Collaborative Research: Element: Development of MuST, A Multiple Scattering Theory based Computational Software for First Principles Approach to Disordered Materials

合作研究：元素：MuST 的开发，一种基于多重散射理论的计算软件，用于无序材料的第一原理方法

• 批准号: 1931525
• 负责人: Yang Wang
• 金额: $ 27万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931525&HistoricalAwards=false
• 关键词: Collaborative; Research; Element; Development; MuST

The effect of disorder in materials is of great fundamental and technological interest. Disorder disrupts the periodic arrangement of atoms in perfect materials. It profoundly affects materials properties and can provide a valuable tool in changing and controlling their physical properties. The best-known example is the transistor and other silicon components which are controlled through the introduction of disorder. Quantum mechanical states in semiconductors induced by introducing impurities and disorder can dramatically increase the efficiency of solar cells. There are many other materials of potential technological interest, such as high entropy alloys, dilute magnetic semiconductors, and topological insulators where disorder plays an essential role. Being able to understand, control, and predict the disorder effects in real physical systems is essential for the development of new structural and functional materials for future technological applications. This project involves building computer software that is aimed to enable the study of disorder effects using the principles of quantum mechanics and to accelerate the discovery of materials essential for industry and information technology applications. The creation of a large community of users and developers who will accelerate this process is envisioned. This project supports interdisciplinary training and education of undergraduate and graduate students in the fields of theoretical condensed matter physics and computational materials sciences. The user community of this software will be supported through webinars, discussion groups on social media, and online tutorial materials. This award supports various training and outreach efforts, including an annual "Beowulf Boot Camp" and "Quantum Day" for high-school students, and undergraduate and graduate research opportunities. The PIs will build upon and unify decades of development of research codes for the first-principles investigation of disordered materials. These codes include the Korringa-Kohn-Rostoker Coherent Potential Approximation, which is the first principles code for the study of random alloys, and the Locally Self-consistent Multiple Scattering code, which can enable the study of extremely large disordered systems from first principles using the largest parallel supercomputers available. Strong disorder effects and Anderson localization have been studied on the model Hamiltonian level using the Typical Medium Dynamical Cluster Approximation (TMDCA). To enable the study the strong disorder effects in real system within the first-principles Locally Self-consistent Multiple Scattering formalism with cluster embedding, the project team will use the typical medium analysis of TMDCA. The software product of this project, MuST, will be made available on GitHub as a self-contained open source package with detailed online documentations. MuST will create a scalable approach for first principles studies of quantum materials that efficiently utilizes petascale and future high-performance computing resources. It will expand the user community by enabling researchers within academia and industry to perform calculations that are presently out of reach for most users. MuST will provide a computational framework for the investigation of phase transitions and electron localization in the presence of disorder in real materials and will also enable the computational study of local chemical correlation effects on the magnetic structure, phase stability, and mechanical properties of high entropy alloys and other disordered structures.This award is jointly supported by the NSF Office of Advanced Cyberinfrastructure and the Division of Materials Research within the NSF Directorate of Mathematical and Physical Sciences.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.

