Theoretical Spectroscopy and Thermodynamics of Correlated Electron Materials

Rutgers University New Brunswick, New Brunswick NJ

Investigators

Abstract

NONTECHNICAL SUMMARY This award supports research aimed at developing new computational tools and applying them to understand and predict properties of complex materials which show prominent competition of quantum effects such as magnetism, superconductivity, and "electronic correlation". While much progress has been made in understanding and accurately predicting properties of simple materials such as silicon or aluminum, in which electrons can be described as nearly free and independent of other electrons, materials exhibiting correlated electronic behavior, where the behavior of one electron is strongly dependent on the behavior of other electrons, are much harder to describe using existing computational tools. This project focuses on the development of new algorithms and software packages for such materials. In particular, the PI and his team will model and predict electronic properties of a class of superconductors, in which electricity can flow without any energy loss below a certain temperature, and which exhibit correlated electronic behavior and complex magnetic properties. The tools and codes developed in this project can allow computational materials scientists to theoretically characterize other quantum materials that are fundamental to the development of many modern technologies. This award also supports the training and mentorship of junior researchers by contributing to their career advancement and to the scientific workforce development. In addition, the algorithms and computer codes developed during the project will be freely shared with the materials science community through an existing open-source software package and enable theory-assisted materials design and discovery. TECHNICAL SUMMARY This award supports theoretical research aimed at developing new ab-initio computational tools and applying them to understand and predict properties of complex materials which show prominent competition of quantum effects such as electron correlation, magnetism, and superconductivity. One of the goals of this project is to develop the next generation cluster-Dynamical Mean Field Theory methods, which are expected to show less severe fermionic sign problem, and hence enable prediction of trends in correlated superconducting cuprates and nickelates. A second goal of the project is to extend the recently developed Variational Diagrammatic Monte Carlo method, which can be solved numerically exactly for the uniform electron gas problem, to an ab-initio setting and apply it to investigate electronic properties of conventional superconductors such as Li, Al, and solid hydrogen under extreme pressure, without the need for phenomenological parameters. The tools and codes developed in this project will allow one to theoretically characterize complex materials, which will give improved scientific understanding of quantum many-body phenomena and will provide a basis for harnessing many-body effects to develop functional materials including strong magnets and novel superconductors. This award also supports the training and mentorship of junior researchers by contributing to their career advancement and to the scientific workforce development. In addition, the algorithms and computer codes developed during the project will be freely shared with the materials science community through an existing open-source software package and enable theory-assisted materials design and discovery. 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.