Efficient prediction of thermodynamic properties of quadrupolar fluids from simulation of a coarse-grained model: The case of carbon dioxide

TL;DR

This paper presents a Monte Carlo simulation approach using a coarse-grained model to accurately predict thermodynamic properties of quadrupolar fluids like carbon dioxide, improving upon previous methods by including quadrupolar effects.

Contribution

The study introduces a coarse-grained model incorporating quadrupolar interactions and demonstrates its effectiveness in predicting thermodynamic properties of quadrupolar fluids, especially carbon dioxide.

Findings

Critical parameters depend linearly on quadrupolar parameter q

Model achieves excellent agreement with experimental data

Perturbation Theory in MSA is less accurate near critical points

Abstract

Monte Carlo simulations are presented for a coarse-grained model of real quadrupolar fluids. Molecules are represented by particles interacting with Lennard-Jones forces plus the thermally averaged quadrupole-quadrupole interaction. The properties discussed include the vapor-liquid coexistence curve, the vapor pressure along coexistence, and the surface tension. The full isotherms are also accessible over a wide range of temperatures and densities. It is shown that the critical parameters (critical temperature, density, and pressure) depend almost linearly on a quadrupolar parameter $q=Q^{*4} /T^*$, $Q^*$ is the reduced quadrupole moment of the molecule and $T^*$ the reduced temperature. The model can be applied to a variety of small quadrupolar molecules. We focus on carbon dioxide as a test case, but consider nitrogen and benzene, too. Experimental critical temperature, density and quadrupolar moment are sufficient to fix the parameters of the model. The resulting agreement with experiments is excellent and marks a significant improvement over approaches which neglect quadrupolar effects. The same coarse-grained model was also applied in the framework of Perturbation Theory (PT) in the Mean Spherical Approximation (MSA). As expected, the latter deviates from the Monte Carlo results in the critical region, but is reasonably accurate at lower temperatures.