Determining state points through the radial distribution function of Yukawa fluids at equilibrium

Abstract

Based on our previous work [Fluid Phase Equilibria, 2023, 567, 113709], we here use the radial distribution function (RDF) to determine the state points (density and temperature) of a fluid under the Yukawa potential at equilibrium. The reduced density and reduced temperature are defined as ${\rho }^{*}=\rho {\sigma }^3$ and ${\beta }^{*}=1/T^{*}=ϵ/k_{B}T$, respectively. Through the Molecular Dynamics (MD) simulations, we obtain equilibrium configurations and use these data for building models via two methods. The first method establishes two empirical correlations for each potential considered, one between the heights of the first peaks of the RDFs and state points, as well as the other between the displacements of the first peaks of the RDFs and state points. Through these empirical correlations, we can determine the state points of new Yukawa fluid systems with 100% accuracy. The second method utilizes artificial neural network models to predict state points from the heights and displacements of the first peaks of the RDFs, achieving 100% accuracy when the predicted results are rounded to one decimal place. The success of these methods again demonstrates the feasibility of determining state points solely based on equilibrium configurations, is an extension from the Lennard-Jones fluids to the Yukawa potential related fluids.