Computational prediction of new magnetic materials
Электронный научный архив УРФУ
Информация об архиве | Просмотр оригинала| Поле | Значение | |
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Computational prediction of new magnetic materials
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| Автор |
Rahmanian, Koshkaki, S.
Allahyari, Z. Oganov, A. R. Solozhenko, V. L. Polovov, I. B. Belozerov, A. S. Katanin, A. A. Anisimov, V. I. Tikhonov, E. V. Qian, G. -R. Maksimtsev, K. V. Mukhamadeev, A. S. Chukin, A. V. Korolev, A. V. Mushnikov, N. V. Li, H. |
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| Тематика |
CHROMIUM COMPOUNDS
CRYSTAL STRUCTURE FORECASTING MAGNETIC MATERIALS MAGNETISM MAGNETS METALS COMPUTATIONAL PREDICTIONS CRYSTALS STRUCTURES HALF METALS HARD MAGNETIC MATERIAL HARD MAGNETS MATERIAL SCIENCE METALLICS METALS MATERIALS SIMULTANEOUS OPTIMIZATION SPIN CHANNELS EVOLUTIONARY ALGORITHMS |
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| Описание |
The discovery of new magnetic materials is a big challenge in the field of modern materials science. We report the development of a new extension of the evolutionary algorithm USPEX, enabling the search for half-metals (materials that are metallic only in one spin channel) and hard magnetic materials. First, we enabled the simultaneous optimization of stoichiometries, crystal structures, and magnetic structures of stable phases. Second, we developed a new fitness function for half-metallic materials that can be used for predicting half-metals through an evolutionary algorithm. We used this extended technique to predict new, potentially hard magnets and rediscover known half-metals. In total, we report five promising hard magnets with high energy product (|BH|MAX), anisotropy field (Ha), and magnetic hardness (κ) and a few half-metal phases in the Cr-O system. A comparison of our predictions with experimental results, including the synthesis of a newly predicted antiferromagnetic material (WMnB2), shows the robustness of our technique. © 2022 Author(s).
Russian Science Foundation, RSF, (19-72-30043) The theoretical study of ferromagnets and DFT + DMFT calculations were supported by the Russian Science Foundation (Grant No. 19-72-30043). We thank Dr. V. A. Mukhanov for assistance in high-pressure experiments and I. V. Blinov, P. Y. Plechov, and A. N. Vasilyev for their help in the initial stages of this project. |
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| Дата |
2024-04-22T15:53:45Z
2024-04-22T15:53:45Z 2022 |
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| Тип |
Article
Journal article (info:eu-repo/semantics/article) info:eu-repo/semantics/submittedVersion |
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| Идентификатор |
Rahmanian Koshkaki, S, Allahyari, Z, Oganov, AR, Solozhenko, VL, Polovov, IB, Belozerov, AS, Katanin, AA, Anisimov, VI, Tikhonov, EV, Qian, GR, Maksimtsev, KV, Mukhamadeev, AS, Chukin, AV, Korolev, AV, Mushnikov, NV & Li, H 2022, 'Computational prediction of new magnetic materials', Journal of Chemical Physics, Том. 157, № 12, 124704. https://doi.org/10.1063/5.0113745
Rahmanian Koshkaki, S., Allahyari, Z., Oganov, A. R., Solozhenko, V. L., Polovov, I. B., Belozerov, A. S., Katanin, A. A., Anisimov, V. I., Tikhonov, E. V., Qian, G. R., Maksimtsev, K. V., Mukhamadeev, A. S., Chukin, A. V., Korolev, A. V., Mushnikov, N. V., & Li, H. (2022). Computational prediction of new magnetic materials. Journal of Chemical Physics, 157(12), [124704]. https://doi.org/10.1063/5.0113745 0021-9606 Final All Open Access; Green Open Access https://hal.science/hal-03791608/document https://hal.science/hal-03791608/document http://elar.urfu.ru/handle/10995/132490 10.1063/5.0113745 85139104595 862365200002 |
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| Язык |
en
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| Права |
Open access (info:eu-repo/semantics/openAccess)
cc-by |
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| Формат |
application/pdf
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| Издатель |
American Institute of Physics Inc.
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| Источник |
The Journal of Chemical Physics
Journal of Chemical Physics |
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