Equation of state for confined fluids

Abstract

Fluids confined in small volumes behave differently than fluids in bulk systems. For bulk systems, a compact summary of the system’s thermodynamic properties is provided by equations of state. However, there is currently a lack of successful methods to predict the thermodynamic properties of confined fluids by use of equations of state, since their thermodynamic state depends on additional parameters introduced by the enclosing surface. In this work, we present a consistent thermodynamic framework that represents an equation of state for pure, confined fluids. The total system is decomposed into a bulk phase in equilibrium with a surface phase. The equation of state is based on an existing, accurate description of the bulk fluid and uses Gibbs’ framework for surface excess properties to consistently incorporate contributions from the surface. We apply the equation of state to a Lennard-Jones spline fluid confined by a spherical surface with a Weeks–Chandler–Andersen wall-potential. The pressure and internal energy predicted from the equation of state are in good agreement with the properties obtained directly from molecular dynamics simulations. We find that when the location of the dividing surface is chosen appropriately, the properties of highly curved surfaces can be predicted from those of a planar surface. The choice of the dividing surface affects the magnitude of the surface excess properties and its curvature dependence, but the properties of the total system remain unchanged. The framework can predict the properties of confined systems with a wide range of geometries, sizes, interparticle interactions, and wall–particle interactions, and it is independent of ensemble. A targeted area of use is the prediction of thermodynamic properties in porous media, for which a possible application of the framework is elaborated.

Estimation of the Compressibility Factor of Nanoconfined Alkanes along Vapor–Liquid Coexistence

“…The fluid pressure–volume–temperature ( PVT ) properties directly influence the fluid compressibility factor, Z . The common sources of Z -factor values are experimental measurements, equations of state, empirical correlations, − artificial intelligence (artificial neural network, ANN), and analytical techniques. − Moreover, equations of states in their current form apply to the bulk fluid only and not to the fluids confined at the nanoscale. − One major challenge in the development of cubic equations of states for confined systems is that the experimental characterization of fluids in nanogeometries is difficult . Challenges associated with the validation of the equation of state are an issue for all types of equations of state that depend on parameters obtained from experiments .…”

“…33−36 One major challenge in the development of cubic equations of states for confined systems is that the experimental characterization of fluids in nanogeometries is difficult. 37 Challenges associated with the validation of the equation of state are an issue for all types of equations of state that depend on parameters obtained from experiments. 38 Moreover, critical insight into the behavior of alkane is important to the reservoir and the chemical engineering calculations that deal with gas as one of the main phases.…”

Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids

“…The effect of confinement on fluid properties is difficult to predict, even using well-established models of fluids and state-of-the-art molecular simulations. − The presence of boundaries, wall–fluid interactions, and confinement disrupt the local structure of the fluid, which in turn affects fluid properties. Of particular interest is the ability to predict fluid transport properties in porous environments for applications ranging from separation, , catalysis, − battery development, , and subsurface sequestration and energy extraction. ,,, …”