Magnetic Properties from First-Principles

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。该奖项支持涉及材料磁性质的理论和计算研究和教育。分子尺度上的磁性在未来技术的发展中具有根本的重要性。提出的研究目标将是发展第一性原理计算方法来预测大分子的磁性，重点是磁交换耦合和磁各向异性能量。这项工作不仅可以增强我们对磁现象的理解，而且可以改变从密度泛函理论方法等第一性原理模型中提取磁参数的方式。所提出的方法允许，类似于响应特性，将磁性参数表示为参考状态的总电子能量相对于探测磁化密度的局部或全局旋转的参数的二阶导数。结合解析微扰理论，可以直接评估磁性参数，这将提供一种独特的工具，可以用来快速可靠地探索新材料的磁性。该方法将首先用于有限系统和局部原子高斯型轨道，考虑单分子磁体和原子团簇。提出的研究活动将大大提高科学界从第一性原理预测磁性质的能力。这项研究将有利于中密歇根大学的先进材料研究计划，并提供可以与本科和研究生教育计划相结合的前沿研究的具体例子。计划将积极促进妇女和少数民族参与科学，鼓励她们从事科学事业。参与这个项目的学生将获得宝贵的计算科学技能。该奖项支持涉及材料磁性质的理论和计算研究和教育。分子尺度上的磁性在未来技术的发展中具有根本的重要性。例子可以在分子自旋电子学中利用电子自旋自由度的装置中找到，或者在可以通过化学合成调节的单分子磁体的磁性中找到。设计具有理想磁性的新材料将要求我们对导致微观磁性的基本物理和化学机制有一个牢固的理解。作为提高我们对这些机制的理解的一种方法，计算机模拟可以在预测新现象和最大化从实验中获得的信息方面发挥关键作用。越来越需要开发具有预测能力的方法，可以提供磁性的定量描述，而本基金支持的研究将提供满足这些需求的方法。这项研究也将有利于中密歇根大学的先进材料研究计划，并提供可以与本科和研究生水平的教育计划相结合的前沿研究的具体例子。计划将积极促进妇女和少数民族参与科学，鼓励她们从事科学事业。参与这个项目的学生将获得宝贵的计算科学技能。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).TECHNICAL SUMMARYThis award supports theoretical and computational research and education involving the magnetic properties of materials. Magnetism at the molecular scale is of fundamental importance in the development of future technologies. The goal of the proposed research will be to develop first-principles computational methods to predict magnetic properties of large molecules, with a focus on magnetic exchange couplings and magnetic anisotropy energy. This work should not only enhance our understanding of magnetic phenomena, but also transform the way that magnetic parameters are extracted from first-principles models such as density functional theory approaches.The proposed method allows, in analogy to response properties, to express magnetic parameters as a second derivative of the total electronic energy of a reference state with respect to a parameter that probes local or global rotations of the magnetization density. In combination with analytic perturbation theory, magnetic parameters can be evaluated in straightforward fashion, which will provide a unique tool that can be employed to explore the magnetic properties of new materials in a fast and reliable way. The methodology will first be developed for finite systems and local atomic Gaussian-type orbitals with single-molecule magnets and atomic clusters in mind. The research activities proposed will greatly enhance the capabilities of the scientific community to predict magnetic properties from first-principles.This research will benefit the Advanced Materials Research initiative at Central Michigan University, and provide concrete examples of forefront research that can be integrated with the educational programs at the undergraduate and graduate levels. The PI will actively work to involve women and minorities in science and encourage them to pursue a scientific career. Students working on this project will gain valuable skills in computational science.NONTECHNICAL SUMMARYThis award supports theoretical and computational research and education involving the magnetic properties of materials. Magnetism at the molecular scale is of fundamental importance in the development of future technologies. Examples can be found in devices that exploit the spin degree of freedom of the electron in molecular spintronics, or in the magnetic properties of single-molecule magnets that can be tuned through chemical synthesis. Designing new materials with desired magnetic properties will require that we have a firm understanding of the basic physical and chemical mechanisms that lead to microscopic magnetism. As one approach to improving our understanding of these mechanisms, computer simulations can play a key role in predicting new phenomena and maximizing the information obtained from experiment. There is an increasing need of developing methodology with predictive capabilities that can provide a quantitative description of magnetic properties, and the research supported under this grant will provide methods to meet these needs. This research will also benefit the Advanced Materials Research initiative at Central Michigan University, and provide concrete examples of forefront research that can be integrated with the educational programs at the undergraduate and graduate levels. The PI will actively work to involve women and minorities in science and encourage them to pursue a scientific career. Students working on this project will gain valuable skills in computational science.