Ab initio Random Structure Searching

TL;DR

This paper introduces ab initio random structure searching (AIRSS), a straightforward and effective method for discovering stable atomic structures in materials using first-principles calculations, with diverse applications and new results.

Contribution

The paper presents AIRSS, a novel, simple approach for structure prediction using DFT, demonstrating its effectiveness across various material systems.

Findings

Successful discovery of new structures of iron clusters on graphene

Identification of stable silicon and boron clusters

Insights into hydrogen-rich lithium hydrides and polymeric nitrogen

Abstract

It is essential to know the arrangement of the atoms in a material in order to compute and understand its properties. Searching for stable structures of materials using first-principles electronic structure methods, such as density functional theory (DFT), is a rapidly growing field. Here we describe our simple, elegant and powerful approach to searching for structures with DFT which we call ab initio random structure searching (AIRSS). Applications to discovering structures of solids, point defects, surfaces, and clusters are reviewed. New results for iron clusters on graphene, silicon clusters, polymeric nitrogen, hydrogen-rich lithium hydrides, and boron are presented.