Collaborative ITR: Computational Design of Magnetic and Superconducting Transitions Based on Cluster DMFT Approach to Electronic Structure Calculation

协作 ITR：基于电子结构计算的簇 DMFT 方法的磁和超导转变的计算设计

• 批准号: 0606498
• 负责人: Sergey Savrasov
• 金额: $ 26.4万
• 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: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0606498&HistoricalAwards=false
• 关键词: Collaborative; ITR; Computational; Design; Magnetic

TECHNICAL SUMMARY:This award supports collaborative computational and theoretical research at the University of California at Davis and Rutgers University through #0606096. The PIs aim to develop a robust computational approach to study, design, and visualize properties of materials containing strongly correlated electrons and showing magnetism, superconductivity, and other possibly novel ordered states. Novel information technology tools will be developed which will facilitate the search for new strongly correlated electron materials. This project contributes to the cyberinfrastructure of the broader materials research community.The dynamical mean field theory (DMFT) and its generalization to clusters in combinations with the theoretical methods of electronic structure calculations will be key theoretical methods employed in the research. In the course of the research, the PIs will continue to contribute to these theoretical foundations.The PIs plan to extend, enhance, and further develop the Material Information and Design Laboratory (MINDLab), a software tool for virtual material exploration created by the PIs with support from an Information Technology Research award. The PIs objectives are: i) to develop a new generation of computationally fast and robust methods, algorithms and computer codes to predict properties of strongly correlated electron materials based on a novel cluster dynamical mean field approach coupled to the electronic structure theory of materials; ii) to test and apply MINDLab by tackling frontier problems, including the search for new magnetic and superconducting materials with predictable critical temperatures, for new multiferroic materials with stronger couplings between magnetic and electric degrees of freedom, and for tunable optical materials; iii) to develop a new generation of user friendly interfaces and visualization software, as well as databases which will systematize the PIs' findings in a web integrated and searchable form; iv) to interact with experimental groups working on materials synthesis, so that the computationally created and optimized materials can be synthesized in practice. MINDLab will be made accessible via the Internet for public use by the scientific community. A simplified intuitive interface coupled with visualization techniques will enable its use as a learning tool for concepts of condensed-matter physics. NON-TECHNICAL SUMMARY:This award supports collaborative computational and theoretical research at the University of California at Davis and Rutgers University through #0606096. The PIs aim to develop a robust computational approach to study, design, and visualize properties of an intriguing class of materials, known as strongly correlated electron materials. These materials have unusual physical properties, such as high magnetic and superconducting transition temperatures, giant dielectric constants, and enhanced thermoelectric and optical properties, that reflect new or poorly understood electronic states of matter. Understanding these materials is a great intellectual challenge; the endeavor holds promise for many potential new discoveries. The PI's will develop computational and visualization tools, collectively called Material Information and Design Laboratory (MINDLab), that are based on promising recent theoretical advances. They will use them to study strongly correlated materials, to attempt to predict their properties, and to contribute guidance to the synthesis of new materials. The PIs will make these tools available for use by the broader materials research community, contributing to its cyberinfrastructure. A simplified intuitive interface coupled with visualization techniques will enable its use as a learning tool for concepts of condensed-matter physics.

技术摘要：该奖项支持加州大学戴维斯大学和罗格斯大学的合作计算和理论研究，通过＃0606096。 PI旨在开发一种可靠的计算方法来研究，设计和可视化包含密切相关的电子并显示磁性，超导性和其他可能新颖的有序状态的材料的性质。将开发新的信息技术工具，这些工具将有助于寻找新的强相关电子材料。该项目有助于更广泛的材料研究界的网络基础结构。动态平均场理论（DMFT）及其对簇的概括与电子结构计算的理论方法的概括将是研究中采用的关键理论方法。在研究过程中，PI将继续为这些理论基础做出贡献。PIS计划扩展，增强和进一步开发物质信息和设计实验室（MindLab），这是PIS在信息技术研究奖的支持下为PIS创建的虚拟物质探索的软件工具。 PIS目标是：i）开发新一代的计算快速，可靠的方法，算法和计算机代码，以预测基于新型群集动态均值场方法与材料的电子结构理论相连的新型群集动力学均值方法； ii）通过解决边境问题测试和应用MindLab，包括寻找具有可预测的临界温度的新磁性和超导材料，在磁性和电力自由度之间具有更强耦合的新型多用量材料，以及可调的光学材料； iii）开发新一代的用户友好界面和可视化软件以及数据库，这些数据库将在Web集成且可搜索的形式中系统化PIS的发现； iv）与在材料合成上工作的实验组相互作用，以便可以在实践中合成计算创建和优化的材料。 MindLab将通过Internet访问科学界的公众使用。简化的直观界面加上可视化技术，它将可以用作凝结物理学概念的学习工具。非技术摘要：该奖项支持加利福尼亚大学戴维斯分校和罗格斯大学通过＃0606096的合作计算和理论研究。 PI旨在开发一种可靠的计算方法来研究，设计和可视化有趣的材料类别（称为强相关的电子材料）的性质。这些材料具有异常的物理特性，例如高磁性和超导过渡温度，巨大的介电常数以及增强的热电和光学特性，这些特性反映了物质的电子状态或鲜为人知的电子状态。 了解这些材料是一个巨大的智力挑战。这项工作对许多潜在的新发现有希望。 PI将开发计算和可视化工具，即统称为物质信息和设计实验室（MindLab），这些工具基于有希望的最近的理论进步。他们将使用它们来研究密切相关的材料，试图预测其性质，并为合成新材料的合成提供指导。 PI将使这些工具可供广泛的材料研究界使用，从而为网络基础设施做出了贡献。简化的直观界面加上可视化技术，它将可以用作凝结物理学概念的学习工具。