通过高通量自旋螺旋计算获得计算二维材料数据库 (C2DB) 中的磁序

IF 9.4 1区 材料科学 Q1 CHEMISTRY, PHYSICAL
Joachim Sødequist, Thomas Olsen
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引用次数: 0

摘要

我们报告了二维材料中磁基态有序的高通量计算筛选。工作流程以自旋螺旋计算为基础,通过二维有序矢量 Q 得出磁有序。然后,我们加入自旋轨道耦合,提取共线结构的易轴和难轴,以及非共线结构中螺旋平面的方向。最后,对于所有预测的铁磁体,我们计算了 Dzyaloshinskii-Moriya 相互作用,并确定这些作用是否足够强大,以克服磁各向异性并稳定手性自旋螺旋基态。我们发现了 58 个铁磁体、21 个共线反铁磁体和 85 个非共线基态,其中 15 个是由 Dzyaloshinskii-Moriya 相互作用驱动的手性自旋螺旋。结果表明,在这些材料中,非共线阶实际上与共线阶一样常见,并强调了在报告新材料的磁性能时详细研究磁基态的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Magnetic order in the computational 2D materials database (C2DB) from high throughput spin spiral calculations

Magnetic order in the computational 2D materials database (C2DB) from high throughput spin spiral calculations

We report high throughput computational screening for magnetic ground state order in 2D materials. The workflow is based on spin spiral calculations and yields the magnetic order in terms of a two-dimensional ordering vector Q. We then include spin-orbit coupling to extract the easy and hard axes for collinear structures and the orientation of spiral planes in non-collinear structures. Finally, for all predicted ferromagnets we compute the Dzyaloshinskii-Moriya interactions and determine whether or not these are strong enough to overcome the magnetic anisotropy and stabilise a chiral spin spiral ground state. We find 58 ferromagnets, 21 collinear anti-ferromagnets, and 85 non-collinear ground states of which 15 are chiral spin spirals driven by Dzyaloshinskii-Moriya interactions. The results show that non-collinear order is in fact as common as collinear order in these materials and emphasise the need for detailed investigation of the magnetic ground state when reporting magnetic properties of new materials.

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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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