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: 0312478
• 负责人: Gabriel Kotliar
• 金额: $ 23万
• 依托单位: Rutgers University New Brunswick
• 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: 2003-08-01 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0312478&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 Rutgers University and New Jersey Institute of Technology through award #0342290 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. ***

该奖项是应国际交易日志征集活动NSF-02-168提交的一个“小”类别提案而颁发的。它通过0342290号奖项支持罗格斯大学和新泽西理工学院团队之间的合作计算和理论研究，该奖项旨在建立更现实的强关联电子材料理论。PIS旨在构建一种计算方法，用于研究、设计和可视化包含强关联电子系统的材料的性质。这项工作的理论基础是基于动力学平均场和GW理论的非微扰多体方法，该方法可以产生特定于材料的预测和对固体性质的解释。PIS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)代码实现这一方法，该代码用于晶体、板条和周期聚合物，称为“LMTART”；(B)增强性能，以便可以处理频率轴上的格林函数、自能和极化算符，用于每单位晶胞有许多原子的复杂系统；(C)为相关电子系统的计算设计和实施用户友好的界面和可视化能力，创建一个快速、强大、支持数据库和网络综合的材料信息和设计实验室(MindLab)，以便在物理、材料科学、工程和教育界受益和使用；(E)通过解决材料科学的前沿问题，如磁性半导体的计算设计和对重费米子系统中的De Haas van Alphen实验的解释，测试和应用这一信息技术支持的量子多体理论工具。它有可能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。%该奖项是根据响应ITR征集而提交的“小”类别建议书NSF-02-168颁发的。它通过0342290号奖项支持罗格斯大学和新泽西理工学院团队之间的合作计算和理论研究，该奖项旨在建立更现实的强关联电子材料理论。强关联电子材料表现出高温超导、巨磁电阻、巨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以及它们的复杂性使得它们的研究在智力上具有挑战性，应用前景令人兴奋。PI旨在构建一种计算方法，用于研究、设计和可视化包含强关联电子系统的材料的性质，以解决实际材料的复杂性，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的信息技术工具，可以在基础水平上研究每单位晶胞中含有许多原子的技术相关化合物，同时还可以包括重要的特定材料细节。数据可视化使人们能够获得捕捉电子关联物理所需的更抽象的理论量。PIS的目标包括设计和实施相关电子系统的计算工具，一个快速、强大、支持数据库和Web集成的材料信息和设计实验室(MindLab)。MindLab将加强研究和教育的基础设施；它有可能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。***