Monte Carlo simulations of the blinking-checkers model for polyamorphic fluids

Abstract

The blinking-checkers model [F. Caupin and M. A. Anisimov, Phys. Rev. Lett, 127,185701 (2021)] is a minimal lattice model which has demonstrated that, in the meanfield approximation, it can reproduce the phenomenon of fluid polyamorphism. This model is a binary lattice-gas, in which each site has three possible states: empty, occupied with particles of type 1, and occupied with particles of type 2. Additionally, the two types of particles may interconvert from one to another. Equilibrium interconversion imposes a constraint that makes this model thermodynamically equivalent to a single-component system. In this work, Monte-Carlo simulations of the blinking-checkers model are performed, demonstrating polyamorphic phase behaviour. The locations of the liquid-liquid and liquid-gas critical points are found to be different from the meanfield predictions for this model with the same interaction parameters, as the phase behaviour is significantly affected by critical fluctuations. Based on the computed values of the critical exponents of the order parameter, susceptibility, correlation length, and surface tension, we confirm that the blinking-checkers model, for both liquid-gas and liquid-liquid equilibria, belongs to the three-dimensional Ising class of critical-point universality.

GRAPHICAL ABSTRACT

Keywords:

• Monte Carlo simulations
• binary-lattice model
• molecular interconversion
• fluid polyamorphism

Acknowledgments

The authors would like to thank Nikolay Shumovskyi for his assistance with the initial simulations. F.C. and M.A. appreciate the beneficial collaborations with the scientists at Universidad Complutense de Madrid. In particular, F.C. thanks José Luis F. Abascal for a fruitful collaboration and for his hospitality during visits in Madrid.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The research of S.V.B. was supported by NSF Award No. 1856496, and partially supported through the Bernard W. Gamson Computational Science Center at Yeshiva College. The research of T.J.L. and M.A.A. was partially supported by NSF award no. 1856479. FC acknowledges support from Agence Nationale de la Recherche, grant number ANR-19-CE30-0035-01.