LAPSE:2019.1166
Published Article
LAPSE:2019.1166
A Thermodynamic Approach for the Prediction of Oiling Out Boundaries from Solubility Data
Venkateswarlu Bhamidi, Brendan P. Abolins
November 24, 2019
Many pharmaceutical molecules, fine chemicals, and proteins exhibit liquid−liquid phase separation (LLPS, also known as oiling out) during solution crystallization. LLPS is of significant concern in crystallization process development, as oiling out can compromise the effectiveness of a crystallization and can lead to operational problems. A comprehensive methodology that allows a process scientist/engineer to characterize the various phase boundaries relevant to oiling out is currently lacking. In this work, we present a modeling framework useful in predicting the binodal, spinodal, and gelation boundaries starting from the solubility data of a solute that is prone to oiling out. We collate the necessary theoretical concepts from the literature and describe a unified approach to model the phase equilibria of solute−solvent systems from first principles. The modeling effort is validated using experimental data reported in the literature for various solute−solvent systems. The predictive methods presented in this work can be easily implemented and help a process engineer establish the design space for a crystallization process that is affected by liquid−liquid phase separation.
Keywords
binodal, gel boundary, liquid–liquid phase separation, LLPS, oiling out, phase diagram prediction, phase diagrams, prediction of oiling out, spinodal
Suggested Citation
Bhamidi V, Abolins BP. A Thermodynamic Approach for the Prediction of Oiling Out Boundaries from Solubility Data. (2019). LAPSE:2019.1166
Author Affiliations
Bhamidi V: Scale-up and Process Innovation, Eastman Chemical Company, 200 S Wilcox Dr., Kingsport, TN 37662, USA [ORCID]
Abolins BP: Corporate Innovation, Eastman Chemical Company, 200 S Wilcox Dr., Kingsport, TN 37662, USA
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Journal Name
Processes
Volume
7
Issue
9
Article Number
E577
Year
2019
Publication Date
2019-09-01
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr7090577, Publication Type: Journal Article
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LAPSE:2019.1166
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doi:10.3390/pr7090577
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Nov 24, 2019
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CC BY 4.0
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Nov 24, 2019
 
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Original Submitter
Calvin Tsay
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