AI 中文总结
本研究提出基于近邻壳层的磁构型筛选方法，可在DFT计算前识别近邻贡献的线性独立性，经Fe和MnF₂验证，能为可靠海森堡交换参数提取提供实用指导。
AI 中文摘要
磁交换相互作用的确定对于磁性材料的定量描述和预测建模至关重要。本研究提出一种基于近邻壳层的筛选方法，用于从密度泛函理论（DFT）计算中选取适合提取超出近邻范围的海森堡交换参数的磁构型。该方法仅利用结构信息，无需依赖磁构型的试错生成，即可在任何第一性原理计算前识别近邻壳层贡献的线性独立性。我们将该方法应用于两类代表性磁构型：随机自旋态和自旋螺旋，并通过对Fe和MnF₂的直接DFT拟合验证其预测结果。研究表明，仅当所有相关近邻壳层贡献线性独立时获得的参数才可迁移至其他磁构型。该方法为选取可靠交换参数提取的磁构型提供了实用指导，也可能惠及其他基于近邻壳层的模型。
英文摘要
The determination of magnetic exchange interactions is essential for the quantitative description and predictive modeling of magnetic materials. In this work, we present a neighbor-shell-based screening method for selecting magnetic configurations suitable for extracting Heisenberg exchange parameters beyond nearest-neighbor from density functional theory (DFT) calculations. Using only the structure, the proposed approach identifies the linear independence of neighbor-shell contributions before any first-principles calculations instead of relying on trial-and-error generation of magnetic configurations. We apply the proposed approach to two representative classes of magnetic configurations: random spin states and spin spirals, and validate its predictions against direct DFT fitting for Fe and MnF$_2$. We show that only parameters obtained when all relevant neighbor-shell contributions are linearly independent remain transferable to other magnetic configurations. The proposed method provides practical guidance for selecting magnetic configurations for reliable exchange-parameter extraction and may also benefit other neighbor-shell-based models.
