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International Journal of Thermophysics

, Volume 35, Issue 9–10, pp 1661–1676 | Cite as

Freezing Transition Studies Through Constrained Cell Model Simulation

  • Michael Nayhouse
  • Joseph Sang-Il Kwon
  • Vincent R. Heng
  • Ankur M. Amlani
  • G. Orkoulas
Article
  • 148 Downloads

Abstract

In the present work, a simulation method based on cell models is used to deduce the fluid–solid transition of a system of particles that interact via a pair potential, \(\phi \left( r\right) \), which is of the form \(\phi \left( r\right) = 4\epsilon \left[ \left( \sigma /r\right) ^{2n}- \left( \sigma /r\right) ^{n}\right] \) with \(n=10\). The simulations are implemented under constant-pressure conditions on a generalized version of the constrained cell model. The constrained cell model is constructed by dividing the volume into Wigner–Seitz cells and confining each particle in a single cell. This model is a special case of a more general cell model which is formed by introducing an additional field variable that controls the number of particles per cell and, thus, the relative stability of the solid against the fluid phase. High field values force configurations with one particle per cell and thus favor the solid phase. Fluid–solid coexistence on the isotherm that corresponds to a reduced temperature of 2 is determined from constant-pressure simulations of the generalized cell model using tempering and histogram reweighting techniques. The entire fluid–solid phase boundary is determined through a thermodynamic integration technique based on histogram reweighting, using the previous coexistence point as a reference point. The vapor–liquid phase diagram is obtained from constant-pressure simulations of the unconstrained system using tempering and histogram reweighting. The phase diagram of the system is found to contain a stable critical point and a triple point. The phase diagram of the corresponding constrained cell model is also found to contain both a stable critical point and a triple point.

Keywords

Cell models Monte Carlo Phase transitions 

Notes

Acknowledgments

Financial support from NSF, CBET-0967291 is gratefully acknowledged. This material is based upon work supported by the NSF Graduate Research Fellowship DGE-0707424 to Michael Nayhouse. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant number TG-CCR120003.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Michael Nayhouse
    • 1
  • Joseph Sang-Il Kwon
    • 1
  • Vincent R. Heng
    • 1
  • Ankur M. Amlani
    • 1
  • G. Orkoulas
    • 1
  1. 1.Department of Chemical and Biomolecular EngineeringUniversity of California, Los AngelesLos AngelesUSA

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