This research uses first-principles methods to perform materials design: not only explain, but also predict the properties of crystalline matter, and come up with new compounds with superior physical properties. The group's research interests lie on the intersection of solid state physics, structural chemistry, and materials science. The long-term research goal is to identify materials realizations of the exotic phases in condensed matter.
The researchers work on a wide array of materials that host interesting phenomena, such as ferroelectrics, multiferroics, spin-orbit coupled Mott insulators, and high-temperature superconductors. Their ab initio tool box includes not only the standard Kohn-Sham Density Functional Theory (DFT), but also more advanced methods that build upon DFT, such as the Embedded Dynamical Mean Field Theory, and evolutionary structure prediction algorithms. Software packages used include Abinit, VASP and Wien2K for DFT, eDMFT (previously known as DMFT-Wien2K) for DMFT, and USPEX for evolutionary structure prediction. The researchers also use a number of scripts, mostly written in Python, to performs calculations of different quantities, such as the Lindhardt functions on fine grids.