## Project Details

### Description

NON-TECHNICAL SUMMARYThis award supports theoretical and computational research and education directed towards a transformative acceleration of progress in our understanding of complex materials, which show prominent competitions of quantum mechanical effects such as strong electron interaction, magnetism and superconductivity. For simpler materials for which the physical properties can be accurately represented in terms of a system of independent particles in the presence of an average potential, methods based on Density Functional Theory have enabled large-scale simulations of realistic systems with high accuracy. For materials in which electrons interact strongly and the 'independent-particle' picture is not as reliable, the so-called Dynamical Mean Field Theory method has enabled practical and accurate calculations of their basic properties. This project is aimed at developing a number of new theoretical tools, which can be used in combination with electronic structure tools based on Dynamical Mean Field Theory to enable theoretical prediction of material properties without using empirical parameters.The project will enable the construction of a predictive framework for describing the physical properties of materials in which electron-electron interactions play a very important role. The tools and codes developed in this project will allow one to theoretically characterize complex materials, which will lead to improved scientific understanding of quantum many-body effects, and will provide a basis for harnessing such effects to develop functional materials such as strong magnets and novel superconductors. The educational component of this project involves the training of the next generation of scientists in an interdisciplinary environment at the intersection of theoretical physics, computational physics, and materials science. The PI will also be involved in public outreach activities by mentoring and providing summer research experiences for high school students through the Liberty Science Center in New Jersey.TECHNICAL SUMMARYTo search for new materials with enhanced physical properties it is crucial to develop capabilities for computational characterization of a material. This award supports theoretical and computational research and education directed toward developing a number of theoretical spectroscopic tools, which can be used in combination with electronic structure tools based on Dynamical Mean Field Theory to enable theoretical prediction of material properties using first principles methods. The spectroscopic tools to be developed will be used for (i) computing dynamical structure factors measured in neutron spectroscopy experiments, (ii) predicting the symmetry of the superconducting order parameter in unconventional superconductors, (iii) Auger spectroscopy, which can be used to measure the strength of correlations and to theoretically estimate the strength of the Coulomb interaction, (iv) Raman spectroscopy which can identify the low frequency excitations of the solid, and (v) computing the free energy of a solid for studying phase transitions at finite temperatures. The project will enable the construction of a predictive framework for describing the physical properties of correlated materials. The tools and codes developed in this project will allow one to theoretically characterize complex materials, which will lead to improved scientific understanding of quantum many-body effects, and will provide a basis for harnessing such effects to develop functional materials such as strong magnets and novel superconductors. The educational component of this project involves the training of the next generation of scientists in an interdisciplinary environment at the intersection of theoretical physics, computational physics, and materials science. The PI will also be involved in public outreach activities by mentoring and providing summer research experiences for high school students through the Liberty Science Center in New Jersey.

Status | Finished |
---|---|

Effective start/end date | 9/1/14 → 8/31/17 |

### Funding

- National Science Foundation (National Science Foundation (NSF))

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