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 magnet's 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).

中文翻译：

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稀土还原永磁体的计算设计

多尺度模拟是寻求新型永磁体的关键研究工具。从第一原理方法开始，可以应用一系列模拟方法来计算由新型磁性材料成分制成的磁体的最大可能矫顽场和预期能量密度积。适用于永磁体的富铁磁相可以通过自适应遗传算法找到。通过 ab initio 模拟计算的固有特性用作具有真实结构的永磁体磁滞特性的微磁模拟的输入。使用机器学习技术，可以优化磁体的结构，从而可以估计给定相的矫顽力和能量密度乘积的上限。计算了几种候选硬磁相的合成永磁体的结构特性关系。Fe3Sn0.75Sb0.25 得到以下对（矫顽力场 (T)、能量密度积 (kJ/m3)）：(0.49, 290), L10 FeNi: (1, 400), CoFe6Ta: (0.87, 425) , 和 MnAl: (0.53, 80)。