Two-phase equilibria and nucleation barriers near a critical point

The influence of coherency strains on phase equilibria in a two-phase microstructure is examined for a binary or pseudobinary alloy system possessing a consolute critical point (chemical miscibility gap). The qualitative features of phase equilibria, including the limits of metastability (chemical spinodal), are shown to depend critically on the mechanical loading conditions and the geometric arrangement of the phases in the microstructure. If the elastic state of a phase in a two-phase coherent system is independent of the presence of the other phase, then the equilibrium characteristics usually associated with fluid systems should be observed, even though the system is nonhydrostatically stressed. If the elastic state of a phase depends upon the presence of the other phase, then the equilibrium characteristics that have come to be associated with coherent systems should be observed; tie lines and field lines do not coincide, the common tangent construction is invalid, and Gibbs phase rule is not applicable.

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Effects of Polydispersity on the Phase Behavior of Additive Hard Spheres in Solution

Molecules ◽

10.3390/molecules26061543 ◽

2021 ◽

Vol 26 (6) ◽

pp. 1543

Author(s):

Luka Sturtewagen ◽

Erik van der Linden

Keyword(s):

Phase Behavior ◽

Critical Point ◽

Volume Fraction ◽

Hard Spheres ◽

Second Virial Coefficient ◽

Two Phase ◽

Different Types ◽

Asymmetric Partitioning ◽

Average Size ◽

Liquid Liquid Phase Separation

The ability to separate enzymes, nucleic acids, cells, and viruses is an important asset in life sciences. This can be realised by using their spontaneous asymmetric partitioning over two macromolecular aqueous phases in equilibrium with one another. Such phases can already form while mixing two different types of macromolecules in water. We investigate the effect of polydispersity of the macromolecules on the two-phase formation. We study theoretically the phase behavior of a model polydisperse system: an asymmetric binary mixture of hard spheres, of which the smaller component is monodisperse and the larger component is polydisperse. The interactions are modelled in terms of the second virial coefficient and are assumed to be additive hard sphere interactions. The polydisperse component is subdivided into sub-components and has an average size ten times the size of the monodisperse component. We calculate the theoretical liquid–liquid phase separation boundary (the binodal), the critical point, and the spinodal. We vary the distribution of the polydisperse component in terms of skewness, modality, polydispersity, and number of sub-components. We compare the phase behavior of the polydisperse mixtures with their concomittant monodisperse mixtures. We find that the largest species in the larger (polydisperse) component causes the largest shift in the position of the phase boundary, critical point, and spinodal compared to the binary monodisperse binary mixtures. The polydisperse component also shows fractionation. The smaller species of the polydisperse component favor the phase enriched in the smaller component. This phase also has a higher-volume fraction compared to the monodisperse mixture.

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Thermodynamics and Machine Learning Based Approaches for Vapor–Liquid–Liquid Phase Equilibria in n-Octane/Water, as a Naphtha–Water Surrogate in Water Blends

Processes ◽

10.3390/pr9030413 ◽

2021 ◽

Vol 9 (3) ◽

pp. 413

Author(s):

Sandra Lopez-Zamora ◽

Jeonghoon Kong ◽

Salvador Escobedo ◽

Hugo de Lasa

Keyword(s):

Machine Learning ◽

Liquid Phase ◽

Phase Equilibria ◽

Aspen Plus ◽

Phase Region ◽

Two Phase ◽

Technical Literature ◽

Phase Liquid ◽

Liquid Vapor ◽

Vapor Liquid

The prediction of phase equilibria for hydrocarbon/water blends in separators, is a subject of considerable importance for chemical processes. Despite its relevance, there are still pending questions. Among them, is the prediction of the correct number of phases. While a stability analysis using the Gibbs Free Energy of mixing and the NRTL model, provide a good understanding with calculation issues, when using HYSYS V9 and Aspen Plus V9 software, this shows that significant phase equilibrium uncertainties still exist. To clarify these matters, n-octane and water blends, are good surrogates of naphtha/water mixtures. Runs were developed in a CREC vapor–liquid (VL_ Cell operated with octane–water mixtures under dynamic conditions and used to establish the two-phase (liquid–vapor) and three phase (liquid–liquid–vapor) domains. Results obtained demonstrate that the two phase region (full solubility in the liquid phase) of n-octane in water at 100 °C is in the 10-4 mol fraction range, and it is larger than the 10-5 mol fraction predicted by Aspen Plus and the 10-7 mol fraction reported in the technical literature. Furthermore, and to provide an effective and accurate method for predicting the number of phases, a machine learning (ML) technique was implemented and successfully demonstrated, in the present study.

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