在CrTe中异常的磁相互作用:来自机器学习和实证模型的见解
F Zhang1,2, J Zhang1,2, D Fang3
1School of Microelectronics & State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.
Journal of physics. Condensed matter : an Institute of Physics journal
|December 13, 2023
概括
本研究使用机器学习和实证模型探索化 (CrTe) 的磁性特性. 揭示了不寻常的磁相互作用,包括远程力量,挑战了传统的理解.
科学领域:
- 凝聚物质物理学 凝聚物质物理学
- 材料科学 材料科学 材料科学
- 计算物理 计算物理
背景情况:
- 化 (CrTe) 呈现出微小的磁性异质,这表明可能存在复杂的磁性结构.
- 在CrTe内部的不寻常的磁相互作用通过数值模拟进行了有限的探索.
研究的目的:
- 为了研究散装和单层CrTe的磁性相位过渡.
- 用计算模型探索CrTe中存在的不寻常的磁相互作用.
主要方法:
- 采用机器学习模型来分析磁性.
- 利用经验模型进行比较分析.
- 研究了散装和单层 telluride.
主要成果:
- 揭示了CrTe.Te.中不寻常的磁相互作用的存在.
- 证明机器学习模型可以捕捉这些交互,与简单的经验模型不同.
- 观察到更遥远的磁矩表现出更强的相互作用,偏离了典型的行为.
结论:
- 机器学习为理解像CrTe.Te这样的材料中的复杂磁现象提供了一个强大的工具.
- 在CrTe中的磁相互作用是非常规的,远程力发挥着重要作用.
- 进一步研究CrTe独特的磁性质是有必要的.
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