Modern society continues to benefit from developments of technology, though this trend is demanding enormous resources from our planet and is resulting in dramatic changes to our environment. One of the keys to advancing environmentally friendly technologies is to develop and control the underlying materials and their properties. These materials are comprised of collections of precisely arranged atoms which, in turn, consist of nuclei surrounded by much lighter electrons. The behavior of these electrons is governed by quantum mechanics and their motions largely determine the properties of materials. One of the grand challenges therefore becomes one of understanding and controlling materials processes at the level of the electrons.
The Sun group at Tulane University (MaTComp) is interested in developing electronic structure methods to predict properties and behaviors of materials as well as to computationally design materials that are scientifically, technologically, and economically important.
The group’s research is based around the density functional theory (DFT) of electronic structure, and the group leader with his collaborators has developed the strongly-constrained and appropriately-normed (SCAN) density functional, a major advance in DFT. The group is applying SCAN and SCAN-based density functionals to study quantum materials that are challenging to traditional density functionals like local spin density approximation (LSDA) and the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA), with the support from the energy frontier research center (EFRC) program of Department of Energy (DOE). In particular we study cuprates, iron-based superconductors, topological materials, and magnetic materials as quantum materials of special interest.
Another current focus of the group is in developing a non-empirical non-local density functional to formally solve the self-interaction errors and strong correlations that are challenging for semi-local density functionals, including SCAN, with the support from the DOE. We are also working on developing density functionals for van der Waals interactions with a focus on the effect of metallic screening, supported by ACS-PRF.
The group has strong interests in collaborating with experimental groups to help understand mechanisms of emergent properties or chemical reactivities of materials, and to discover/design materials for particular properties/applications by high throughput computations and machine learning. We are a part of the Louisiana Consortium of Neutron Scattering (LaCNS) studying the couplings between charge, spin, orbital, and lattice degrees of freedom in magnetic materials. We have on-going collaborations with Prof. Zhiqiang Mao’s group at Penn State University for computational materials synthesis that can guide experimental synthesis, funded by the DOE. The group is collaborating with different experimental groups studying the catalysis of important reactions, such as water splitting, with different funding resources.
Besides the funded research mentioned above, the group members are actively working in improving density functionals by machine learning, quantum computation for DFT, molecular magnets, superconductivity, and strongly correlated topological materials.