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.

材料中的无序效应具有重大的基础和技术意义。无序破坏了完美材料中原子的周期性排列。它深刻地影响材料的性能，并可以提供一个有价值的工具，在改变和控制其物理性能。最著名的例子是晶体管和其他通过引入无序来控制的硅元件。通过引入杂质和无序在半导体中引入量子力学态可以显著提高太阳能电池的效率。还有许多其他具有潜在技术价值的材料，如高熵合金、稀磁半导体和拓扑绝缘体，其中无序起着至关重要的作用。能够理解、控制和预测真实的物理系统中的无序效应对于开发用于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，旨在利用量子力学原理研究无序效应，并加速发现工业和信息技术应用所必需的材料。设想创建一个由用户和开发人员组成的大型社区，以加速这一进程。该项目支持理论凝聚态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得到支持。该奖项支持各种培训和推广工作，包括每年的“贝奥武夫靴子营”和“量子日”的高中生，本科生和研究生的研究机会。PI将建立在无序材料第一性原理研究的研究代码的基础上，并将其统一起来。这些代码包括Korringa-Kohn-Rostoker相干势近似，这是研究随机合金的第一原理代码，以及局部自洽多重散射代码，它可以使用最大的并行超级计算机从第一原理研究超大型无序系统。采用典型介质动力学集团近似（TMDCA），在模型哈密顿量水平上研究了强无序效应和安德森局域化。为了能够在具有簇嵌入的第一性原理局部自洽多重散射形式主义中研究真实的系统中的强无序效应，项目团队将使用TMDCA的典型介质分析。该项目的软件产品MuST将在GitHub上作为一个独立的开源软件包提供，并附有详细的在线文档。MuST将为量子材料的第一原理研究创建一种可扩展的方法，有效利用千万亿次和未来的高性能计算资源。它将通过使学术界和工业界的研究人员能够执行目前大多数用户无法实现的计算来扩大用户社区。MuST将为研究真实的材料中存在无序时的相变和电子局域化提供一个计算框架，也将使局部化学相关效应对磁结构、相稳定性、高熵合金和其他无序结构的物理和机械性能。该奖项由NSF高级网络基础设施办公室和该奖项反映了NSF的法定使命，并通过使用基金会的知识价值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

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

An investigation of high entropy alloy conductivity using first-principles calculations

使用第一性原理计算研究高熵合金电导率

• DOI: 10.1063/5.0065239
• 发表时间: 2021
• 期刊: Applied Physics Letters
• 影响因子: 4
• 作者: Raghuraman, Vishnu;Wang, Yang;Widom, Michael
• 通讯作者: Widom, Michael