Genetic algorithms predict formation of exotic ordered configurations for two-component dipolar monolayers

TL;DR

This paper uses genetic algorithms to predict complex ordered structures in binary dipolar monolayers, revealing diverse configurations influenced by component asymmetry and concentration, with potential experimental validation.

Contribution

Introduces a genetic algorithm approach for unbiased prediction of equilibrium configurations in binary dipolar systems, expanding understanding of their structural diversity.

Findings

Identified a wide variety of ordered arrangements.

Complexity increases with component asymmetry and concentration.

Results align with potential experimental observations.

Abstract

We employ genetic algorithms (GA), which allow for an unbiased search for the global minimum of energy landscapes, to identify the ordered equilibrium configurations formed by binary dipolar systems confined on a plane. A large variety of arrangements is identified, the complexity of which grows with increasing asymmetry between the two components and with growing concentration of the small particles. The effects of the density are briefly discussed and a comparison with results obtained via conventional lattice-sum minimization is presented. Our results can be confirmed by experiments involving Langmuir monolayers of polystyrene dipolar spheres or super-para-magnetic colloids confined on the air-water interface and polarized by an external, perpendicular magnetic field.