Computational Studies of Dynamical Phenomena in Nanoscale Ferromagnets

这是授予密西西比州立大学的奖项，佛罗里达州立大学也获得了这一奖项。这是一个正在进行的纳米磁学计算研究现状的研究计划的更新。因此，它抓住了NSF最近关于ITR和NSE的倡议的精神，因为它的影响将在复杂相互作用系统的新算法、在纳米尺度上理解磁性以及新的超高密度磁存储系统的设计上感受到。这项研究的技术动机之一是不断努力提高磁记录介质的信息存储密度。超高密度磁记录介质可能在未来几年内变得可用，该介质可以在一个单域纳米级磁性颗粒上存储一比特信息。为了在室温下以可接受的数据完整性和读/写速度实现这一目标，有必要提高对磁性纳米粒子、分子和超薄膜在非零温度下的磁化-反转动力学的科学理解。这将需要对具有重要技术意义的磁性材料的真实模型进行大规模的数值模拟。这项研究项目将进一步开发新的模拟算法，用于纳米级磁体模型中的磁滞和热驱动磁化反转。该项目的材料目标是提高对真实纳米级铁磁材料在大范围时间范围内非零温度下的动力学现象的理解。之前的工作将通过加强对量子力学系统和不太强烈的各向异性材料的重视，对更广泛的真实材料进行模拟来扩展。这些推广将包括具有有限自旋各向异性的连续自旋模型，具有缺陷和猝灭无序的系统，磁性分子的三维模型和量子自旋模型。为了研究这些模型，将采用和开发能够覆盖大范围时间尺度的新算法，特别是以前在该项目上开发的吸收马尔可夫链算法的投影动力学和蒙特卡罗算法。连续自旋模型的研究还将使用朗之万微磁学方法来进行有限温度模拟，这是在前一次赠款期间开发的。将特别强调开发方法，使这些模拟能够涵盖广泛的时间范围。还建议使用量子密度矩阵来预测磁性分子的实验EPR谱线宽度，并为动力学蒙特卡罗和朗之万法模拟提供从头算跃迁几率。将研究这些算法对各种并行化范例的适用性，并将它们在可伸缩的并行计算机上实现。并行模拟算法的尺度特性将通过映射到在该项目中发现的非平衡界面生长问题来研究。这些算法和并行化方法构成了研究的计算目标。这是对密西西比州立大学的奖励，对佛罗里达州立大学也是一个子奖。这是一个正在进行的纳米磁学计算研究现状的研究计划的更新。因此，它抓住了NSF最近关于ITR和NSE的倡议的精神，因为它的影响将在复杂交互系统的新算法、在纳米尺度上理解磁性以及新的超高密度磁存储系统的设计上感受到。

This is an award to Mississippi State University with a subaward to Florida State University. It is a renewal of an ongoing research program on state of the art computational studies of nanomagnetism. As such, it captures the spirit of recent NSF initiatives on ITR and NSE, in that its impact will be felt on new algorithms for complex interacting systems, understanding magnetism on the nanoscale, and the design of new ultrahigh-density magnetic strorage systems.One technological motivation of the research is the ongoing effort to increase the information storage density of magnetic recording media. It is likely that ultrahigh-density magnetic recording media that can store one bit of information on one single-domain, nanoscale magnetic particle may become available in the next few years. To achieve this goal with acceptable data integrity and read/write speeds at room temperature, it is necessary to improve the scientific understanding of magnetization-reversal dynamics in magnetic nanoparticles, molecules, and ultrathin films, at nonzero temperatures. This will require large-scale numerical simulations of realistic models of technologically important magnetic materials.This research project will further develop novel simulation algorithms for hysteresis and thermally driven magnetization reversal in models of nanoscale magnets. The materials objective of the project is to improve understanding of dynamical phenomena in real nanoscale ferromagnetic materials at nonzero temperature over a large range of time scales. Previous work will be extended by conducting simulations of a wider range of real materials through increased emphasis on quantum mechanical systems and less strongly anisotropic materials. These generalizations will include continuous spin models with finite spin anisotropy, systems with defects and quenched disorder, three-dimensional models and quantum spin models of magnetic molecules. In order to study these models, novel algorithms capable of covering a wide range of time scales will be adapted and developed, in particular the Projective Dynamics and Monte Carlo with Absorbing Markov Chains algorithms previously developed on this project. The studies of continuous spin models will also use Langevin Micromagnetics methods for finite-temperature simulations developed during the previous grant period. Particular emphasis will be given to developing methods that enable these simulations to cover a wide range of time scales. It is also proposed to use quantum density matrices to predict experimental EPR line widths for magnetic molecules and to provide ab initio transition probabilities for kinetic Monte Carlo and Langevin simulations. The suitability of these algorithms for various parallelization paradigms will be studied and they will be implemented on scalable parallel computers. The scaling properties of parallel simulation algorithms will be studied using mappings to non-equilibrium interface-growth problems that were discovered on this project. These algorithmic and parallelization methods constitute the computational objectives of the research. %%%This is an award to Mississippi State University with a subaward to Florida State University. It is a renewal of an ongoing research program on state of the art computational studies of nanomagnetism. As such, it captures the spirit of recent NSF initiatives on ITR and NSE, in that its impact will be felt on new algorithms for complex interacting systems, understanding magnetism on the nanoscale, and the design of new ultrahigh-density magnetic strorage systems.***