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Allan D. Mackie

Publications and source records attributed to Allan D. Mackie.

3 recordsLinked to original sources

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

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.

cond-mat.soft↗

Dissipative particle dynamics with energy conservation: equilibrium properties

The stochastic differential equations for a model of dissipative particle dynamics, with both total energy and total momentum conservation at every time-step, are presented. The algorithm satisfies detailed balance as well as the fluctuation-dissipation theorems that ensure that the proper thermodynamic equilibrium can be reached. Macroscopic equilibrium probability distributions as well as equations of state for the model are also derived, and an appropriate definition of the free energy of the system is consistently proposed. Several simulations results of equilibrium as well as transport properties, including heat transport and thermal convection in a box, are shown as proof of the internal consistency of the model.

cond-mat.stat-mech↗

Dissipative Particle Dynamics with Energy Conservation: Dynamic and Transport Properties

Simulation results of the thermal conductivity ${\cal L}$ of Dissipative Particle Dynamics model with Energy Conservation (DPDE) are reported. We also present an analysis of the transport equations and the transport coefficients for DPDE based on a local equilibrium approximation. This approach is valid when the particle-particle thermal conductivity $λ$ and the friction coefficient $ζ$ are large. A qualitative derivation of the scaling form of the kinetic contribution of the transport of energy is derived, yielding two different forms for the kinetic contribution to the heat transport, depending on the value of $λ$. We find agreement between the theoretically predicted value for ${\cal L}$ and the simulation results, for large $λ$ and many particles interacting at one time. Significant differences are found for small number of interacting particles, even with large $λ$. For smaller values of $λ$, the obtained macroscopic thermal conductivity is dominated by diffusive transport, in agreement with the proposed scaling form.

cond-mat.stat-mech↗