Phase Transitions and Hysteresis for a Simple Model Liquid Crystal by Replica-Exchange Monte Carlo Simulations.

Kenji Yasuoka,Paul E Brumby,Akie Kowaguchi

doi:10.3390/molecules26051421

Kenji Yasuoka, Paul E Brumby + Show 1 more

Open Access

https://doi.org/10.3390/molecules26051421

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Journal: Molecules (Basel, Switzerland)	Publication Date: Mar 5, 2021
Citations: 6	License type: CC BY 4.0

Affiliation: Keio University

Abstract

In this work, the advantages of applying the temperature and pressure replica-exchange method to investigate the phase transitions and the hysteresis for liquid-crystal fluids were demonstrated. In applying this method to the commonly used Hess–Su liquid-crystal model, heat capacity peaks and points of phase co-existence were observed. The absence of a smectic phase at higher densities and a narrow range of the nematic phase were reported. The identity of the crystalline phase of this system was found to a hexagonal close-packed solid. Since the nematic-solid phase transition is strongly first order, care must be taken when using this model not to inadvertently simulate meta-stable nematic states at higher densities. In further analysis, the Weighted Histogram Analysis Method was applied to verify the precise locations of the phase transition points.

Highlights

Despite the significant impact that liquid crystals have had in the development of portable display devices, there remains much that is incomplete in our understanding of their complex phase behavior
To validate our simulation set up and set a baseline from which to measure the precise phase transition points in this system, we first perform a series of conventional constant
To examine the phase transitions, we look for peaks in the heat capacity profiles

Summary

Introduction

Despite the significant impact that liquid crystals have had in the development of portable display devices, there remains much that is incomplete in our understanding of their complex phase behavior. The precise prediction of phase transition points is a challenging task when using molecular simulations. This is due to the fact that simulation trajectories may often become trapped in local minima rather than their most stable phase [1]. It is desirable to be able to capture the essential molecular properties that give rise to the multitude of different phases that are observed experimentally. The most common of these are the isotropic, nematic, and smectic phases. The isotropic phase is characterised by both random positioning and orientation. With decreasing temperature and increasing pressure, molecules gain orientational order [2]

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