A Few Fluid Phase Predictions via Gibbs Ensemble Monte Carlo Simulation
2018-05
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A Few Fluid Phase Predictions via Gibbs Ensemble Monte Carlo Simulation
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2018-05
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Gathering data of the mutual miscibility of alkanes, alcohols, and water at a range of thermodynamic state points has long been of interest for the energy industry. Gathering liquid--liquid coexistence data experimentally is challenging at extreme conditions or time consuming if many molecular structures or thermodynamic state points are of interest. Simpler methods perform quite well when correlating experimental data, but often lack predictive capabilities, especially at extreme conditions. On the contrary, molecular simulations, with the aid of advanced sampling techniques and with the use of accurate force fields, can serve as a predictive method to study a variety of phase equilibria at different temperatures, pressures, and overall compositions. In this thesis, after some background is given, I present configurational-bias Monte Carlo simulations in the isothermal--isobaric Gibbs ensemble for various mixtures at various state points. The simulations show qualitative agreement with experiment, but the miscibility gaps are in general overestimated with respect to temperature.
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University of Minnesota Ph.D. dissertation. May 2018. Major: Chemistry. Advisor: J. Siepmann. 1 computer file (PDF); 101 pages.
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Harwood, David. (2018). A Few Fluid Phase Predictions via Gibbs Ensemble Monte Carlo Simulation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/218048.
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