Joint MSE Colloquium with the Center for Computational Science (CCS)
Towards computational design of correlated functional materials from first-principles
Abstract: In the past decade, there has been a remarkable advance in theory, algorithms, and computational techniques for describing strongly correlated materials from first-principles. In this talk, I will introduce methods that can be used to understand and even predict physical properties of existing and new correlated materials. I will illustrate that a combination of density functional theory and dynamical mean field theory DFT+DMFT) describes well both the paramagnetic and antiferromagnetic states of the iron pnictide and chalcogenide superconductors. They are Hund’s metals and have very different physics from the cuprate superconductors. Their charge and spin dynamics (e.g., optical conductivity and magnetic excitations), Fermi surface, mass enhancements, etc., and the variations among different families are well reproduced by DFT+DMFT calculations.[1-4] I will further show that the GW method and screened hybrid functional density functional theory, on the other hand, not only account for the normal state properties of the celebrated bismuthate and chloronitride superconductors but also explain their mysterious high critical superconducting temperatures. In the end, I will demonstrate, by designing a new family of correlated mixed-valent materials as candidates for high temperature superconductors, that these methods can be used for computational design of correlated materials with desirable properties thus have great potentials for both academic research and industry applications in the future.
 Z. P. Yin, K. Haule, and G. Kotliar, Nat. Mater. 10, 932-935 (2011).
 Z. P. Yin, K. Haule, and G. Kotliar, Nat. Phys. 7, 294-297 (2011).
 Z. P. Yin, K. Haule, and G. Kotliar, Phys. Rev. B 86, 195141 (2012).
 Z. P. Yin, K. Haule, and G. Kotliar, to be submitted (2013).
 Z. P. Yin, A. Kutepov, and G. Kotliar, submitted to Phys. Rev. X, see also arXiv:1110.5751.
 Z. P. Yin and G. Kotliar, EPL 101, 27002(2013).