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

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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.***