Exploration of a new reconstructed structure on GaN(0001) surface by Bayesian optimization

TL;DR

This study employs Bayesian optimization combined with density-functional calculations to discover a novel, stable GaN(0001) surface structure with unique adsorbate arrangements, advancing understanding of semiconductor surface configurations.

Contribution

The paper introduces a Bayesian optimization approach to efficiently identify stable surface structures of GaN(0001), revealing a new structure that defies traditional symmetry assumptions.

Findings

Identified a low-energy GaN(0001) surface structure with unique adsorbate arrangement.

The structure satisfies local electron counting rules and exhibits characteristics of nitride semiconductors.

Successfully explored hundreds of thousands of candidate structures to find the optimal configuration.

Abstract

GaN(0001) surfaces with Ga- and H-adsorbates are fundamental stages for epitaxial growth of semiconductor thin films. We explore stable surface structures with nanometer scale by the density-functional calculations combined with Bayesian optimization, and succeed to reach a single structure with satisfactorily low mixing enthalpy among hundreds of thousand possible candidate structures. We find that the obtained structure is free from any postulated high symmetry previously introduced by human intuition, satisfies electron counting rule locally, and shows new adsorbate arrangement, reflecting characteristics of nitride semiconductors.