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تسجيل مستخدم جديدComputational Design of the Rare-Earth Reduced Permanent Magnets
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Multiscale simulation is a key research tool for the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density product of a magnet made from a novel magnetic material composition. Fe-rich magnetic phases suitable for permanent magnets can be found by adaptive genetic algorithms. The intrinsic properties computed by ab initio simulations are used as input for micromagnetic simulations of the hysteresis properties of permanent magnets with realistic structure. Using machine learning techniques, the magnets structure can be optimized so that the upper limits for coercivity and energy density product for a given phase can be estimated. Structure property relations of synthetic permanent magnets were computed for several candidate hard magnetic phases. The following pairs (coercive field (T), energy density product (kJ/m3)) were obtained for Fe3Sn0.75Sb0.25: (0.49, 290), L10 FeNi: (1, 400), CoFe6Ta: (0.87, 425), and MnAl: (0.53, 80).
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The development of permanent magnets containing less or no rare-earth elements is linked to profound knowledge of the coercivity mechanism. Prerequisites for a promising permanent magnet material are a high spontaneous magnetization and a sufficientl
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Computational design of more efficient rare earth/transition metal (RE-TM) permanent magnets requires accurately calculating the magnetocrystalline anisotropy (MCA) at finite temperature, since this property places an upper bound on the coercivity. H
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