Free-volume theory coupled with modified group-contribution PC-SAFT for predicting the viscosities. II. Alcohols and their mixtures
Autor: | Xuan T.T. Nguyen, Dong NguyenHuynh, My T. Luu, Chau T.Q. Mai, Siem T.K. Tran |
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Rok vydání: | 2019 |
Předmět: |
Work (thermodynamics)
Series (mathematics) 010405 organic chemistry Group (mathematics) Free volume theory General Chemical Engineering General Physics and Astronomy Estimator Thermodynamics Alcohol 02 engineering and technology 01 natural sciences 0104 chemical sciences Physics::Fluid Dynamics chemistry.chemical_compound Viscosity 020401 chemical engineering chemistry Methanol 0204 chemical engineering Physical and Theoretical Chemistry |
Zdroj: | Fluid Phase Equilibria. 502:112298 |
ISSN: | 0378-3812 |
DOI: | 10.1016/j.fluid.2019.112298 |
Popis: | This work continues a series of studies on the actual ability of the model based on the Free-volume theory (FVT) recently proposed coupled with the modified group-contribution PC-SAFT (DOI: 10.1016/j.fluid.2019.112280) to simultaneously predict fluid phase equilibria and the viscosity of alcohols (from methanol to 1-octadecanol). Generalized correlations coefficients are suggested for the FVT triplet parameter set, which allows extrapolating the prediction of viscosity of similar compounds that are not included in the regression database. Similar to the previous considered systems, our model also remains a realistic estimator of the viscosities in the cases of associative molecules, over extended temperature and pressure up to 2000 bar. The overall average absolute deviations of the experimental vapor and liquid viscosity from those calculated by the model are 2.47% and 3.77%, respectively, which are appropriate for most industrial applications. In addition, liquid viscosity of alcohol containing mixtures was also predicted, with an overall average deviation of 4.5% for 62 considered mixtures (4157 data points). The calculation results shown the superiority of the proposed model compared to the other available viscosity models. |
Databáze: | OpenAIRE |
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