Dynamic neighbours: a proposal of a tool to characterize phase transitions

Abstract

For molecular dynamics simulations of hard particles, we define dynamic neighbours as the distinct particles that collide with a given reference one during a specific time interval. This definition allows us to determine the distribution of the number of dynamic neighbours, its average, and its standard deviation. We will show that regardless of the time window used to identify dynamic neighbours, their distribution is correlated with diffusion coefficients, structure, and configurational entropy. Thus, it is likely that the distribution of the number of dynamic neighbours may be employed as another tool to gain insights into the dynamic behaviour of hard-core systems. We tested this approach on 2D and 3D systems consisting of monodisperse and binary mixtures of hard disks and spheres. Results show that implementing dynamic neighbours to define order parameters can sharpen the signals where transitions take place.

GRAPHICAL ABSTRACT

Keywords:

• Hard core potential
• fluid
• phase transition
• hexatic phase
• neighbours

Acknowledgements

We thank David P. Sanders and Michael Schmiedeberg for their valuable discussions. The authors appreciate the computing platform provided by the Laboratorio de Cómputo de Alto Rendimiento, under the coordination of Departamento de Matemáticas of Facultad de Ciencias, UNAM. The authors would like to thank Guillermo Vazquez for significant technical assistance. MLH acknowledges the hospitality of Universidad de Extremadura at Badajoz (where the final draft of this paper was completed) during his present sabbatical stay there.

Disclosure statement

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

Additional information

Funding

We acknowledge the support received through the project PAPIIT IN113923. GO is grateful for financial support through CONAHCyT project A1-S-9197. ASK was supported by the Chinese Academy of Sciences President's International Fellowship Initiative for Visiting Scientist grant No 2023VMB0013