Global exploration of the energy landscape of solids on the ab initio level

TL;DR

This paper introduces a method for global exploration of solid energy landscapes directly at the ab initio level, improving the accuracy of predicting stable crystal structures.

Contribution

The authors develop an approach to perform global structure searches using ab initio energy functions, avoiding reliance on empirical potentials.

Findings

Successfully explored LiF energy landscape at the ab initio level

Identified relevant crystalline modifications during the search

Demonstrated the method's effectiveness in structure prediction

Abstract

Predicting which crystalline modifications can be present in a chemical system requires the global exploration of its energy landscape. Due to the large computational effort involved, in the past this search for sufficiently stable minima has been performed employing a variety of empirical potentials and cost functions followed by a local optimization on the ab initio level. However, this entails the risk of overlooking important modifications that are not modeled accurately using empirical potentials. In order to overcome this critical limitation, we develop an approach to employ ab initio energy functions during the global optimization phase of the structure prediction. As an example, we perform a global exploration of the landscape of LiF on the ab initio level and show that the relevant crystalline modifications are found during the search.