ITR: Computational Design of Strongly Correlated Materials Based on a Combination of the Dynamical Mean Field and the GW Methods

ITR：基于动态平均场和引力场方法相结合的强相关材料的计算设计

• 批准号: 0342290
• 负责人: Sergey Savrasov
• 金额: $ 27万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2006-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0342290&HistoricalAwards=false
• 关键词: ITR; Computational; Design; Strongly; Correlated

This award was made on a 'small' category proposal submitted in response to the ITR solicitation, NSF-02-168. It supports collaborative computational and theoretical research between groups at New Jersey Institute of Technology and Rutgers University through award #0312478 that aims for a more realistic theory of strongly correlated electron materials. The PIs aim to construct a computational approach for the study, design and visualization of properties of materials containing strongly correlated electron systems.The theoretical foundations of this work are based on a non-perturbative many-body method involving on a combination of dynamical mean field and GW theories, which can yield material-specific predictions and interpretation of properties of solids. The PIs' objectives are to: (a) implement this approach using the high-performance, all-electron, full-potential, relativistic linear-muffin-tin orbital (LMTO) code for crystals, slabs, and periodic polymers called "LMTART;" (b) enhance performance so that Green functions, self-energies, and polarization operators on the frequency axis can be handled for complicated systems with many atoms per unit cell; (c) design and implement user-friendly interfaces and visualization capabilities for calculations of correlated electronic systems, creating a fast, powerful, database enabled and Web integrated Material Information and Design Laboratory (MINDLab) for the benefit and use in physics, material science, engineering, and educational communities; (e) test and apply this information technology enabled quantum many-body theory tool by tackling frontier problems of material science such as computational design of magnetic semiconductors and interpretation of de Haas van Alphen experiments in heavy fermion systems.MINDLab would enhance the infrastructure for research and education; it has the potential to advance discovery and understanding of materials while promoting teaching, training and learning through powerful visualization techniques. %%%This award was made on a 'small' category proposal submitted in response to the ITR solicitation, NSF-02-168. It supports collaborative computational and theoretical research between groups at Rutgers University and New Jersey Institute of Technology through award #0342290 that aims for a more realistic theory of strongly correlated electron materials. Strongly correlated electron materials display unusual phenomena such as high-temperature superconductivity, colossal magnetoresistance, giant optical non-linearities and large thermoelectric coefficients. These systems are at the frontier of materials science, and the variety of behavior they exhibit as well as their complexity makes their study intellectually challenging, and the prospects for applications exciting.The PIs aim to construct a computational approach for the study, design and visualization of properties of materials containing strongly correlated electron systems To tackle the complexity of real materials new theoretical methods, algorithms, and computer programs will be developed. By means of these novel information technology tools for computation and data generation, technologically relevant compounds containing many atoms per unit cell may be studied at a fundamental level while also including important material-specific detail. Data visualization enables access to more abstract theoretical quantities required to capture the physics of electronic correlation. The PIs' objectives include the design and implementation of a computational tool for correlated electronic systems, a fast, powerful, database enabled and Web integrated Material Information and Design Laboratory (MINDLab). MINDLab would enhance the infrastructure for research and education; it has the potential to advance discovery and understanding of materials while promoting teaching, training and learning through powerful visualization techniques. ***

该奖项是根据 ITR 征集 NSF-02-168 提交的“小型”类别提案而颁发的。它通过#0312478 奖项支持新泽西理工学院和罗格斯大学小组之间的协作计算和理论研究，旨在建立更现实的强相关电子材料理论。 PI 旨在构建一种计算方法，用于研究、设计和可视化包含强相关电子系统的材料的特性。这项工作的理论基础基于涉及动态平均场组合的非微扰多体方法和引力波理论，它可以产生特定材料的预测和固体特性的解释。 PI 的目标是： (a) 使用高性能、全电子、全势、相对论性线性松饼锡轨道 (LMTO) 代码来实施这种方法，用于晶体、板和周期性聚合物，称为“LMTART”； ” (b) 增强性能，以便可以针对每个晶胞具有许多原子的复杂系统处理频率轴上的格林函数、自能和偏振算子； (c) 设计和实现用户友好的界面和可视化功能，用于相关电子系统的计算，创建一个快速、强大、支持数据库和网络集成的材料信息和设计实验室（MINDLab），以造福于物理学、材料科学、工程和教育社区； (e) 通过解决材料科学的前沿问题（例如磁性半导体的计算设计和重费米子系统中德哈斯·范阿尔芬实验的解释）来测试和应用这种信息技术支持的量子多体理论工具。MINDLab 将增强研究基础设施和教育；它有潜力促进对材料的发现和理解，同时通过强大的可视化技术促进教学、培训和学习。 %%%该奖项是针对响应 ITR 征集 NSF-02-168 提交的“小型”类别提案而颁发的。它通过#0342290 奖项支持罗格斯大学和新泽西理工学院小组之间的协作计算和理论研究，旨在建立更现实的强相关电子材料理论。强关联电子材料表现出高温超导、巨磁阻、巨大光学非线性和大热电系数等异常现象。这些系统处于材料科学的前沿，它们表现出的各种行为及其复杂性使得它们的研究在智力上具有挑战性，并且应用前景令人兴奋。PI旨在构建一种用于研究、设计和可视化的计算方法为了解决真实材料的复杂性，将开发新的理论方法、算法和计算机程序。通过这些用于计算和数据生成的新型信息技术工具，可以在基础水平上研究每个晶胞包含许多原子的技术相关化合物，同时还包括重要的材料特定细节。数据可视化可以获取捕获电子关联物理所需的更抽象的理论量。 PI 的目标包括设计和实现相关电子系统的计算工具、快速、强大、支持数据库和网络集成的材料信息和设计实验室 (MINDLab)。 MINDLab 将加强研究和教育基础设施；它有潜力促进对材料的发现和理解，同时通过强大的可视化技术促进教学、培训和学习。 ***