کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5408737 | 1506540 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Prediction of the surface tension of binary liquid mixtures of associating compounds using the Cubic Plus Association (CPA) equation of state
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی تئوریک و عملی
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چکیده انگلیسی
Accurate knowledge of the surface tension of liquid mixtures is of considerable importance in the development of chemical processes that involve mass and heat transfer across phase interfaces. Despite the significant progress made in the development of advanced equations of state (EOS) for accurate representation of thermophysical properties, as well as sophisticated models for the thermodynamic equilibrium of highly non-ideal mixtures, they nonetheless have been to a large extent underrepresented in the prediction and correlation of the surface tension of such systems. In the current work, a modified version of the Butler equation is adopted alongside the Cubic Plus Association (CPA) EOS, with the objective of predicting and correlating the surface tension of binary liquid mixtures of associating compounds. In doing so, the experimental data of aqueous and non-aqueous mixtures of alcohols, glycols, acids, and phenol, comprised of 238 data points belonging to 18 binary mixtures are studied. It is shown that by incorporation of an association term based on the Wertheim's first-order thermodynamic perturbation theory, the CPA EOS can satisfactorily predict the values of surface tension with an AARD of only 9.78%, compared with deviations of 73.87% and 28.38% obtained for the Soave-Redlich-Kwong (SRK) and Peng-Robinson (PR) EOSs, respectively. Also, a major advantage of the proposed model is its inherent capability to simultaneously estimate the composition of the surface phase alongside the mixture surface tension. In addition, with only one adjusted binary parameter, AARDs of 5.29%, 7.09%, and 11.02% are obtained for the correlation of the experimental data using the CPA, SRK, and PR EOSs, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Molecular Liquids - Volume 231, April 2017, Pages 451-461
Journal: Journal of Molecular Liquids - Volume 231, April 2017, Pages 451-461
نویسندگان
Javad Hekayati, Sona Raeissi,