STATISTICAL MECHANICS OF COARSE-GRAIN SYSTEMS WITH DENSITY- AND TEMPERATURE-DEPENDENT POTENTIALS: APPLICATION TO GENERALIZED DISSIPATIVE PARTICLE DYNAMICS
In this thesis, we present several enhancements of the Generalized Dissipative Particle Dynamics with Energy Conservation (GenDPDE) mesoscopic simulation method (J. Bonet Avalos et al., Phys. Chem. Chem. Phys. 2019, 21, 24891). In the first part of the work, we focus on the development of a consistent theoretical framework for the description of the dynamic coupling between energy and mass transport at the mesoscale. We validate the extended GenDPDE-M algorithm by investigating the Ludwig-Soret effect in a supercritical binary mixture, demonstrating that the method is capable of reproducing and, crucially, controlling the strength of this phenomenon, through a suitable tuning of the model parameters. In the second part of this work, we deal with the analysis of liquid systems using GenDPDE. We show that the traditional GenDPDE approach fails to correctly reproduce liquid phase behavior, due to an inadequate evaluation of the particle volume. We thus propose a physically justified solution to this issue, which allows us to recover meaningful results. Subsequently, we develop a novel thermodynamic model, optimized for the description of liquids at the mesoscale. This model allows us to accurately simulate the behavior of liquid argon in a range of thermodynamic conditions that is of practical interest. From a theoretical perspective, we also investigate the application of Equilibrium Statistical Mechanics to density- and temperature-dependent many-body potentials, representing a novelty in the field of liquid theory. With the advancements proposed herein, GenDPDE becomes a general tool for the analysis of complex multiphase, multicomponent systems.
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