| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 710712 | IFAC Proceedings Volumes | 2009 | 6 Pages |
Abstract
AbstractThe use of predictive solubility models can be of great use for crystallization modeling, and can decrease the amount of experimental data needed to create a robust crystallization model. In this paper, predictive solubility models such as MOSCED, UNIFAC, NRTL-SAC, and the Jouyban-Acree model are compared against an empirical model for predicted solubility accuracy. The best models are subsequently compared against the empirical model for the antisolvent crystallization of acetaminophen in acetone using water. Two different optimization objective functions are executed for each solubility model to generate corresponding optimal profiles. The effect of these optimal profiles on the predicted crystal properties is evaluated.
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
D.J. Widenski, A. Abbas, J.A. Romagnoli,