CAREER: Advancing nanostructure & interface science for permanent magnets without rare earth materials

职业：推进纳米结构

基本信息

批准号：
2142935
负责人：
Mahmood Mamivand
金额：
$ 50.86万
依托单位：
Boise State University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-02-01 至 2027-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2142935&HistoricalAwards=false
关键词：
CAREER Advancing nanostructure &amp interface

项目摘要

NONTECHNICAL SUMMARYThis award supports theoretical, computational, and educational activities that aim to advance the fundamental understanding of mechanisms underlying nanostructure formation in multicomponent permanent magnet alloys during magnetic-field-assisted manufacturing. This knowledge paves the path toward developing a novel permanent magnet composed of earth-abundant elements that can outperform the state-of-the-art permanent magnets at high temperatures. Current high-temperature permanent magnets, used in electric vehicles and wind power production industries, are based on rare earth elements. The U.S. produces a small fraction globally of industrial rare-earth elements like neodymium and dysprosium. Therefore, developing alternatives to their use can reduce U.S. dependence on these materials and have a positive impact on U.S. national economic and energy security.The PI and his team will develop a new computational model by incorporating novel artificial intelligence methods to unravel the mechanisms that can improve the desirable magnetic properties in a class of alloys made of earth-abundant elements such as iron, aluminum, nickel, and cobalt. A proof-of-concept permanent magnet, based on the chemistry and processing routes predicted by computational modeling, will be fabricated and characterized. This award also supports a unique educational activity for Idaho high school and college students to gain hands-on experience on machine learning through a novel educational curriculum and involvement in authentic machine learning projects together. The project will also provide professional training for high school teachers. The education plan of the project addresses both national and regional workforce shortages in the areas of science, technology, engineering, and mathematics that primarily originate from low entrance and retention rates, particularly for underserved students.TECHNICAL SUMMARYThis award supports research and educational activities that aim to develop a fundamental understanding of mechanisms underlying nanostructure formation in multicomponent permanent magnets alloys during thermo-magnetic treatment. The PI and his team will develop an atomistically informed phase-field model to unravel the mechanism of nanostructure formation in FeAlNiCo-based alloys during thermo-magnetic treatment with a particular focus on understanding and engineering the Cu-rich and Ni-rich interfacial phases as solutions for FeCo-rich phase isolation and consequently magnetic property improvement. The team will also develop a new mixed-data three-dimensional convolutional neural network framework to construct the process-structure linkages for FeAlNiCo-based alloys. A proof-of-concept permanent magnet, based on the chemistry and processing routes predicted by the neural network, will be fabricated and characterized. The project outcomes can potentially displace rare earth-based permanent magnets in high-temperature applications, such as electric vehicle and wind generator traction motors, with a more widely available alternative.This award also supports a unique educational activity for Idaho high school and college students to gain hands-on experience on machine learning through a novel educational curriculum and involvement in authentic machine learning projects together. The project will also provide professional training for high school teachers. The education plan of the project addresses both national and regional workforce shortages in the areas of science, technology, engineering, and mathematics that primarily originate from low entrance and retention rates, particularly for underserved students.This project is jointly funded by the Division of Materials Research through the Condensed Matter and Materials Theory program, and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术摘要该奖项支持理论、计算和教育活动，旨在促进对磁场辅助制造过程中多组分永磁合金纳米结构形成机制的基本理解。这些知识为开发一种由地球丰富的元素组成的新型永磁体铺平了道路，这种永磁体在高温下的性能优于最先进的永磁体。目前用于电动汽车和风力发电行业的高温永磁体是基于稀土元素的。美国生产全球一小部分工业稀土元素，如钕和镝。因此，开发它们的替代品可以减少美国对这些材料的依赖，并对美国国家经济和能源安全产生积极影响。PI和他的团队将通过结合新颖的人工智能方法来开发一种新的计算模型，以揭示可以实现这一目标的机制。提高由铁、铝、镍和钴等地球丰富元素制成的一类合金的理想磁性。将根据计算模型预测的化学和加工路线来制造和表征概念验证永磁体。该奖项还支持爱达荷州高中和大学生开展一项独特的教育活动，通过新颖的教育课程和共同参与真实的机器学习项目来获得机器学习的实践经验。该项目还将为高中教师提供专业培训。该项目的教育计划解决了科学、技术、工程和数学领域的国家和地区劳动力短缺问题，这主要是由于入学率和保留率低，特别是对于服务不足的学生而言。技术摘要该奖项支持旨在对热磁处理过程中多组分永磁体合金中纳米结构形成的机制有一个基本的了解。 PI 和他的团队将开发一种原子信息相场模型，以揭示热磁处理过程中 FeAlNiCo 基合金中纳米结构形成的机制，特别关注理解和设计富铜和富镍界面相：富 FeCo 相隔离的解决方案，从而改善磁性能。该团队还将开发一种新的混合数据三维卷积神经网络框架，以构建 FeAlNiCo 基合金的过程-结构联系。将根据神经网络预测的化学和加工路线来制造和表征概念验证永磁体。该项目成果有可能在高温应用中取代稀土永磁体，例如电动汽车和风力发电机牵引电机，并提供更广泛的替代品。该奖项还支持针对爱达荷州高中和大学生的独特教育活动通过新颖的教育课程并共同参与真实的机器学习项目，获得机器学习的实践经验。该项目还将为高中教师提供专业培训。该项目的教育计划解决了国家和地区科学、技术、工程和数学领域的劳动力短缺问题，这主要是由于入学率和保留率低，特别是对于服务不足的学生而言。该项目由材料司共同资助通过凝聚态和材料理论计划以及促进竞争性研究的既定计划 (EPSCoR) 进行研究。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响进行评估，被认为值得支持审查标准。