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Original Articles

AZEOTROPE PREDICTION BY MONTE CARLO MOLECULAR SIMULATION

, &
Pages 673-688 | Published online: 06 Mar 2012
 

Abstract

This article presents a methodology for checking the existence of the azeotrope and computing its composition, density, and pressure at a given temperature by integrating chemical engineering insights with molecular simulation principles. Liquid-vapor equilibrium points are computed by molecular simulations using the Gibbs ensemble Monte Carlo (GEMC) method at constant volume. The appearance of the azeotropic point is marked by a shift of the equilibrium constant from one side of the unity to the other. After each GEMC simulation, an identity change move is derived in the grand canonical ensemble to progress towards the azeotrope along the equilibrium curve. The effectiveness of the proposed methodology is successfully tested for several binary Lennard-Jones mixtures reported in the literature.

Acknowledgments

The authors wish to thank P. Ungerer at Institut Français du Pétrole (IFP), France, for his useful comments and discussions about this work. They also thank the CALMIP supercomputer center for allocating computer resources to this project.

Notes

 = 0.025 and  = 0.975.

Subscript numbers follow the notation for uncertainty values (for example, 0.421217 means 0.4212 ± 0.0017).

* = reduced units (Frenkel and Smit, Citation2002).

Subscript numbers follow the notation for uncertainty values (for example, 0.420411 means 0.4204 ± 0.0011).

Subscript numbers follow the notation for uncertainty values (for example, 0.607019 means 0.6070 ± 0.0019).

a Pandit and Kofke (1999).

b Panagiotopoulos et al. (1988).

*In practice, to ensure an efficient convergence of the algorithm, the first steps are bounded to a maximum value, so that Z = min(Rand(Z H , Z L ) ; Z L (or Z H ) ± ΔZ max ). ΔZ max is taken here equal to 0.20.

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