An Improved Real--Space Genetic Algorithm for Crystal Structure and Polymorph Prediction

TL;DR

This paper introduces an enhanced genetic algorithm for crystal structure prediction that penalizes similar structures to increase diversity, leading to the discovery of new phases and improved prediction accuracy.

Contribution

The paper presents a novel genetic algorithm that improves structural diversity and accuracy in crystal prediction by penalizing similar structures during evolution.

Findings

Successfully predicted new zero-temperature phases of the Dzugutov potential

Enhanced structural diversity improved prediction quality

Discovered three previously unreported crystal phases

Abstract

Existing Genetic Algorithms for crystal structure and polymorph prediction can suffer from stagnation during evolution, with a consequent loss of efficiency and accuracy. An improved Genetic Algorithm (GA) is introduced herein which penalizes similar structures and so enhances structural diversity in the population at each generation. This is shown to improve the quality of results found for the theoretical prediction of simple model crystal structures. In particular, this method is demonstrated to find three new zero--temperature phases of the Dzugutov potential that have not been previously reported.