Theoretical Spectroscopy and Thermodynamics of Correlated Electron Materials

该奖项支持旨在开发新的计算工具的研究，并应用它们来理解和预测复杂材料的性质，这些材料表现出突出的量子效应竞争，如磁性、超导性和“电子相关”。虽然在理解和准确预测简单材料（如硅或铝）的性质方面取得了很大进展，其中电子可以被描述为几乎自由且独立于其他电子，但表现出相关电子行为的材料，其中一个电子的行为强烈依赖于其他电子的行为，使用现有的计算工具来描述要困难得多。这个项目的重点是为这些材料开发新的算法和软件包。特别是，PI和他的团队将模拟和预测一类超导体的电子特性，其中电流可以在一定温度下流动而没有任何能量损失，并且表现出相关的电子行为和复杂的磁性。在这个项目中开发的工具和代码可以让计算材料科学家从理论上表征其他量子材料，这些材料对许多现代技术的发展至关重要。该奖项还支持对初级研究人员的培训和指导，为他们的职业发展和科学队伍的发展做出贡献。此外，在项目期间开发的算法和计算机代码将通过现有的开源软件包与材料科学界免费共享，并使理论辅助材料设计和发现成为可能。该奖项支持旨在开发新的从头计算工具的理论研究，并应用它们来理解和预测复杂材料的性质，这些材料表现出突出的量子效应竞争，如电子相关，磁性和超导性。该项目的目标之一是发展下一代簇动力平均场理论方法，该方法有望显示不那么严重的费米子符号问题，从而能够预测相关超导铜酸盐和镍酸盐的趋势。该项目的第二个目标是将最近开发的变分图解蒙特卡罗方法扩展到从头算设置，并将其应用于研究传统超导体（如Li， Al和固态氢）在极端压力下的电子特性，而不需要现象学参数。变分图解蒙特卡罗方法可以精确地解决均匀电子气体问题。在这个项目中开发的工具和代码将允许人们从理论上表征复杂材料，这将提高对量子多体现象的科学理解，并将为利用多体效应开发包括强磁铁和新型超导体在内的功能材料提供基础。该奖项还支持对初级研究人员的培训和指导，为他们的职业发展和科学队伍的发展做出贡献。此外，在项目期间开发的算法和计算机代码将通过现有的开源软件包与材料科学界免费共享，并使理论辅助材料设计和发现成为可能。该奖项反映了美国国家科学基金会的法定使命，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。

NONTECHNICAL SUMMARYThis award supports research aimed at developing new computational tools and applying them to understand and predict properties of complex materials which show prominent competition of quantum effects such as magnetism, superconductivity, and "electronic correlation". While much progress has been made in understanding and accurately predicting properties of simple materials such as silicon or aluminum, in which electrons can be described as nearly free and independent of other electrons, materials exhibiting correlated electronic behavior, where the behavior of one electron is strongly dependent on the behavior of other electrons, are much harder to describe using existing computational tools. This project focuses on the development of new algorithms and software packages for such materials. In particular, the PI and his team will model and predict electronic properties of a class of superconductors, in which electricity can flow without any energy loss below a certain temperature, and which exhibit correlated electronic behavior and complex magnetic properties. The tools and codes developed in this project can allow computational materials scientists to theoretically characterize other quantum materials that are fundamental to the development of many modern technologies.This award also supports the training and mentorship of junior researchers by contributing to their career advancement and to the scientific workforce development. In addition, the algorithms and computer codes developed during the project will be freely shared with the materials science community through an existing open-source software package and enable theory-assisted materials design and discovery.TECHNICAL SUMMARYThis award supports theoretical research aimed at developing new ab-initio computational tools and applying them to understand and predict properties of complex materials which show prominent competition of quantum effects such as electron correlation, magnetism, and superconductivity. One of the goals of this project is to develop the next generation cluster-Dynamical Mean Field Theory methods, which are expected to show less severe fermionic sign problem, and hence enable prediction of trends in correlated superconducting cuprates and nickelates. A second goal of the project is to extend the recently developed Variational Diagrammatic Monte Carlo method, which can be solved numerically exactly for the uniform electron gas problem, to an ab-initio setting and apply it to investigate electronic properties of conventional superconductors such as Li, Al, and solid hydrogen under extreme pressure, without the need for phenomenological parameters. The tools and codes developed in this project will allow one to theoretically characterize complex materials, which will give improved scientific understanding of quantum many-body phenomena and will provide a basis for harnessing many-body effects to develop functional materials including strong magnets and novel superconductors.This award also supports the training and mentorship of junior researchers by contributing to their career advancement and to the scientific workforce development. In addition, the algorithms and computer codes developed during the project will be freely shared with the materials science community through an existing open-source software package and enable theory-assisted materials design and discovery.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.