A symmetry-oriented crystal structure prediction method for crystals with rigid bodies

TL;DR

This paper introduces a symmetry-oriented crystal structure prediction method optimized for compounds with rigid molecules, successfully identifying known and novel phases, and outperforming existing methods in predicting metastable structures.

Contribution

The paper presents a new CSP approach tailored for rigid bodies, demonstrating improved prediction of metastable phases and providing open-source Python implementation.

Findings

Successfully predicted experimental structures of Li3PS4 and Na6Ge2Se6

Discovered new phases including a stannite-type Li3PS4

Outperformed USPEX in predicting metastable structures

Abstract

We have developed an efficient crystal structure prediction (CSP) method for desired chemical compositions, specifically suited for compounds featuring recurring molecules or rigid bodies. We applied this method to two metal chalcogenides: $\text{Li}_3\text{PS}_4$ and $\text{Na}_6\text{Ge}_2\text{Se}_6$, treating $\text{PS}_4$ as a tetrahedral rigid body and $\text{Ge}_2\text{Se}_6$ as an ethane-like dimer rigid body. Initial trials not only identified the experimentally observed structures of these compounds but also uncovered several novel phases, including a new stannite-type $\text{Li}_3\text{PS}_4$ structure and a potential metastable structure for $\text{Na}_6\text{Ge}_2\text{Se}_6$ that exhibits significantly lower energy than the observed phase, as evaluated by density functional theory (DFT) calculations. We compared our results with those obtained using USPEX, a popular CSP package leveraging genetic algorithms. Both methods predicted the same lowest energy structures in both compounds. However, our method demonstrated better performance in predicting metastable structures. The method is implemented with Python code which is available at https://github.com/ColdSnaap/sgrcsp.git.