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

材料中的无序效应具有重大的基础和技术意义。无序打乱了完美材料中原子的周期性排列。它深刻地影响着材料的性质，并为改变和控制其物理性质提供了一个有价值的工具。最著名的例子是通过引入无序来控制的晶体管和其他硅组件。在半导体中引入杂质和无序引起的量子力学状态可以极大地提高太阳能电池的效率。还有许多其他具有潜在技术意义的材料，如高熵合金、稀磁半导体和拓扑绝缘体，在这些材料中，无序起着至关重要的作用。能够理解、控制和预测真实物理系统中的无序效应，对于为未来的技术应用开发新的结构和功能材料是至关重要的。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。预计将创建一个庞大的用户和开发人员社区，他们将加速这一进程。该项目支持理论凝聚态物理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、社交媒体上的讨论小组和在线教程材料得到支持。该奖项支持各种培训和推广活动，包括每年为高中生举办的“贝奥武夫训练营”和“量子日”，以及本科生和研究生的研究机会。PI将建立并统一几十年来为无序材料的第一原理调查而开发的研究代码。这些程序包括Korringa-Kohn-Rostoker相干势近似，这是研究随机合金的第一原理程序，以及局部自洽多重散射程序，它可以用现有最大的并行超级计算机从第一原理研究超大型无序系统。在模型哈密顿水平上，用典型的介质动力学团簇近似(TMDCA)研究了强无序效应和Anderson局域化。为了能够在第一原理局域自洽多重散射团嵌入形式下研究实际系统中的强无序效应，项目组将使用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放源码包提供，并带有详细的在线文档。MUST将为量子材料的第一性原理研究创造一种可扩展的方法，有效地利用千万亿级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完成的计算来扩大用户社区。该奖项由NSF高级网络基础设施办公室和NSF数学和物理科学局内的材料研究部共同支持。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，认为值得支持。

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.