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Autocorrelation functions for phase separation in ternary mixtures.

Sanjay Puri1, Deepak Kumar

  • 1School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067, India.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 17, 2004
PubMed
Summary

We studied domain growth in ternary mixtures using simulations and analytical models. Our findings link aging properties to domain size distribution, showing good agreement between numerical and analytical results.

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Area of Science:

  • Physics
  • Materials Science
  • Chemistry

Background:

  • Domain growth is crucial in understanding phase transitions in mixtures.
  • Autocorrelation functions are key to characterizing this growth dynamics.

Purpose of the Study:

  • To investigate domain growth in ternary mixtures.
  • To model and analyze autocorrelation functions governing this process.

Main Methods:

  • Monte Carlo simulations of the spin-1 Blume-Emery-Griffiths model with spin-exchange kinetics.
  • Analytical modeling using the continuous-time random walk formalism.

Main Results:

  • Autocorrelation functions were calculated numerically and analytically.
  • The aging property was linked to the time-dependent domain-size distribution.

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  • Analytical predictions closely matched simulation data.

    • Conclusions:

    • The continuous-time random walk model effectively describes domain growth dynamics.
    • Aging behavior is intrinsically tied to how domain sizes evolve over time.
    • The study validates analytical approaches against detailed numerical simulations.