Phase-coexistence Simulations of Fluid Mixtures by the Markov Chain Monte Carlo Method Using Single-Particle Models

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Veröffentlicht in:arXiv.org (Sep 10, 2012), p. n/a
1. Verfasser: Li, Jun
Weitere Verfasser: Calo, Victor M
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Cornell University Library, arXiv.org
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022 |a 2331-8422 
024 7 |a 10.1016/j.jcp.2013.04.016  |2 doi 
035 |a 2082841496 
045 0 |b d20120910 
100 1 |a Li, Jun 
245 1 |a Phase-coexistence Simulations of Fluid Mixtures by the Markov Chain Monte Carlo Method Using Single-Particle Models 
260 |b Cornell University Library, arXiv.org  |c Sep 10, 2012 
513 |a Working Paper 
520 3 |a We present a single-particle Lennard-Jones (L-J) model for CO2 and N2. Simplified L-J models for other small polyatomic molecules can be obtained following the methodology described herein. The phase-coexistence diagrams of single-component systems computed using the proposed single-particle models for CO2 and N2 agree well with experimental data over a wide range of temperatures. These diagrams are computed using the Markov Chain Monte Carlo (MC) method based on the Gibbs-NVT ensemble. This good agreement validates the proposed simplified models. That is, with properly selected parameters, the single-particle models have similar accuracy in predicting gas-phase properties as more complex, state-of-the-art molecular models. To further test these single-particle models, three binary mixtures of CH4, CO2 and N2 are studied using a Gibbs-NPT ensemble. These results are compared against experimental data over a wide range of pressures. The single-particle model has similar accuracy in the gas phase as traditional models although its deviation in the liquid phase is greater. The simplified model improves the computational efficiency significantly, particularly in the case of high liquid density where the acceptance rate of the particle-swap trial move increases. The MC method based on Gibbs-NVT ensemble is a viable alternative to simulate phase-coexistence of fluid mixtures. We compare, at constant temperature and pressure, the Gibbs-NPT and Gibbs-NVT ensembles to analyze their performance differences and results consistency. As theoretically predicted, the agreement between the simulations implies that Gibbs-NVT can be used to validate Gibbs-NPT predictions when experimental data is not available. 
653 |a Monte Carlo simulation 
653 |a Markov analysis 
653 |a Liquid phases 
653 |a Model accuracy 
653 |a Markov chains 
653 |a Polyatomic molecules 
653 |a Binary mixtures 
653 |a Carbon dioxide 
653 |a Predictions 
653 |a Vapor phases 
653 |a Computing time 
653 |a Computer simulation 
700 1 |a Calo, Victor M 
773 0 |t arXiv.org  |g (Sep 10, 2012), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2082841496/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/1209.1973