Monte Carlo simulation of the grand canonical ensemble

Yao, Jing-Shing; Greenkorn, Robert A.; Chao, Kwang‐Chu

doi:10.1080/00268978200101411

Cited by 75 publications

(36 citation statements)

References 9 publications

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“…21 Let z be the activity of the fluid molecules, defined so as to become asymptotic to the number density = N / V in the limit → 0. Then z / = exp͓͑ − id ͒ / kT͔ where id is the ideal part of .…”

Section: Systems and Simulation Methodsmentioning

confidence: 99%

“…The GCMC simulations for the bulk and confined systems are implemented as follows: first, each of the three trail actions ͑"move," "insert," "remove" a particle͒ is chosen at random with the equal probability; second, the chosen attempt is accepted or rejected according to the Boltzmann sampling algorithm; 21 and third the above procedures are repeated. We define the number of configurations generated in each simulation as the number of any trail actions.…”

Section: Systems and Simulation Methodsmentioning

confidence: 99%

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Phase equilibria and interfacial tension of fluids confined in narrow pores

Hamada

Koga

Tanaka

2007

The Journal of Chemical Physics

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Correlation between phase behaviors of a Lennard-Jones fluid in and outside a pore is examined over wide thermodynamic conditions by grand canonical Monte Carlo simulations. A pressure tensor component of the confined fluid, a variable controllable in simulation but usually uncontrollable in experiment, is related with the pressure of a bulk homogeneous system in equilibrium with the confined system. Effects of the pore dimensionality, size, and attractive potential on the correlations between thermodynamic properties of the confined and bulk systems are clarified. A fluid-wall interfacial tension defined as an excess grand potential is evaluated as a function of the pore size. It is found that the tension decreases linearly with the inverse of the pore diameter or width.

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Section: Systems and Simulation Methodsmentioning

confidence: 99%

Section: Systems and Simulation Methodsmentioning

confidence: 99%

Phase equilibria and interfacial tension of fluids confined in narrow pores

Hamada

Koga

Tanaka

2007

The Journal of Chemical Physics

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“…The polar contribution to fluid pressure is extracted from the calculations on Stockmayer potential of the dipole strength of interest and zero dipole strength which is the Lennard-Jones potential. p(po1ar) = p(Stockmayer) -p(Lennard-Jones) (2) Yao (1981) prepared a table of interpolated values from his direct simulated data. The ranges of conditions are as follows g, = a, + a2/?…”

Section: Correlation Of Computer Simulated Polar Contribution To Fluimentioning

confidence: 99%

Chain-of-rotators equation of state. 2. Polar fluids

Masuoka¹,

Chao²

1984

Ind. Eng. Chem. Fund.

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Literature Cited Belyaev, V. D.: Slinko, M. M.; Timoshenko, V. I.; Slinko, M. G. Kinet. Katal. ia73. 14. BID . -. -, . . , -. -. Beiyaev, V. D.; Sllnko, M. M.: Tlmoshenko, V. I.; Slinko, M. G. Dokl. Akad. Belyaev, V. D.: Slinko, M. M.: Timoshenko, V. I.; Sllnko, M. G. Kinet. Katal. Nauk SSSR 1974, 274, 1098. 1975. 16. 555. Hiavacek, V.; Van Rompay, P. Chem. Eng. Sci. 1981, 36, 1587. Jensen, K. F.; Ray, W. H. Chem. Eng. Sci. 1980, 35. 2439. Kurtanjek, Z.; Shelntuch, M.: Luss, D. Ber. Bunsenges. Phys. Chem. 198Oa. Kurtanjek, 2.; Sheintuch, M.; Luss, D. J . Catal. 1980b, 66, 11. Ray, W. H.; Uppai, A.; Poore, A. E. Chem. Eng. Sci. 1874, 2 9 , 1330. Renola, G. T. Ph.D. Thesis, University of Illinois, 1980a. Renola, G. T.; Ziodas, A.; Schmitz, R. A. Ber. Bunsenges. Phys. Chem. Sault, A. G.; Masel, R. I. J . Catal. 1982, 73, 294. Schmitz. A. A.; DNetto, G. 0. AlChE National Meeting, 1982, Paper 59c. Sllnko, M. 0.; Slinko. M. M. Catal. Rev. 1978, 77, 119. Shelntuch, M.; Schmltz, R. A. Catal. Rev. 1977, 75, 107. Wicke, E.; Kumman, P.; Keil, W.; Schlefler, J. Ber. Gunsenges . Wys . Chem,

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“…There are other methods based on the simulation in the grand canonical ensemble, which allow to set the target chemical potential externally. Starting from the pioneering work of Norman and Filinov, 8 and by Adams 9,10 on the grand canonical simulation of fluids, other MC simulations in the grand canonical ensemble have been performed by Rowley et al, 11 by Yao et al, 12 and by Torrie and Valleau, 13 followed by modifications in the sampling method by Yau et al 14 Generally MC methods fit better for performing simulations in the grand canonical ensemble. This is because of the fact that insertion or deletion of the particles in the grand canonical ensemble simulation fits with the stochastic moves in MC, but they cannot easily be incorporated into the equations of motion in MD simulation.…”

Section: Introductionmentioning

confidence: 98%

Molecular dynamics simulation in the grand canonical ensemble

Eslami

Müller‐Plathe

2007

J Comput Chem

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An extended system Hamiltonian is proposed to perform molecular dynamics (MD) simulation in the grand canonical ensemble. The Hamiltonian is similar to the one proposed by Lynch and Pettitt (Lynch and Pettitt, J Chem Phys 1997, 107, 8594), which consists of the kinetic and potential energies for real and fractional particles as well as the kinetic and potential energy terms for material and heat reservoirs interacting with the system. We perform a nonlinear scaling of the potential energy parameters of the fractional particle, as well as its mass to vary the number of particles dynamically. On the basis of the equations of motion derived from this Hamiltonian, an algorithm has been proposed for MD simulation at constant chemical potential. The algorithm has been tested for the ideal gas, for the Lennard-Jones fluid over a wide range of temperatures and densities, and for water. The results for the low-density Lennard-Jones fluid are compared with the predictions from a truncated virial equation of state. In the case of the dense Lennard-Jones fluid and water our predicted results are compared with the results reported using other available methods for the calculation of the chemical potential. The method is also applied to the case of vapor-liquid coexistence point predictions.

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Monte Carlo simulation of the grand canonical ensemble

Cited by 75 publications

References 9 publications

Phase equilibria and interfacial tension of fluids confined in narrow pores

Phase equilibria and interfacial tension of fluids confined in narrow pores

Chain-of-rotators equation of state. 2. Polar fluids

Molecular dynamics simulation in the grand canonical ensemble

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