Npj Comput. Mater.: 高通量计算—助力Heusler功能材料设计
海归学者发起的公益学术平台
分享信息，整合资源
交流学术，偶尔风月
伴随着人工智能与大数据技术的快速发展，数据量的急剧增加和对数据处理速度的更高要求，使得发展高效节能的数据存储技术与器件变得尤为重要。传统存储技术在满足这些需求方面面临挑战，因此，发展下一代高效节能的磁存储技术作为一种潜在的解决方案备受瞩目。新型磁存储技术应具有较高的数据密度、长期数据保存性和较低的功耗等特点，而其中的垂直磁隧道结（MTJ）作为重要的存储元件，在自旋电子学领域扮演着关键角色。此外，发展高效节能的数据存储技术对于实现in-memory computing（内存计算）以及neuromorphic computing（神经形态计算）等领域的突破同样具有重要意义。
High-throughput design of perpendicular magnetic anisotropy at quaternary Heusler and MgO interfaces
Sicong Jiang, Kesong Yang
Heusler alloys combined with MgO interfaces exhibit interfacial perpendicular magnetic anisotropy, making them attractive for energy-efficient spintronic technologies. However, finding suitable Heusler/MgO heterostructures with desired properties is challenging due to the vast range of compositions available and the complexity of interfacial structures, particularly for the emerging quaternary Heusler compounds. In this study, we report a high-throughput screening of quaternary-Heusler/MgO heterostructures for spintronic applications. By analyzing various materials descriptors, including formation energy, convex hull distance, magnetic ordering, lattice misfit, magnetic anisotropy constant, tunnel magnetoresistance, Curie temperature, and atomic site disordering, we identified 5 promising compounds out of 27,000 quaternary Heusler compounds. These compounds, namely IrCrAlTi, IrCrGaTi, IrMnZnTi, OsCrAlTa, and TaGaOsCr, show potential for designing energy-efficient perpendicular magnetic tunnel junctions. This work demonstrates an efficient approach using open quantum materials repositories, effective materials descriptors, and high-throughput computational techniques to accelerate the discovery of quaternary-Heusler-based functional materials.
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