Finding the stable structures of 2D hexagonal materials with Bayesian optimization: Beyond the structural relationship with 3D crystals in weakly-bonded binary systems

TL;DR

This paper uses Bayesian optimization and density-functional theory to discover stable 2D structures in binary metallic systems, revealing structures that differ from traditional 3D crystal relationships.

Contribution

It introduces a novel approach combining Bayesian optimization with DFT to predict 2D structures in binary systems, beyond known 3D structural relationships.

Findings

Optimized 2D Cu-Au structure with unique hexagonal ring configuration.

Structures of 2D Cu-X with X=Be, Zn, Pd show diverse ring arrangements.

Binary Lennard-Jones model explains the emergence of these structures.

Abstract

The graphene-graphite relationship in structural geometry is a basic principle to predict novel two-dimensional (2D) materials. Here, we demonstrate that this is not the case in binary metallic systems. We use the Bayesian optimization framework combined with the density-functional theory approach to determine the stable configuration of atomic species on a hexagonal plane. We show that the optimized structure of 2D Cu-Au exhibits the hexagonal lattice of a hexagonal ring of Cu atoms containing one Au atom, where the number of the Cu atoms is larger than that of the Au atoms in the unit cell, which is difficult to speculate from the atomic distribution of CuAu in the L1$_0$ structure. We also show that 2D Cu-$X$ with $X=$ Be, Zn, and Pd have hexagonal or elongated rings containing different atoms in the unit cell. Based on the binary Lennard-Jones model, we propose that such structures can appear for weakly-bonded systems located in between the phase-separated and strongly-bonded systems with the interatomic interaction energy between different species.