity coefficient model. Industrial & Engineering Chemistry Research 2015, 54 (34), 8611-8623.
4. Islam, M. R.; Chen, C.-C., COSMO-SAC sigma profile generation with conceptual segment concept. Industrial & Engineering Chemistry Research 2014, 54 (16), 4441-4454.