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: 0604531
• 负责人: Sergey Savrasov
• 金额: $ 11.71万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-10-21 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0604531&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. ***

该奖项是在响应ITR招标的“小型”类别提案中颁发的，NSF-02-168。它通过奖项＃0312478奖，旨在建立更现实的电子材料理论，以支持新泽西理工学院和罗格斯大学的团体之间的合作计算和理论研究。 PI旨在为研究，设计和可视化包含密切相关的电子系统的材料的性质的计算方法。这项工作的理论基础是基于一种非扰动多体方法，涉及动态平均场的组合和GW理论，可以产生特定于材料的预测和固体性质的解释。 PIS的目标是：（a）使用高性能，全电子，全电力，相对论线性松饼轨道（LMTO）代码来实现此方法，用于晶体，平板和周期性聚合物，称为“ lmtart”； “ （b）提高性能，以便可以为每个单位细胞许多原子的复杂系统处理绿色功能，自我能量和极化算子； （c）设计和实施用户友好的接口和可视化功能，以计算相关的电子系统，创建快速，功能强大，启用数据库和网络集成的材料信息和设计实验室（MindLab），以实现物理，材料科学，材料科学的利益和使用工程和教育社区； （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以及对重型费米昂系统中的de Haas van Alphen实验的解释，测试和应用此信息技术启用了量子多体型理论工具。Mindlab将增强研究基础架构和教育；它有可能在通过强大的可视化技术促进，培训和学习的同时提高发现和理解材料。该奖项是在响应ITR招标（NSF-02-168）提交的“小”类别提案上颁发的。它通过奖项＃0342290奖，旨在建立更现实的电子材料理论，以支持罗格斯大学和新泽西理工学院的团体之间的合作计算和理论研究。密切相关的电子材料表现出异常现象，例如高温超导性，巨大的磁性，巨大的光学非线性和大型热电系数。这些系统处于材料科学的边界，它们表现出的各种行为以及它们的复杂性使他们的研究在智力上具有挑战性，并且应用程序的前景令人兴奋。PIS旨在为研究，设计和可视化构建计算方法将开发包含密切相关的电子系统的材料的性质，以应对真实材料的复杂性新理论方法，算法和计算机程序的复杂性。通过这些新颖的信息技术工具用于计算和数据生成，可以在基本层面研究包含许多单位细胞原子的技术相关化合物，同时还包括重要的特定材料细节。数据可视化可以访问捕获电子相关物理所需的更抽象的理论量。 PIS的目标包括用于关联电子系统的计算工具的设计和实施，快速，功能强大，启用数据库和Web集成的材料信息和设计实验室（MindLab）。 MindLab将增强研究和教育的基础设施；它有可能在通过强大的可视化技术促进，培训和学习的同时提高发现和理解材料。 ***