Statistical Mechanics of Density- and Temperature-Dependent Potentials: Application to Condensed Phases within GenDPDE

TL;DR

This paper develops a local thermodynamic model within GenDPDE to accurately simulate thermodynamic properties of liquids and supercritical fluids at the mesoscale, incorporating thermal fluctuations and density-temperature dependence.

Contribution

It introduces a novel LTh model for GenDPDE that captures thermodynamic behavior of condensed phases, validated against argon data, and discusses its analytical and approximation-based predictions.

Findings

The LTh model accurately reproduces argon thermodynamics at various states.

Analytical pressure and energy equations derived from the model are validated.

HNC approximation's applicability to GenDPDE radial distribution functions is assessed.

Abstract

Coarse-grain Lagrangian methods, such as Dissipative Particle Dynamics ( Hoogerbrugge et al., EPL, 1992), are suitable for describing mesoscopic fluid systems that include thermal fluctuations. However, the realistic simulation of liquids using these methods represents a longstanding problem. In this work, we develop a local thermodynamic (LTh) model for the description of condensed phases within the framework of the Generalized Dissipative Particle Dynamics with Energy Conservation (GenDPDE) method (Bonet Avalos et al., PCCP 2019). Such a model is appropriate for the analysis of liquids, due to the explicit account of the thermal expansion coefficient and isothermal compressibility at the mesoscale. We demonstrate the accuracy of the LTh model by examining the thermodynamic properties of argon at both liquid and supercritical conditions, through equilibrium simulations performed around two key reference states (125.7 K, 85.31 MPa, 1419.7 kg/m3 for liquid Ar, and 418.8 K, 85.31 MPa, 695.99 kg/m3 for supercritical Ar). Remarkably, we show that the model is also valid over a range of thermodynamic conditions near the reference states, allowing a correct description of the physics of systems with spatial variations in density and temperature. We further derive analytical expressions for the macroscopic pressure and energy equations of state based on the model parameters, discussing their validity and limitations. We demonstrate that, even at the mean-field level, accurately capturing local particle arrangements is essential for predicting macroscopic thermodynamic properties from mesoscopic data. We also assess the applicability of the HNC approximation in predicting the radial distribution function of the GenDPDE system, exploring its strengths and limitations. With the LTh model, GenDPDE offers a dependable and versatile tool for analysing condensed phases through coarse-grain techniques.