| Autor: |
Arunprakash T. Karunanithi, Steven L. Suib, Shanthakumar Sithambaram, Luke E. K. Achenie, Charles Acquah |
| Rok vydání: |
2009 |
| Předmět: |
|
| Zdroj: |
Computers & Chemical Engineering. 33:1014-1021 |
| ISSN: |
0098-1354 |
| DOI: |
10.1016/j.compchemeng.2008.11.003 |
| Popis: |
Critical to crystallization chemical product design is the choice of an appropriate solvent. Traditional methods have focused on bench scale experiments using classes of solvents (e.g. polarity) with the different classes giving rise to different crystal morphologies. However, there are instances where some solvents belonging to a particular class give completely different morphology from other solvents in the same class. There has been some modeling effort aimed at predicting crystal morphology. A major drawback with some of these morphology prediction models is that they tend to be limited in application. It is clear that the solvent selection, with respect to crystal morphology cannot be carried out efficiently by just experimentation or modeling alone. This paper outlines a systematic methodology which combines targeted bench scale crystallization experiments, an efficient computer-aided molecular design (CAMD) approach and a database search approach for the design and selection of solvents for crystallization of carboxylic acids. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect