Assistant Professor, Department of Chemistry, CSU Northridge
Visiting Professor, Beijing Comput. Sci. Res. Center
Email: firstname.lastname@example.org; email@example.com
My major interests on method development is large scale electronic structure simulation based on orbital free density funcional theory, and automatic unbiased structure search for functional materials, surfaces and interfaces etc.
Structure search for 2D materials and surface reconstructions
It is well-known that determining the surface structure is an important, but challenging step toward the understanding of its effect to the performance of devices. The experimental studies of the surface structures are often impeded by the fact that the semiconductor surfaces undergo complicated reconstructions and are severely disturbed by the chemical processes such as surface oxidation. On the theory side, numerous surface reconstruction simulations were carried out, most of which were relied on the educated structures either known from other materials or initialized by chemical intuition. There is a growing need on the intelligent structure searching method on surfaces not relying on any prior known surface structure information. We develop an automatic surface structure searching method by virtue of the structure swarm intelligence, a technique recently developed for searching global minimum in a complex configuration space. We improve the search efficiency by implementing the symmetry group of surfaces and the chemical constraints on surface structures.
Two-dimensional (2D) materials are of special importance because of their unusual electronic and structural properties. We developed a structure prediction method for layered materials based on two-dimensional (2D) particle swarm optimization algorithm. The relaxation of atoms in the perpendicular direction within a given range is allowed. Additional techniques including structural similarity determination, symmetry constraint enforcement, and discretization of structure constructions based on space gridding are implemented and demonstrated to significantly improve the global structural search efficiency. Our method is successful in predicting the structures of known 2D materials, including single layer and multi-layer graphene, 2D BN compounds and some quasi-2D group VIB chalcogenides.
Local pseudopotentials for large scale DFT calculations
Local pseudopotentials have advantages in many aspects of computational study of materials such as the orbital-free density functional calculations and the quantum Monte Carlo method. The current local pseudopotentials are limited by their transferability as they are usually constructed empirically for atoms in certain chemical environments and do not satisfy norm-conserving (NC) condition. We found that local NC pseudopotentials can be constructed by taking the Slater average of the first principles NC pseudopotentials for large number of elements, including most of the group I and II elements and the elements with atom numbers larger than Ga. For these elements, the Slater averaged potentials are exact optimized effective potentials (OEP) of the original NC pseudopotentials and can achieve accuracy to first principles level.