Crystal structure prediction at finite temperatures
Abstract Crystal structure prediction is a central problem of crystallography and materials science, which until mid-2000s was considered intractable. Several methods, based on either energy landscape exploration or, more commonly, global optimization, largely solved this problem and enabled fully n...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-10-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-023-01120-6 |
| _version_ | 1797452121342214144 |
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| author | Ivan A. Kruglov Alexey V. Yanilkin Yana Propad Arslan B. Mazitov Pavel Rachitskii Artem R. Oganov |
| author_facet | Ivan A. Kruglov Alexey V. Yanilkin Yana Propad Arslan B. Mazitov Pavel Rachitskii Artem R. Oganov |
| author_sort | Ivan A. Kruglov |
| collection | DOAJ |
| description | Abstract Crystal structure prediction is a central problem of crystallography and materials science, which until mid-2000s was considered intractable. Several methods, based on either energy landscape exploration or, more commonly, global optimization, largely solved this problem and enabled fully non-empirical computational materials discovery. A major shortcoming is that, to avoid expensive calculations of the entropy, crystal structure prediction was done at zero Kelvin, reducing to the search for the global minimum of the enthalpy rather than the free energy. As a consequence, high-temperature phases (especially those which are not quenchable to zero temperature) could be missed. Here we develop an accurate and affordable solution, enabling crystal structure prediction at finite temperatures. Structure relaxation and fully anharmonic free energy calculations are done by molecular dynamics with a forcefield (which can be anything from a parametric forcefield for simpler cases to a trained on-the-fly machine learning interatomic potential), the errors of which are corrected using thermodynamic perturbation theory to yield accurate results with full ab initio accuracy. We illustrate this method by applications to metals (probing the P–T phase diagram of Al and Fe), a refractory covalent solid (WB), an Earth-forming silicate MgSiO3 (at pressures and temperatures of the Earth’s lower mantle), and ceramic oxide HfO2. |
| first_indexed | 2024-03-09T15:04:12Z |
| format | Article |
| id | doaj.art-a5fd87e415b6402aaa4629b72036e5d0 |
| institution | Directory Open Access Journal |
| issn | 2057-3960 |
| language | English |
| last_indexed | 2024-03-09T15:04:12Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Computational Materials |
| spelling | doaj.art-a5fd87e415b6402aaa4629b72036e5d02023-11-26T13:47:21ZengNature Portfolionpj Computational Materials2057-39602023-10-01911810.1038/s41524-023-01120-6Crystal structure prediction at finite temperaturesIvan A. Kruglov0Alexey V. Yanilkin1Yana Propad2Arslan B. Mazitov3Pavel Rachitskii4Artem R. Oganov5Moscow Institute of Physics and TechnologyMoscow Institute of Physics and TechnologyMoscow Institute of Physics and TechnologyMoscow Institute of Physics and TechnologyMoscow Institute of Physics and TechnologySkolkovo Institute of Science and Technology, Skolkovo Innovation CenterAbstract Crystal structure prediction is a central problem of crystallography and materials science, which until mid-2000s was considered intractable. Several methods, based on either energy landscape exploration or, more commonly, global optimization, largely solved this problem and enabled fully non-empirical computational materials discovery. A major shortcoming is that, to avoid expensive calculations of the entropy, crystal structure prediction was done at zero Kelvin, reducing to the search for the global minimum of the enthalpy rather than the free energy. As a consequence, high-temperature phases (especially those which are not quenchable to zero temperature) could be missed. Here we develop an accurate and affordable solution, enabling crystal structure prediction at finite temperatures. Structure relaxation and fully anharmonic free energy calculations are done by molecular dynamics with a forcefield (which can be anything from a parametric forcefield for simpler cases to a trained on-the-fly machine learning interatomic potential), the errors of which are corrected using thermodynamic perturbation theory to yield accurate results with full ab initio accuracy. We illustrate this method by applications to metals (probing the P–T phase diagram of Al and Fe), a refractory covalent solid (WB), an Earth-forming silicate MgSiO3 (at pressures and temperatures of the Earth’s lower mantle), and ceramic oxide HfO2.https://doi.org/10.1038/s41524-023-01120-6 |
| spellingShingle | Ivan A. Kruglov Alexey V. Yanilkin Yana Propad Arslan B. Mazitov Pavel Rachitskii Artem R. Oganov Crystal structure prediction at finite temperatures npj Computational Materials |
| title | Crystal structure prediction at finite temperatures |
| title_full | Crystal structure prediction at finite temperatures |
| title_fullStr | Crystal structure prediction at finite temperatures |
| title_full_unstemmed | Crystal structure prediction at finite temperatures |
| title_short | Crystal structure prediction at finite temperatures |
| title_sort | crystal structure prediction at finite temperatures |
| url | https://doi.org/10.1038/s41524-023-01120-6 |
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