Q I Zhang, Amitava Choudhury, Aleksandr V Chernatynskiy
{"title":"面向刚体晶体的对称性晶体结构预测方法。","authors":"Q I Zhang, Amitava Choudhury, Aleksandr V Chernatynskiy","doi":"10.1088/1361-648X/ad9f07","DOIUrl":null,"url":null,"abstract":"<p><p>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 metastable 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 (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.</p>","PeriodicalId":16776,"journal":{"name":"Journal of Physics: Condensed Matter","volume":" ","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A symmetry-oriented crystal structure prediction method for crystals with rigid bodies.\",\"authors\":\"Q I Zhang, Amitava Choudhury, Aleksandr V Chernatynskiy\",\"doi\":\"10.1088/1361-648X/ad9f07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 metastable 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 (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.</p>\",\"PeriodicalId\":16776,\"journal\":{\"name\":\"Journal of Physics: Condensed Matter\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Physics: Condensed Matter\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-648X/ad9f07\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PHYSICS, CONDENSED MATTER\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physics: Condensed Matter","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1088/1361-648X/ad9f07","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PHYSICS, CONDENSED MATTER","Score":null,"Total":0}
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: Li3PS4and Na6Ge2Se6, treating PS4as a tetrahedral rigid body and Ge2Se6as 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 Li3PS4structure and a potential metastable structure for Na6Ge2Se6that 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.
期刊介绍:
Journal of Physics: Condensed Matter covers the whole of condensed matter physics including soft condensed matter and nanostructures. Papers may report experimental, theoretical and simulation studies. Note that papers must contain fundamental condensed matter science: papers reporting methods of materials preparation or properties of materials without novel condensed matter content will not be accepted.