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Updated: Mar 8, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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通过随机朗格温模型对磁纳米粒子属性的数据驱动和物理信息估计

Ebrahim Azizi1, Hanlei Wang2, Hansong Zuo3

  • 1Texas Tech University, Lubbock, TX 79409, United States, Lubbock, Texas, 79409, United States.

Nanotechnology
|March 6, 2026
PubMed
概括

这项研究引入了一种新的随机朗格温模型,以准确地确定来自交流歇斯底里循环数据的磁纳米粒子特性,如和磁化和异性质. 该模型增强了对磁纳米粒子动态的理解.

关键词:
贝叶斯优化的贝叶斯优化斯过程是高斯过程.歇斯底里循环中的歇斯底里循环.磁性纳米粒子是一种磁性纳米粒子.随机的兰格温模型模型

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