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CAREER: Material Design Using Motifs Present in the Electron's Wavefunction

职业：使用电子波函数中存在的图案进行材料设计

基本信息

批准号：
1848074
负责人：
Sinisa Coh
金额：
$ 53.27万
依托单位：
University of California-Riverside
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-01-01 至 2023-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1848074&HistoricalAwards=false
关键词：
CAREER Material Design Using Motifs

项目摘要

NONTECHNICAL SUMMARY This CAREER award supports research and education towards developing a new framework for the computational design of functional materials by harnessing vast amounts of data that have not been examined systematically. Most properties of matter are ultimately governed by complex patterns of quantum mechanical motion of electrons in a material. At the present time, researchers can accurately model this complex motion of electrons by numerically solving a well-defined set of mathematical equations on a modern computer. In many cases, the only input information one needs to solve these equations are the approximate locations of the atomic nuclei in the material. However, such modeling produces as an end result a massive amount of information, most of which remains unexplored in practice. The PI and his team will examine these large amounts of data to search and discover the most essential bits of information that govern the behavior of matter. In the next stage of the project, the team will use this distilled information to establish an innovative and systematic strategy for designing and discovering novel materials. The software developed as part of the project will be made available to the community as open source.The research will be closely integrated with educational and outreach efforts to create a better understanding of preconceived notions that freshman students and the public at large may have about what determines the properties of matter. This understanding will be used to create and disseminate active learning strategies for the classroom and for engaging the public, aiming to improve academic achievement at the university level, increase the public's understanding and appreciation of materials science, and inspire more young people to pursue careers in STEM fields.TECHNICAL SUMMARY This CAREER award supports research and education towards developing a new framework for the computational design of functional materials by harnessing vast amounts of data that have not been examined systematically. Solving the quantum mechanical equations that govern properties of matter produces a massive amount of information, most of which remains unexplored. The first thrust of this project will enable extracting essential pieces of information, motifs in the electron's wave function, that govern the behavior of matter. The second thrust will use the extracted motifs, along with principles of nearsightedness, symmetry, geometry, and topology, to establish an innovative and systematic strategy for computational materials design and discovery. The software developed as part of the project will be made available to the community as open source. The research will be closely integrated with educational and outreach efforts to create a better understanding of preconceived notions that freshman students and the public at large may have about what determines the properties of matter. This understanding will be used to create and disseminate active learning strategies for the classroom and for engaging the public, aiming to improve academic achievement at the university level, increase the public's understanding and appreciation of materials science, and inspire more young people to pursue careers in STEM fields.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.

非技术总结这个职业奖项支持研究和教育，通过利用大量未经系统检查的数据，为功能材料的计算设计开发一个新的框架。物质的大多数性质最终都是由材料中电子的量子力学运动的复杂模式决定的。目前，研究人员可以通过在现代计算机上数值求解一组定义明确的数学方程来准确地模拟这种复杂的电子运动。在许多情况下，求解这些方程所需的唯一输入信息是原子核在材料中的大致位置。然而，这样的建模最终会产生大量的信息，其中大部分仍未在实践中得到开发。PI和他的团队将检查这些大量数据，以搜索和发现管理物质行为的最基本的信息。在该项目的下一阶段，该团队将使用这些提取的信息来建立设计和发现新材料的创新和系统战略。作为项目的一部分开发的软件将以开放源代码的形式向社会提供。这项研究将与教育和外展工作紧密结合，以更好地了解新生和一般公众可能对决定物质性质的先入为主的观念。这一理解将被用于为课堂和公众参与创建和传播积极的学习策略，旨在提高大学水平的学术成就，增加公众对材料科学的理解和欣赏，并激励更多的年轻人在STEM领域追求职业生涯。该职业奖支持研究和教育，通过利用大量未经系统审查的数据，为功能材料的计算设计开发一个新的框架。求解支配物质性质的量子力学方程会产生大量信息，其中大部分仍未被探索。这个项目的第一个推力将能够提取控制物质行为的电子波函数中的基本信息片段。第二个推力将使用提取的主题，以及近视、对称、几何和拓扑原理，为计算材料设计和发现建立创新和系统的策略。作为该项目的一部分开发的软件将作为开放源码向社区提供。这项研究将与教育和推广工作紧密结合，以更好地理解新生和广大公众可能对什么决定物质性质的先入为主的观念。这一理解将被用来为课堂和公众参与创建和传播积极的学习策略，旨在提高大学水平的学术成就，增加公众对材料科学的理解和欣赏，并激励更多的年轻人在STEM领域追求职业生涯。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Magneto-optical Kerr spectra of gold induced by spin accumulation

DOI：
10.1103/physrevb.106.014410
发表时间：
2021-09
期刊：
Physical Review B
影响因子：
3.7
作者：
V. Ortiz;Sinisa Coh;Richard B. Wilson
通讯作者：
V. Ortiz;Sinisa Coh;Richard B. Wilson

Differentiating contributions of electrons and phonons to the thermoreflectance spectra of gold

DOI：
10.1103/physrevmaterials.5.106001
发表时间：
2021-03
期刊：
Physical Review Materials
影响因子：
3.4
作者：
Kexin Liu;Xinping Shi;Frank Angeles;R. Mohan;J. Gorchon;Sinisa Coh;Richard B. Wilson
通讯作者：
Kexin Liu;Xinping Shi;Frank Angeles;R. Mohan;J. Gorchon;Sinisa Coh;Richard B. Wilson

Nonadiabatic Born Effective Charges in Metals and the Drude Weight

金属中的非绝热有效电荷和德鲁德重量