发表机构
School of Chemistry, University of Edinburgh; Faculty of Physics, University of Vienna; Institute of Electrical and Biomedical Engineering, UMIT TIROL– Private University for Health Sciences and Health Technology; Institute for Computational Physics, University of Stuttgart; Biomedical Engineering Group, Department of Mechatronics, University of Innsbruck; School of Mathematical, Physical and Computational Sciences, University of Reading（爱丁堡大学化学学院; 维也纳大学物理学院; UMIT蒂罗尔私立健康科学与健康技术大学电气与生物医学工程研究所; 斯图加特大学计算物理研究所; 因斯布鲁克大学机电系生物医学工程组; 雷丁大学数学、物理与计算科学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文综述了磁性纳米颗粒在不同物理区域下的建模方法，比较了多种模型的适用性，并针对模型选择提供了指导，同时指出了多尺度模拟的挑战。
AI 中文摘要
磁性纳米颗粒（MNPs）对外加磁场的响应支撑着广泛的生物医学和技术应用。在本展望中，我们综述了描述MNP动力学的主要建模方法，这些方法覆盖不同的物理区域，从粗粒化的宏自旋描述到空间分辨的微磁模拟。选择合适的模型取决于相关的能量尺度和时间尺度，包括与磁各向异性相关的那些。我们比较了固定点偶极子、有效场、热Stoner-Wohlfarth、扩散跳跃、耦合Landau-Lifshitz-Gilbert、蛋形和微磁模型的假设、计算需求和适用区域。特别关注将磁化动力学与颗粒的平移和旋转运动、流体动力学相互作用以及长程偶极相互作用耦合。通过将相关物理区域与每种方法的分辨率和计算成本相关联，我们为模型选择提供了实用指导，并概述了预测性多尺度模拟相互作用MNP系统所面临的挑战。
英文摘要
The response of magnetic nanoparticles (MNPs) to applied magnetic fields underpins a broad range of biomedical and technological applications. In this Perspective, we review the principal modeling approaches for describing MNP dynamics across different physical regimes, ranging from coarse-grained macrospin descriptions to spatially resolved micromagnetic simulations. Selecting an appropriate model depends on the relevant energy scales and timescales, including those associated with magnetic anisotropy. We compare the assumptions, computational requirements, and regimes of applicability of the fixed-point-dipole, effective-field, thermal Stoner-Wohlfarth, diffusion-jump, coupled Landau-Lifshitz-Gilbert, egg, and micromagnetic models. Particular attention is given to coupling magnetization dynamics with translational and rotational particle motion, hydrodynamic interactions, and long-range dipolar interactions. By relating the relevant physical regimes to the resolution and computational cost of each approach, we provide practical guidance for model selection and outline challenges for predictive multiscale simulations of interacting MNP systems.
