Structure Prediction of Atoms Adsorbed on Two-Dimensional Layer Materials: Method and Applications

Abstract

The adsorption of atoms is one of the efficient approaches for functionalizing two-dimensional (2D) layer materials with desirable properties. The structural knowledge of atoms adsorbed on 2D layer materials is crucial for understanding their functional performance. Here we propose a versatile method for predicting the structures of atoms adsorbed on 2D materials via the swarm-intelligence-based CALYPSO structure-prediction method. Several techniques are implemented to improve the efficiency of structure searching, including fixed adsorption sites, constraints of symmetry and distance during structure generation, and the constrained particle swarm-optimization algorithm for structure evolution. The method is successfully applied to investigate the well-studied systems of hydrogenated and oxidized graphene. The energetically most stable structures of single-sided hydrogenated graphene are predicted for different contents of hydrogen; altering the hydrogen content appears to effectively tune the band gap. A...