二维 Heisenberg 型磁体转变温度的自动计算
Automatic Calculation of the Transition Temperatures for two-dimensional Heisenberg type Magnets
AI总结：
本文提出一种基于第一性原理、从结构自动到 TM 的 Heisenberg 型二维磁体计算流程，并结合 Monte Carlo 与高通量筛选揭示 CrTe2 磁性调控及六种高 TM Cr 硫族化合物。
摘要：
二级磁转变温度（TM）的理论预测过去十分困难。在此，我们针对有效哈密顿量遵循 Heisenberg 模型的二维（2D）磁体，开发了一种基于第一性原理、从结构到 TM 的全自动方法。可计算至任意近邻壳层的 Heisenberg 交换作用被传递到 Monte Carlo 计算中。以 Cr 基磁体作为示例，我们从两个方面展示该方法是研究二维磁体的有力工具。首先，考虑长程交换作用使我们能够识别悬浮 CrTe2 单层中的自旋阻挫，而异质结构计算表明，如果将单层 CrTe2 生长在各种二维衬底上，其铁磁性可以恢复。其次，我们实现了对通过随机结构搜索发现的新型磁体的高通量筛选，筛选出六种具有高 TM 的二维 Cr 硫族化合物。我们的工作为二维磁体研究提供了新的见解，并有助于加快磁性材料数据挖掘的步伐。
英文摘要：
Theoretical prediction of the 2nd-order magnetic transition temperature (TM) used to be arduous. Here, we develop a first principle-based, fully automatic structure-to-TM method for two-dimensional (2D) magnets whose effective Hamiltonians follow the Heisenberg model. The Heisenberg exchanges, which can be calculated to an arbitrary shell, are transferred into the Monte Carlo calculation. Using Cr-based magnets as the showcases, we show that our method is a powerful tool to study the 2D magnets in two aspects. First, considering long-range exchanges enables us to identify the spin frustration in the suspended CrTe2 monolayer, whereas the heterostructure calculations reveal that the ferromagnetism can be recovered if the monolayer CrTe2 is grown onto various 2D substrates. Second, we realize a high-throughput screening of novel magnets discovered by random structure searches. Six 2D Cr chalcogenides are selected to have high TM. Our work provides a new insight for the study of 2D magnets and helps accelerate the pace of magnetic materials data-mining.
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