Thermodynamic and statistical consistency of vapor–liquid equilibrium data

Carrero-Mantilla, Javier; Ramírez-Ramírez, Diógenes; Suárez-Cifuentes, Julio Fernando

doi:10.1016/j.fluid.2015.12.035

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…), vapor-phase compositions are required, which is not the case for electrolyte systems. Hence, only the method based on residuals is used, as proposed in refs , . We use a thermodynamic model that has intrinsically embedded the following thermodynamic relations: The Gibbs–Duhem equation relates salt activity coefficients and osmotic coefficients (eq ) The modified Raoult law can be used to test the consistency of vapor pressures and solvent activity coefficient (eq ) The Gibbs–Helmholtz equation relates the derivatives of the activity coefficients with the enthalpies of solution (eqs and ) …”

Section: Internal Consistency Analysismentioning

confidence: 99%

Data Analysis for Electrolyte Systems: A Method Illustrated on Alkali Halides in Water

et al. 2021

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In the recent years, the need to improve the thermodynamic models, particularly making them more precise and predictable for complex systems, has increased [Industrial Requirements for Thermodynamics and Transport PropertiesHendriksE. Hendriks, E. Ind. Eng. Chem. Res.2010491113111141 Industrial Requirements for Thermodynamic and Transport PropertiesKontogeorgisG. Kontogeorgis, G. Ind. Eng. Chem. Res.20216049875013 The complexity of electrolyte systems is due to the strong interactions between ions, the hydration forces that take place during salt dissociation, and the physical forces at high concentrations of solute. Consequently, the existing thermodynamic electrolyte models show some limitations and are far from being completely optimized for industrial simulations. Thermodynamics based on electrolyte mixtures and mixed solvents requires further development and research [PolingB. E. Poling, B. E. The Properties of Gases and LiquidsMcGraw-Hill Education2001The EleTher Joint Industrial Project (JIP) aims at promoting research in this field. A practical workflow is under development where the first stage consists in analyzing the data. The present work is part of this larger scope and presents a strategy to analyze the internal and external consistency of experimental data for electrolyte mixtures. The focus is on alkali halide salts in water. Internal consistency allows testing the quality of data by confronting them to each other and using the thermodynamic relationships between these data. For that purpose, the data are confronted with a model that was initially optimized and the deviations are analyzed. For this purpose, the electrolyte non-random two-liquid (eNRTL) thermodynamic model was selected. Some deviations are attributed to the model inadequacy (high temperature or high molalities). Others are to be attributed to data inconsistencies. On the other hand, the objective of external consistency is to evaluate the consistency between different systems of the same family. The Bromley model is used for this purpose, as it contains a single adjustable parameter. Investigating the trend of this parameter with type of compound or with temperature may provide valuable information regarding the underlying physics, in addition to identifying outliers.

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Section: Internal Consistency Analysismentioning

confidence: 99%

Data Analysis for Electrolyte Systems: A Method Illustrated on Alkali Halides in Water

et al. 2021

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“…Some consistency tests are limited by various approximations intended to reduce the amount of data necessary for performing the test (e.g., excluding excess volume or excess enthalpy from consideration). VLE and other consistency tests have been widely discussed in the literature, and that discussion is still active[68,69,70].…”

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confidence: 99%

Validation of thermophysical data for scientific and engineering applications

Diky

Bazyleva

Paulechka

et al. 2019

The Journal of Chemical Thermodynamics

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High quality thermophysical property data are essential to many scientific and engineering applications. These data are produced at a high rate and are affected by a range of experimental and reporting error sources that often exceed stated uncertainties. As a result, critical evaluation is required to establish the limits of reliability in a quantified way. The present work describes reporting recommendations and property data validation methods developed and applied at the Thermodynamics Research Center at NIST through the use of the ThermoData Engine (TDE; SRD 103a/b) software. Examples are provided with an emphasis on various consistency checks, which may include the use of equations of state (EOS).

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