Thermodynamic modeling of amino acid solutions: A new perspective on CPA EOS
The Journal of Chemical Thermodynamics, ISSN: 0021-9614, Vol: 124, Page: 21-31
2018
- 7Citations
- 9Captures
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Article Description
The Cubic Plus Association (CPA) equation of state is applied to simultaneously calculate various thermodynamic properties of single aqueous solutions containing amino acids. Likewise, with a new perspective on CPA model, the highly dependency of amino acid solubility on the prevailing pH value is investigated bringing up dissociation/association equilibria. Hence, pure component parameters of 24 organic amino acids are fitted to density, solute activity coefficient, and water activity of their aqueous solutions at ambient conditions, and solely one temperature independent binary interaction parameter is used for each system. Also, two new equations are presented according to optimized parameters of amino acids. To prove the proficiency of applied models, solubility of aqueous solutions is predicted in binary systems at different temperatures and pH values taking into account the dissociation/association equilibria. Subsequently, the optimized parameters of CPA model are applied to reproduce the literature data for various thermodynamic properties including density and solute activity coefficient at other temperatures which range till 333 K. In addition, the effect of pressure on liquid density is checked, and the liquid density of mixed aqueous solutions containing two amino acids is evaluated. Eventually, it can be comprehended that not only the water activity and activity coefficients of aqueous amino acid solutions, but also liquid density and solubility of single solutions are reasonably calculated by CPA EOS over a wide range of temperatures and solute concentration applying dissociation/association equilibria.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0021961418303811; http://dx.doi.org/10.1016/j.jct.2018.04.016; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85046367249&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0021961418303811; https://dx.doi.org/10.1016/j.jct.2018.04.016
Elsevier BV
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