Modeling and Prediction of Solid Solubility by GE Models

Larissa P. Cunico Anjan K. Tula Roberta Ceriani  

Computational Pharmaceutical Solid State Chemistry, First Edition. Edited by Yuriy A. Abramov. 2016 John Wiley Sons, Inc. Published 2016 by John WUey Sons, Inc. 

An important first step in any model-based calculation procedure is the analysis and type of data used. Here, the accuracy and reliability of the measured data sets to be used in regression of model parameters is a very important issue. It is clear that reliable parameters for any model cannot be obtained from low-quality or inconsistent data. However, for many published experimentally measured solid solubility data, information on measurement uncertainties or quality estimates are unavailable. Also, pure component temperature limits and the excess GE models typically used for nonideality in vapor-liquid equilibrium (VLE) may not be rehable for SEE (or solid solubility). To address this situation, an alternative set of consistency tests [3] have been developed, including a new approach for modehng dilute solution SEE, which combines solute infinite dilution activity coefficients in the hquid phase with a theoretically based term to account for the nonideality for dilute solutions relative to infinite dilution. This model has been found to give noticeably better descriptions of experimental data than traditional thermodynamic models (nonrandom two liquid (NRTE) [4], UNIQUAC [5], and original UNIversal Eunctional group Activity Coefficient (UNIEAC) [6]) for the studied systems. 

Choose a thermodynamic model (UNIFAC, PC-SAFT, NRTL-SAC, UNISAC) 

Model-based pure compound parameters estimation 

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