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energy starts to diverge from the molecular dynamics one as we move to lower pressures. Traditionally, the Monte Carlo has a weak performance (Kofke, 1993) with simulation of systems at low density (gas phase) and strongly associating fluids, in which molecules can find each other to bond. In other words, there are regions of phase space having a large contribution to the properties of the system, but the simulation cannot find them. In our case we believe that this discrepancy between Monte Carlo simulation and molecular dynamics is problem is attributed to the nature of the Monte Carlo simulation. In the Metropolis algorithm, the criterion of the acceptance of a random generated configuration depends on its energy, since the fixed variables in the canonical ensemble are the number of particles, volume and temperature. We believe that the problem is that the Markov chain process does not properly represent the statistical distribution of states for energy particularly for low densities. 104 0 340 320 300 280 260 240 220 0 200 400 600 800 1000 1200 1400 340 320 300 280 260 240 220 1200 1400 5.00MPa 7.00Mpa 7.5MPa 8.00MPa 10.00MPa 2.00MPa 200 400 600 800 1000 d(Kg/m3) Figure 7-7: Phase diagram for carbon dioxide the blues marks indicate the points we performed molecular simulations at low densities T(K)PDF Image | MOLECULAR SIMULATION STUDIES IN THE SUPERCRITICAL REGION
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