Stable and metastable rare-earth-free permanent magnets from a database of predicted crystal structures
Source abstract
Abstract
With the recent developments in crystal structure prediction, databases of new (not previously synthesized) materials are being created. One of these databases contains more than a million entries with the distance to the Convex Hull predicted by crystal-graph attention networks. Hence, stable and metastable materials can be extracted and then investigated for any desired properties. A high-throughput and data-mining approach we previously developed to search for rare-earth-free permanent magnets was applied to these compounds. As a result, four promising candidates for novel rare-earth-free permanent magnets were discovered with high magnetization, high uniaxial magnetocrystalline anisotropy, and high Curie temperature - Ta3ZnFe8, AlFe2, Co3Ni2, and Fe3Ge. The materials were investigated in more detail and all were verified to be dynamically stable.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Magnetic Properties of Alloys · Magnetic and transport properties of perovskites and related materials · Hydrogen Storage and Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (74)
Show source-provided references
1. Skomski · 1999
2. European Commission · 2018
3. What Is Tesla’s Mystery Magnet, https://spectrum.ieee.org/permanent-magnet-tesla.
4. Engineering microstructure to improve coercivity of bulk MnBi magnet10.1016/j.jmmm.2022.169912 ↗
5. Optimizing composition in MnBi permanent magnet alloys10.1016/j.actamat.2019.10.003 ↗
6. Directly obtained τ-phase MnAl, a high performance magnetic material for permanent magnets10.1016/j.jssc.2016.02.031 ↗
7. One step towards MnAl-based permanent magnets - Differences in magnetic, and microstructural properties from an intermediate annealing step during synthesis10.1016/j.jssc.2019.03.035 ↗
8. Large magnetic anisotropy predicted for rare-earth-free Fe16−xCoxN2 alloys10.1103/PhysRevB.94.224424 ↗
9. The impact of carbon coating on the synthesis and properties of α-Fe16N2 powders10.1039/C6CP00737F ↗
10. Chemical synthesis of magnetic nanoparticles for permanent magnet applications10.1002/chem.201902916 ↗
11. Strongly exchange coupled core—Shell nanoparticles with high magnetic anisotropy: A strategy toward rare-earth-free permanent magnets10.1021/acs.chemmater.6b00623 ↗
12. A facile chemical synthesis of PrCo5 particles with high performance10.1016/j.jallcom.2019.151674 ↗
13. Dense arrays of cobalt nanorods as rare-earth free permanent magnets10.1039/C5NR07143G ↗
14. Combinatorial exploration of rare-earth-free permanent magnets: Magnetic and microstructural properties of Fe-Co-W thin films10.1063/1.4775581 ↗
15. Structure and magnetic properties of highly coercive L10 nanocomposite FeMnPt thin films10.1016/j.matchar.2019.04.028 ↗
16. Phase- and composition-tunable hard/Soft magnetic nanofibers for high-performance permanent magnet10.1021/acsanm.9b02470 ↗
17. A general strategy for synthesizing high-coercivity L10-FePt nanoparticles10.1039/C7NR04849A ↗
18. Inspired by nature: investigating tetrataenite for permanent magnet applications
19. High-throughput and data-mining approach to predict new rare-earth free permanent magnets10.1103/PhysRevB.101.094407 ↗
20. Data-driven design of a new class of rare-earth free permanent magnets10.1016/j.actamat.2021.116913 ↗
21. Fe2C- and Mn2(W/Mo)B4-based rare-earth-free permanent magnets as a result of the high-throughput and data-mining search10.1080/21663831.2022.2117576 ↗
22. Inorganic Crystal Structure Database, http://www2.fiz-karlsruhe.de/icsd_home.html.
23. High-throughput search for potential permanent magnet materials
24. USPEX—Evolutionary crystal structure prediction10.1016/j.cpc.2006.07.020 ↗
25. Crystal structure prediction via particle-swarm optimization
26. XtalOpt: An open-source evolutionary algorithm for crystal structure prediction10.1016/j.cpc.2010.07.048 ↗
27. Crystal structure prediction accelerated by Bayesian optimization
28. Crystal structure prediction via deep learning10.1021/jacs.8b03913 ↗
29. Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning10.1103/PhysRevB.99.064114 ↗
30. CALYPSO: A method for crystal structure prediction10.1016/j.cpc.2012.05.008 ↗
31. Crystal structure prediction of magnetic materials
32. Discovering rare-earth-free magnetic materials through the development of a database
33. Synergistic computational and experimental discovery of novel magnetic materials10.1039/D0ME00050G ↗
34. Xia · Proc. Natl. Acad. Sci. · 2022 · 119
35. Magnetic iron-cobalt silicides discovered using machine-learning
36. Crystal graph attention networks for the prediction of stable materials10.1126/sciadv.abi7948 ↗
37. Large-scale machine-learning-assisted exploration of the whole materials space
38. Large-scale machine-learning-assisted exploration of the whole materials space
39. Discovery of earth-abundant nitride semiconductors by computational screening and high-pressure synthesis10.1038/ncomms11962 ↗
40. First principles high throughput screening of oxynitrides for water-splitting photocatalysts10.1039/C2EE23482C ↗
41. Commentary: The materials project: A materials genome approach to accelerating materials innovation10.1063/1.4812323 ↗
42. P. Villars, H. Okamoto (Eds.), Fe-Ta Binary Phase Diagram 0-0.5 at.% Ta: Datasheet from “PAULING FILE Multinaries Edition – 2022” in SpringerMaterials, Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan, Copyright 2016 Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan. URL.
