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Computing absolute free energies of disordered structures by molecular simulation.

T Schilling1, F Schmid

  • 1Institut für Physik, Johannes Gutenberg-Universität, Staudinger Weg 7, D-55099 Mainz, Germany. schillit@uni-mainz.de

The Journal of Chemical Physics
|December 23, 2009
PubMed
Summary

This study introduces a novel Monte Carlo simulation method for directly calculating the free energy of disordered systems using thermodynamic integration. The technique efficiently samples integration paths for both lattice and complex off-lattice models.

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Area of Science:

  • Computational Physics
  • Statistical Mechanics
  • Materials Science

Background:

  • Calculating free energy in disordered systems is computationally challenging.
  • Existing methods often require complex approximations or extensive sampling.
  • Accurate free energy calculations are crucial for understanding material properties and phase transitions.

Purpose of the Study:

  • To develop a direct Monte Carlo simulation technique for computing free energy in disordered systems.
  • To establish an efficient method based on thermodynamic integration.
  • To demonstrate the applicability to both lattice and off-lattice models, with a focus on the latter.

Main Methods:

  • Utilizes thermodynamic integration with a Monte Carlo simulation approach.
  • Constructs an analytically solvable reference system from a representative configuration.
  • Proposes a specific Monte Carlo algorithm for efficient sampling of the thermodynamic integration path.

Main Results:

  • The presented method allows for direct computation of free energy in disordered systems.
  • Successfully applied to hard sphere liquids and hard disk solids with defects.
  • Demonstrates efficient sampling of the thermodynamic integration path for complex models.

Conclusions:

  • The developed Monte Carlo technique offers a direct and efficient route to free energy calculations.
  • The method is versatile, applicable to various disordered systems including challenging off-lattice models.
  • Provides a valuable tool for statistical mechanics and computational materials science research.