A Genetic Algorithm For Convex Hull Optimisation

Abstract

Computationally efficient and automated generation of convex hulls is desirable for high throughput materials discovery of thermodynamically stable multi-species crystal structures. A convex hull genetic algorithm is proposed that uses methodology adapted from multi-objective optimisation techniques to optimise the convex hull itself as an object, enabling efficient discovery of convex hulls for N >= 2 species. This method, when tested on a LiSi system utilising pre-trained machine learned potentials, was found to be able to efficiently discover reported structures as well as new potential LiSi candidate structures.