ITR: A Thermodynamic Density-Functional Theory of Static and Dynamic Correlations in Complex Solids

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。它支持对多组分材料的计算研究，这些材料表现出不同程度的无序，具有化学、电荷和磁关联。例如金属(钢、磁铁和耐火材料)、电池材料以及铁电和超导氧化物。PI旨在发展一种基于密度泛函理论的静态和动态关联热力学理论，以预测和理解具有多亚晶格无序的多组分系统中的原子、磁和电荷关联。系统特有的电子和电子结构效应被并入变分密度泛函理论(DFT)线性响应框架内，该框架使用相干势近似及其扩展，用于构型平均。将开发计算效率高的线性响应算法，以将该理论整合到实用的计算框架中。具体目标包括：(I)发展一般晶格N组分合金中静态和动态关联的基于密度泛函理论的热力学理论，(Ii)通过对偏序合金的直接计算来验证预测，(Iii)将静态和动态关联与它们的电子来源联系起来，以便于具体材料的了解和相稳定性信息，以控制有序性，(Iv)适用于重要的氧化物、铁基磁体、镍基高温合金和耐火材料，(V)与正在进行的实验相联系。这项工作产生的计算工具，如KKR-CPA代码，将提供给更广泛的材料理论界。该奖项支持先进材料物理、计算技术和算法开发方面的教育。%该奖项是在回应ITR征集NSF-02-168时提交的一个小类别提案上颁发的。它支持对多组分材料的计算研究，这些材料表现出不同程度的无序，具有化学、电荷和磁关联。一些重要的例子包括金属(钢、磁铁和耐火材料)、电池材料以及铁电和超导氧化物。PI旨在发展一种基于密度泛函理论的静态和动态关联热力学理论，以预测和理解无序多组分系统中的原子、磁和电荷关联。计算将与最近和正在进行的实验相联系。这项工作产生的计算工具将提供给更广泛的材料理论社区。该奖项支持先进材料物理、计算技术和算法开发方面的教育。*

This award was made on a 'small' category proposal submitted in response to the ITR solicitation, NSF-02-168. It supports computational research into multicomponent materials exhibiting various levels of disorder with chemical, charge and magnetic correlations. Examples include metals (steels, magnets, and refractories), battery materials, and ferroelectric and superconducting oxides. The PI aims to develop a density-functional-theory-based thermodynamic theory of static and dynamic correlations to predict and understand the atomic, magnetic, and charge correlations in multi-component systems with multi-sublattice disorder. System-specific electronic and electronic-structure effects are incorporated on an equal basis within a variational density-functional-theory (DFT) linear-response framework using the coherent-potential-approximation, and its extensions, for configurational averaging. Computationally efficient linear-response algorithms will be developed to integrate the theory into a practical computational framework. Specific goals include: (I) developing a DFT-based thermodynamic theory of static and dynamic correlations in general lattice N-component alloys, (II) validating predictions via direct calculations for partially ordered alloys, (III) relating static and dynamic correlations to their electronic origin for materials-specific understanding and phase stability information for control of ordering, (IV) applying to important oxides, Fe-based magnets, Ni-based superalloys, and refractories, (V) connecting to on-going experiments. Computational tools resulting from this work such as KKR-CPA codes will be made available to the broader materials theory community. This award supports education in advanced materials physics, computational techniques, and algorithm development.%%%This award was made on a 'small' category proposal submitted in response to the ITR solicitation, NSF-02-168. It supports computational research into multi-component materials that exhibit various levels of disorder with chemical, charge and magnetic correlations. Some important examples include metals, (steels, magnets, and refractories), battery materials, and ferroelectric and superconducting oxides. The PI aims to develop a density-functional-theory-based thermodynamic theory of static and dynamic correlations to predict and understand the atomic, magnetic, and charge correlations in multi-component systems with disorder. Calculations will be performed to connect to recent and on-going experiments.Computational tools resulting from this work will be made available to the broader materials theory community. This award supports education in advanced materials physics, computational techniques, and algorithm development.***