Modeling vapour pressure using compound specific cohesion factor relationship

Joshipura, Milind; Dabke, S.P.; Subrahmanyam, N.

doi:10.1016/j.jtice.2010.01.006

Cited by 13 publications

(8 citation statements)

References 8 publications

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“…In this equation, T R is the reduced temperature, given in eq , and m is a generalized function of the acentric factor, modified further by the same authors, given in eq . As a part of the cohesion parameter, the alpha function is also known as the cohesion function …”

Section: Peng–robinson Equation Of Statementioning

confidence: 99%

“…Besides that, we have focused in the “crude” format of each model, i.e., with the adjustable parameters free for estimation, aiming to evaluate the maximum potential of each model. Some alpha function proposals consist only in new generalizations for the parameters of an already proposed format, and several examples of “original” functions could be found with rearranged formats. ,,− Other articles that reviewed and/or compared some alpha functions models could also be cited. ,,− …”

Section: Different Alpha Functionsmentioning

confidence: 99%

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Comparison of 20 Alpha Functions Applied in the Peng–Robinson Equation of State for Vapor Pressure Estimation

Young

Pessoa

Ahón

2016

Ind. Eng. Chem. Res.

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Since Peng and Robinson proposed their cubic equation of state (cubic EoS) in 1976, several attempts were made to improve its performance and to extend its application to an increasing number of substances. Many authors have focused in vapor pressure calculation, which in great part signifies the proposal of a new alpha function for the attractive term. In this work, 20 alpha function models were compared in vapor pressure estimation for 56 compounds with the Peng−Robinson EoS. The values calculated with the EoS were compared with values obtained from the DIPPR database. The parameters are presented as an useful data bank for future applications. With these results, it was possible to show which model had the best performance for each class of compounds, which is important information for the development of new alpha function models. The alpha functions of Androulakis et al., Schwartzentruber et al., and Almeida−Aznar−Telles obtained the best results among all the models evaluated.

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Section: Peng–robinson Equation Of Statementioning

confidence: 99%

Section: Different Alpha Functionsmentioning

confidence: 99%

Comparison of 20 Alpha Functions Applied in the Peng–Robinson Equation of State for Vapor Pressure Estimation

Young

Pessoa

Ahón

2016

Ind. Eng. Chem. Res.

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“…According to literature these three models show a minimum deviation from the experimental values of density and proved to be better alternative for the estimation of density. Nasrifar and Moshfeghian proposed a model for the estimation of density of refrigerant fluids in conjunction with PSRK. − Recently Valderrama and Forero have shown that the PRNSM1 cohesion factor model can predict the vapor pressure of ILs accurately. In the present study, Nasrifar’s density model (NM) was used in conjunction with PRNSM1 and original SRK cohesion factor expressions.…”

Section: Computational Detailsmentioning

confidence: 99%

“…In this work experimental densities of six commercial ILs, namely, [EMIM][MeSO 3 ], [EMIM][Ac], [EMIM][SCN], [EMIM][EtSO 4 ], [TEMA][MeSO 4 ], and [TDTHP][Phosph] (Figure ) were measured and predicted by different models. Out of these models, two models based on cohesion factor of cubic equation of state are chosen from literature , along with our newly derived cohesion factor expression . The deviation between measured and predicted density was checked, and the best model with minimum deviation was selected.…”

Section: Introductionmentioning

confidence: 99%

Densities of Six Commercial Ionic Liquids: Experiments and Prediction Using a Cohesion Based Cubic Equation of State

et al. 2014

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Ionic liquids (ILs) are eco-friendly solvents due to their low vapor pressure. Properties such as density should be known as it affects the mass transfer rates. Due to its limitless combinations, it is impractical to measure densities experimentally. For the first time, the cohesion factor in the cubic equations of state (CEOS) is used to predict the densities of six commercial ILs, namely, 1-ethyl-3-methylimidazolium methane sulfonateTris(2-hydroxyethyl)-methylammonium methyl sulfate [TEMA][MeSO 4 ], and trihexyl(tetradecyl) phosphonium bis(2,4,4-trimethylpentyl) phosphinate [TDTHP] [Phosph]. CEOS models such as predictive Soave−Redlich−Kwong (PSRK) coupled with cohesion factor gave better results when compared to the correlations such as Reid et al. (RR), Mchaweh et al. (MH), and the linear generalized model (LGM). In this work the PSRK equation of state (EOS) with the derived NSM1 alpha function and PSRK with original SRK alpha function were used for the prediction. PSRK EOS model with NSM1 alpha function and PSRK EOS with original SRK alpha function proved very accurate with average minimum deviation of 0.02 % to 0.44 % and 0.29 % to 0.66 % from experimental values for six ILs, respectively.

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“…To obtain better results, pure substances have been divided in some families and a quadratic generalized polynomial have been presented for each family [46]. The first derivative of the Joshipura et al function is:…”

Section: Alpha Functionsmentioning

confidence: 99%

The Patel–Teja and the Peng–Robinson EoSs performance when Soave alpha function is replaced by an exponential function

Forero

Velásquez

2012

Fluid Phase Equilibria

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Modeling vapour pressure using compound specific cohesion factor relationship

Cited by 13 publications

References 8 publications

Comparison of 20 Alpha Functions Applied in the Peng–Robinson Equation of State for Vapor Pressure Estimation

Comparison of 20 Alpha Functions Applied in the Peng–Robinson Equation of State for Vapor Pressure Estimation

Densities of Six Commercial Ionic Liquids: Experiments and Prediction Using a Cohesion Based Cubic Equation of State

The Patel–Teja and the Peng–Robinson EoSs performance when Soave alpha function is replaced by an exponential function

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