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

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: Li<sub>3</sub>PS<sub>4</sub>and Na<sub>6</sub>Ge<sub>2</sub>Se<sub>6</sub>, treating PS<sub>4</sub>as a tetrahedral rigid body and Ge<sub>2</sub>Se<sub>6</sub>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 Li<sub>3</sub>PS<sub>4</sub>structure and a potential stable structure for Na<sub>6</sub>Ge<sub>2</sub>Se<sub>6</sub>that exhibits significantly lower energy than the observed phase, as evaluated by density functional theory 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 athttps://github.com/ColdSnaap/sgrcsp.git.

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Publication Details

Journal
Journal of Physics Condensed Matter
Published
2024-12-13
DOI
https://doi.org/10.1088/1361-648x/ad9f07
Citations
1
Primary Topic
Crystallography and molecular interactions
Type
article
Field-Weighted Citation Impact
0.44

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article

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

Amitava Choudhury, Aleksandr Chernatynskiy, Qi Zhang
1 citations
Journal of Physics Condensed Matter
Crystallography and molecular interactions
0.44
article

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

Amitava Choudhury, Aleksandr Chernatynskiy, Qi Zhang
article en
1 citations

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: Li<sub>3</sub>PS<sub>4</sub>and Na<sub>6</sub>Ge<sub>2</sub>Se<sub>6</sub>, treating PS<sub>4</sub>as a tetrahedral rigid body and Ge<sub>2</sub>Se<sub>6</sub>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 Li<sub>3</sub>PS<sub>4</sub>structure and a potential stable structure for Na<sub>6</sub>Ge<sub>2</sub>Se<sub>6</sub>that exhibits significantly lower energy than the observed phase, as evaluated by density functional theory 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 athttps://github.com/ColdSnaap/sgrcsp.git.

Journal of Physics Condensed MatterVol. 37(9)
Missouri University of Science and Technology (US)
National Science Foundation
Affordable and clean energy
Openalex Percentile: Top 26%
Crystallography and molecular interactions
0.44
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