NONTECHNICAL SUMMARY This award supports theoretical and computational research and education to advance understanding of strongly correlated materials which have unusual properties and to improve their theoretical description. Materials are ubiquitous in our daily life and improving them is key for future technological progress. This project advances the methods, concepts, techniques and computer codes needed to understand and predict the properties of strongly correlated electron materials. In these solids, the strong interactions among electrons lead to correlations in their motions that are challenging to describe in standard theoretical frameworks. Strongly correlated electron materials display a wealth of new and unusual physical properties, ranging from superconductivity at unusually high temperature to materials that transform from metals to insulators, a process that depends sensitively on external conditions. Superconductivity enables the flow of electric currents without resistance, while metal to insulator transitions are used in fast switches and new memory devices. A goal is to advance the predictive power of the theory to accelerate the process of material discovery and design.This project enables multiple educational activities, such as the training of undergraduate and graduate students, as well as postdoctoral associates, in the use of analytical and computational methods, and the use of computational facilities. Research will be disseminated through journal publications and the internet, as well as through seminars, conferences and schools. TECHNICAL SUMMARY This award supports theoretical and computational research and education to advance understanding of strongly correlated materials and to improve their theoretical description. This award supports developing methods, concepts, theory, algorithms and computer codes to understand the physical properties of strongly correlated materials in and out of equilibrium. A long-term goal is to enhance predictive power to accelerate the process of material discovery and design utilizing strongly correlated materials. Simplified many-body Hamiltonians will be constructed and used to understand qualitative aspects of strong correlation phenomena at low energies with computationally intensive calculations that model more accurately the microscopic complexity of real materials. Computational methods include combining electronic structure and dynamical mean-field theory. This project will continue the development and testing of this non-perturbative approach on materials of current experimental interest. In materials proximate to the Mott transition, the physics is governed by charge blocking. The PI will explore the implications of strong correlations near a Mott transition in nonequilibrium steady states in the presence of dissipation and electric fields. In Hund's metals, the physics is governed by spin blocking while the charge fluctuates strongly. The PI aims to develop the theory of Hund's metal and apply it to prototypical systems such as the iron pnictides and chalcogenide high-temperature superconductors and the ruthenium oxides. This project enables multiple educational activities, such as the training of undergraduate and graduate students, as well as postdoctoral associates, in the use of analytical and computational methods, and the use of computational facilities. Research will be disseminated through journal publications and the internet, as well as through seminars, conferences and schools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|Effective start/end date||6/1/18 → 5/31/21|
- National Science Foundation (National Science Foundation (NSF))
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