DMREF:SusChEM:Collaborative Research: Design and Synthesis of Novel Magnetic Materials

DMREF：SusChEM：合作研究：新型磁性材料的设计与合成

基本信息

批准号：
1729202
负责人：
James Chelikowsky
金额：
$ 36.35万
依托单位：
University of Texas at Austin
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1729202&HistoricalAwards=false
关键词：
DMREF SusChEM Collaborative Research Design

项目摘要

Non-technical Description: This collaborative research project will implement new, transformative strategies for the design of novel magnetic materials, with special focus on sustainable materials containing earth-abundant and inexpensive elements. The project will couple a strong experimental effort with recent theoretical advances in quantum modeling algorithms and software, data-mining techniques, and high-performance hardware to accomplish its objectives. Magnets play a crucial role in contemporary technologies. They are essential components in generators, computer hard drives, mobile devices, and in all electric motors. This research will focus on the discovery of new phases with anisotropic structures, high magnetization, high Curie temperatures, high spin polarization and high magnetic anisotropy. Materials with these properties will have important applications in ultra-small spintronics devices, new high-density data-storage schemes and high-energy-product permanent-magnet materials. The broader impact activities of the project will involve graduate education, maintaining contact with the private sector, and outreach to underrepresented groups and middle-school students. Specially designed activities will include the Alice in Wonderland, Nanocamp and STEM after-school, and summer-intern programs. The algorithms, code, and databases created in this research will be made available to other accelerated materials-discovery efforts, and will be placed in the public domain on a website dedicated to this project.Technical Description: The technical design and synthesis of new magnetic materials is an intimidating problem, especially because of the huge numbers of possible combinations of composition and structure. This research will use computationally nonequilibrium explorations and materials-structure prediction coupled with experiment to identify materials with desirable properties. An adaptive genetic algorithm coupled to first-principle codes specifically designed for magnetic properties will be used for structure and property searches. The algorithm will possess the speed and efficiency of classical simulations, while maintaining the accuracy of quantum-based simulations. Concurrent, experimental research will involve novel synthetic techniques and a comprehensive set of characterization methods. With guidance from theory, nonequilibrium processes will be employed to generate transitional-metal-rich (stable and metastable) material phases, including inert-gas condensation techniques, and sputtering methods to synthesize nanoscale clusters and particles, and ultra-fast quenching from the melt to produce bulk materials for sustainable technologies. Comprehensive structural characterization of these material phases will be performed with x-ray and neutron diffraction, and high-resolution electron microscopy; magnetic and electronic-structure studies will be pursued with magnetization, x-ray magnetic circular dichroism and other methods. The characterization of these material phases is key to validate and verify theoretical work, and provide strategies for the synthesis of new materials. The PIs also plan to release codes for the magnetic and structural properties of clusters and solids, named PARSEC and AGA, respectively, as open source and build a user community around the language by ensuring that interested researchers are able to contribute to our codebase. This will allow a wider growth of the project. This aspect is of special interest to the software cluster in the Office of Advanced Cyberinfrastructure, which has provided co-funding for this award.

非技术描述：该协作研究项目将针对新型磁性材料的设计实施新的，变革性的策略，并特别关注含有地球丰富和廉价元素的可持续材料。该项目将对量子建模算法和软件，数据挖掘技术和高性能硬件的近期理论进步进行努力，以实现其目标。磁铁在当代技术中起着至关重要的作用。它们是发电机，计算机硬盘驱动器，移动设备以及所有电动机中的重要组件。这项研究将集中于发现具有各向异性结构，高磁化，高质量温度，高自旋极化和高磁各向异性的新阶段。具有这些特性的材料将在超小的SpinTronics设备，新的高密度数据存储方案和高能产品永久磁铁材料中具有重要应用。该项目的更广泛的影响活动将涉及研究生教育，与私营部门保持联系，并与代表性不足的团体和中学生宣传。专门设计的活动将包括爱丽丝梦游仙境，纳米板和STEM课后以及暑期课程。在本研究中创建的算法，代码和数据库将提供给其他加速材料 - 发现的工作，并将在专门用于该项目的网站上放置在公共领域中。技术描述：新磁性材料的技术设计和合成是一个可怕的问题，尤其是由于可能组成和结构的大量组合组合。这项研究将使用计算上的非平衡探索和材料结构预测以及实验，以识别具有理想特性的材料。耦合到专门为磁性特性设计的第一原质代码的自适应遗传算法将用于结构和属性搜索。该算法将具有经典模拟的速度和效率，同时保持基于量子的模拟的准确性。同时进行的实验研究将涉及新颖的合成技术和一组全面的表征方法。在理论的指导下，将采用非平衡过程来产生过渡金属（稳定且可稳定）的材料相，包括惰性气体凝结技术以及溅射方法，以合成纳米级簇和颗粒，以及从融合物产生构成构成材料的超快速淬火。这些材料相的全面结构表征将使用X射线和中子衍射以及高分辨率电子显微镜进行。磁性和电子结构研究将通过磁化，X射线磁圆二色性和其他方法进行。这些材料阶段的表征是验证和验证理论工作的关键，并为合成新材料提供策略。 PI还计划发布簇和固体的磁性和结构性特性的代码，分别为PARSEC和AGA作为开源，并通过确保感兴趣的研究人员能够为我们的代码库做出贡献，从而围绕语言建立用户社区。这将允许该项目的更大增长。这方面是高级网络基础设施办公室的软件集群特别感兴趣的，该策略已为该奖项提供了共同资助。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Synergistic computational and experimental discovery of novel magnetic materials

DOI：
10.1039/d0me00050g
发表时间：
2020-07-01
期刊：
MOLECULAR SYSTEMS DESIGN & ENGINEERING
影响因子：
3.6
作者：
Balasubramanian, Balamurugan;Sakurai, Masahiro;Sellmyer, David J.
通讯作者：
Sellmyer, David J.

Real-space pseudopotential method for calculating magnetocrystalline anisotropy

DOI：
10.1103/physrevmaterials.2.084411
发表时间：
2018-08
期刊：
Physical Review Materials
影响因子：
3.4
作者：
M. Sakurai;J. Chelikowsky
通讯作者：
M. Sakurai;J. Chelikowsky

Influence of nitrogen dopants on the magnetization of Co3N clusters

氮掺杂剂对Co3N团簇磁化强度的影响

DOI：
10.1103/physrevmaterials.2.024401
发表时间：
2018
期刊：
Physical Review Materials
影响因子：
3.4
作者：
Sakurai, Masahiro;Zhao, Xin;Wang, Cai-Zhuang;Ho, Kai-Ming;Chelikowsky, James R.
通讯作者：
Chelikowsky, James R.

Metastable B-doped FeNi compounds for permanent magnets without rare earths

用于无稀土永磁体的亚稳态掺硼 FeNi 化合物