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Ring population statistics in an ice lattice model.

Ali Khosravi1, Jorge Lasave2, Sergio Koval3

  • 1International School for Advanced Studies (SISSA), I-34136 Trieste, Italy.

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|December 16, 2021
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We calculated the probability distribution of hexagonal six-site rings in disordered ice lattices. Results align with Monte Carlo simulations, aiding understanding of proton ordering transitions.

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Area of Science:

  • Condensed Matter Physics
  • Materials Science
  • Statistical Mechanics

Background:

  • Understanding the disordered state of ice is crucial for predicting its physical properties.
  • Proton ordering in ice lattices influences ferroelectric transitions.
  • Lattice models provide a framework for studying ice at a molecular level.

Purpose of the Study:

  • To calculate the distribution probability of hexagonal six-site rings in disordered cubic and hexagonal ice.
  • To compare theoretical mean-field results with simulation data.
  • To explore the implications for disorder-to-ferroelectric proton order transitions.

Main Methods:

  • Mean-field theory applied to ice lattice models.
  • Monte Carlo simulations of cubic and hexagonal ice.
  • Analysis of hexagonal six-site ring distributions.

Main Results:

  • The mean-field calculation accurately predicts the distribution of hexagonal six-site rings.
  • Simulations confirmed the theoretical distribution, with minor variations.
  • The findings provide insights into the disordered phase of ice.

Conclusions:

  • The study validates mean-field approaches for analyzing ice structures.
  • Results contribute to understanding the mechanisms driving ferroelectric proton ordering.
  • This work bridges theoretical calculations and simulation-based evidence in ice physics.