基于自适应遗传算法和第一性原理计算的铁硅化物结构和磁性研究
Structures and magnetic properties of iron silicide from adaptive genetic algorithm and first-principles calculations
摘要：
采用基于自适应遗传算法的晶体结构预测方法，对二元铁硅化物的低能结构进行了系统的搜索。预测了36个形成能在50 meV/atom以内的结构（其中11个在20 meV以内）。这些低能量结构的磁性进行了研究。这些结构中的一些可以是无稀土永磁体的有希望的候选者。
英文摘要：
We performed a systematic search for low-energy structures of binary iron silicide over a wide range of compositions using the crystal structure prediction method based on adaptive genetic algorithm. 36 structures with formation energies within 50 meV/atom (11 of them are within 20 meV) above the convex hull formed by experimentally known stable structures are predicted. Magnetic properties of these low-energy structures are investigated. Some of these structures can be promising candidates for rare-earth-free permanent magnet.
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