A Simple Method to Reduce the Optimized Parameters of Aqueous Amino Acid Solutions Using Association EOSs

Document Type : Research Article

Authors

School of Chemical, Gas and Petroleum Engineering, Semnan University, Semnan, I.R. IRAN

10.30492/ijcce.2020.38165

Abstract

Bringing up dissociation/ association equilibria, four new correlated equations are suggested for fixing the parameters of less investigated amino acid systems in a given value for two association models including PC-SAFT and CPA EOSs. Correlated parameters including co-volume parameter, association volumes, and the number of segments are dependent on the molecular weight of amino acids and have derived optimizing and fitting the parameters of the much-used aqueous amino acid solution. Moreover, to indicate the applicability of offered new equations, these formulas are utilized to reduce the number of optimized parameters from six to four for less investigated amino acid solutions. In the case of PC-SAFT EOS, the number of segments and association volume are fixed in a specified value and used to adjust four other parameters of PC-SAFT EOS including the segment of diameter, association energy, dispersion energy, and binary interaction parameter for less investigated amino acid solutions. In the case of CPA model, the correlated parameters are co-volume parameter and association volume, and these two parameters are applied to optimize four other parameters of CPA model such as temperature-dependent energy parameter containing a0 and c1, association energy, and binary interaction parameter.  Also, the solubility of studied systems is predicted at different temperatures for aqueous binary solutions. Furthermore, osmotic coefficients and water activity of these less investigated systems are evaluated. In the case of PC-SAFT model, the calculated AADs for liquid density, activity coefficient, water activity, osmotic coefficient, and solubility are 0.0032, 0.0864, 0.0058, 0.051, and 4.46*10-4, respectively. For CPA model, the AADs of these thermodynamic properties are 0.0117, 0.075, 0.0023, 0.16, and 2.79*10-4, respectively. Both models can reproduce the literature data as well, and though the CPA model is a semi-empirical EOS, it doesn’t have irrelevant answers.

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Main Subjects


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