43. B. Predel, in: B. Predel (Ed.), Fe - Zn (Iron - Zinc): Datasheet from Landolt-Börnstein - Group IV Physical Chemistry · Volume 12C: “Dy - Er … Ir - Y” in SpringerMaterials, Springer-Verlag Berlin Heidelberg, http://dx.doi.org/10.1007/978-3-642-24778-1_46, Copyright 2013 Springer-Verlag Berlin Heidelberg. URL.
44. G. Balaji Kale, K. Bhanumurthy, S. Parakash Garg, Materials Science International Team, MSIT®, in: G. Effenberg (Ed.), Ta-Zn Binary Phase Diagram Evaluation · Phase diagrams, crystallographic and thermodynamic data: Datasheet from MSI Eureka in SpringerMaterials, MSI Materials Science International Services GmbH, Copyright 2005 MSI Materials Science International Services GmbH. URL.
45. P. Villars, H. Okamoto (Eds.), Fe-Ga Binary Phase Diagram 10-40 at.% Ga: Datasheet from “PAULING FILE Multinaries Edition – 2022” in SpringerMaterials, Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan, Copyright 2016 Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan. URL.
46. AFLOW: An automatic framework for high-throughput materials discovery10.1016/j.commatsci.2012.02.005 ↗
47. P. Villars, H. Okamoto (Eds.), Co-Ni Binary Phase Diagram 0-100 at.% Ni: Datasheet from “PAULING FILE Multinaries Edition – 2022” in SpringerMaterials, Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan, Copyright 2016 Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan. URL.
48. Magnetocrystalline anisotropy of Fe3Ge single crystal: Effect of pressure and Mn substitution for Fe10.1063/1.1768613 ↗
49. Electronic and magnetic properties of Si substituted Fe3Ge10.1063/1.4931574 ↗
50. Tuning magnetocrystalline anisotropy by cobalt alloying in hexagonal Fe3Ge110.1038/s41598-018-32577-x ↗
51. Rare-earth iron permanent magnets
52. Ab initio molecular dynamics for liquid metals10.1103/PhysRevB.47.558 ↗
53. Kresse · Comput. Mat. Sci. · 1996 · 6 · 1510.1016/0927-0256(96)00008-0 ↗
54. Blöchl · Phys. Rev. B · 1994 · 50 · 1795310.1103/PhysRevB.50.17953 ↗
55. Perdew · Phys. Rev. Lett. · 1996 · 77 · 386510.1103/PhysRevLett.77.3865 ↗
56. Synthesis of band and model Hamiltonian theory for hybridizing cerium systems10.1103/PhysRevB.36.3809 ↗
57. Full-potential electronic structure method10.1007/978-3-642-15144-6_6 ↗
58. Blöchl · Phys. Rev. B · 1994 · 49 · 1622310.1103/PhysRevB.49.16223 ↗
59. The electronic structure of h.c.p. Ytterbium10.1016/0038-1098(71)90313-9 ↗
60. Monkhorst · Phys. Rev. B · 1976 · 13 · 518810.1103/PhysRevB.13.5188 ↗
61. Eriksson · 2017
62. Exchange parameters of strongly correlated materials: Extraction from spin-polarized density functional theory plus dynamical mean-field theory10.1103/PhysRevB.91.125133 ↗
63. Exchange interactions and spin-wave stiffness in ferromagnetic metals10.1088/0305-4608/14/7/007 ↗
64. Szilva · 2022
65. Magnetic anisotropy — How much is enough for a permanent magnet?10.1016/j.scriptamat.2015.09.021 ↗
66. First principles phonon calculations in materials science10.1016/j.scriptamat.2015.07.021 ↗
67. Command-line tools for plotting and analysis of periodic ab initio calculations10.21105/joss.00717 ↗
68. VESTA3 for three-dimensional visualization of crystal, volumetric and morphology data10.1107/S0021889811038970 ↗
69. Computational screening of Fe-Ta hard magnetic phases10.1103/PhysRevB.101.014426 ↗
70. Tunable magnetic order in transition metal doped, layered, and anisotropic Bi2O2Se: Competition between exchange interaction mechanisms
71. Constituents of magnetic anisotropy and a screening of spin–orbit coupling in solids10.1016/j.ssc.2014.06.003 ↗
72. The origin of perpendicular magneto-crystalline anisotropy in L10–FeNi under tetragonal distortion
73. Band-filling effect on magnetic anisotropy using a Green’s function method10.1103/PhysRevB.92.014423 ↗
74. Large magnetic anisotropy and strain induced enhancement of magnetic anisotropy in monolayer TaTe210.1039/C7CP04445C ↗