材料中疾病的影响具有极大的基本和技术意义。疾病破坏原子在完美材料中的定期布置。它对材料的特性产生了深远的影响，并可以为改变和控制其物理特性提供有价值的工具。最著名的例子是通过引入疾病来控制的晶体管和其他硅成分。通过引入杂质和混乱引起的半导体中的量子机械状态可以大大提高太阳能电池的效率。还有许多其他潜在技术兴趣的材料，例如高熵合金，稀释磁性半导体和拓扑绝缘子，而疾病起着至关重要的作用。能够理解，控制和预测实际物理系统中的障碍效应对于开发未来技术应用的新结构和功能材料至关重要。该项目涉及构建计算机软件，旨在使用量子力学原理来研究障碍效应，并加速发现对行业和信息技术应用必不可少的材料的发现。设想了一个将加速此过程的大量用户和开发人员的社区的创建。该项目支持理论凝结物理学和计算材料科学领域的本科生和研究生的跨学科培训和教育。该软件的用户社区将通过网络研讨会，社交媒体上的讨论组和在线教程材料来支持。该奖项支持各种培训和推广工作，包括一年一度的“ Beowulf Boot Camp”和“量子日”，用于高中生，以及本科和研究生研究机会。 PI将建立并统一数十年来开发研究法规的第一原则研究无序材料的研究。这些代码包括Korringa-kohn-Rostoker连贯的潜在近似，这是研究随机合金研究的第一个原理代码，以及本地自洽的多个散射代码，可以利用最大的平行超级投放器从第一原理中研究最大的无序系统。使用典型的媒体动力簇近似（TMDCA），已经研究了强烈的障碍效应和安德森定位。为了使研究能够在第一原理中使用群集嵌入的本地自一致的多个散射形式主义中的真实系统中的强大障碍效应，项目团队将使用TMDCA的典型介质分析。该项目的软件产品必须在Github上作为一个具有详细在线文档的独立开源包装提供。必须为量子材料的第一原理研究创建一种可扩展的方法，该研究有效利用Petascale和未来的高性能计算资源。它将通过使学术界和行业中的研究人员能够执行目前对大多数用户遥不可及的计算来扩展用户社区。必须提供一个计算框架，以研究实际材料中疾病的存在相变和电子定位的研究，还将能够对局部化学相关效应的计算研究对磁性结构，相位稳定性以及高熵合金和其他无序结构的机械特性的影响。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准评估值得支持。

项目成果

Non-local corrections to the typical medium theory of Anderson localization

安德森局域化典型介质理论的非局域修正

• DOI: 10.1016/j.aop.2021.168454
• 发表时间: 2021
• 期刊: Annals of Physics
• 影响因子: 3
• 作者: Terletska, H.;Moilanen, A.;Tam, K.-M.;Zhang, Y.;Wang, Y.;Eisenbach, M.;Vidhyadhiraja, N.S.;Chioncel, L.;Moreno, J.
• 通讯作者: Moreno, J.

Averaged cluster approach to including chemical short-range order in KKR-CPA

在 KKR-CPA 中包含化学短程有序的平均聚类方法

• DOI: 10.1103/physrevb.102.054207
• 发表时间: 2020
• 期刊: Physical Review B
• 影响因子: 3.7
• 作者: Raghuraman, Vishnu;Wang, Yang;Widom, Michael
• 通讯作者: Widom, Michael

Application of the locally self-consistent embedding approach to the Anderson model with non-uniform random distributions

局部自洽嵌入方法在非均匀随机分布Anderson模型中的应用

• DOI: 10.1016/j.aop.2021.168480
• 发表时间: 2021
• 期刊: Annals of Physics
• 影响因子: 3
• 作者: Tam, K.-M.;Zhang, Y.;Terletska, H.;Wang, Y.;Eisenbach, M.;Chioncel, L.;Moreno, J.
• 通讯作者: Moreno, J.

Ab initio approaches to high-entropy alloys: a comparison of CPA, SQS, and supercell methods

• DOI: 10.1007/s10853-022-07186-9
• 发表时间: 2022-05-07
• 期刊: JOURNAL OF MATERIALS SCIENCE
• 影响因子: 4.5
• 作者: Karabin, Mariia;Mondal, Wasim Raja;Eisenbach, Markus
• 通讯作者: Eisenbach, Markus

Monte Carlo simulation of order-disorder transition in refractory high entropy alloys: A data-driven approach

• DOI: 10.1016/j.commatsci.2020.110135
• 发表时间: 2020-11
• 期刊: Computational Materials Science
• 影响因子: 3.3
• 作者: Xianglin Liu;Jiaxin Zhang;Junqi Yin;Sirui Bi;M. Eisenbach;Yang Wang