Papers
Topics
Authors
Recent
Search
2000 character limit reached

Dynamical Mean-Field Theory for Molecules and Nanostructures

Published 5 Sep 2011 in physics.atm-clus | (1109.0893v1)

Abstract: Dynamical Mean-Field Theory (DMFT) has established itself as a reliable and well-controlled approximation to study correlation effects in bulk solids and also two-dimensional systems. In combination with standard density-functional theory (DFT) it has been successfully applied to study materials in which localized electronic states play an important role. There are several evidences that for extended systems this DMFT+DFT approach is more accurate than the traditional DFT+U approximation, particularly because of its ability to take into account dynamical effects, such as the time-resolved double occupancy of the electronic orbitals. It was recently shown that this approach can also be successfully applied to study correlation effects in nanostructures. Here, we present a brief review of the recently proposed generalizations of the DFT+DMFT method. In particular, we discuss in details our recently proposed DFT+DMFT approach to study the magnetic properties of nanosystems [V. Turkowski, A. Kabir, N. Nayyar and T. S Rahman, J. Phys.: Condens. Matter (Fast Track) 22, 462202 (2010)] and present its application to small (up to five atoms) Fe and FePt clusters. We demonstrate that being a mean-field approach, DMFT produces meaningful results even for such small systems. We compare our results with those obtained using DFT+U and find that, as in the case of bulk systems, the latter approach tends to overestimate correlation effects in nanostructures. Finally, we discuss possible ways to farther improve the nano-DFT+DMFT approximation and to extend its application to molecules and nanoparticles on substrates and to nonequilibrium phenomena.

Summary

Paper to Video (Beta)

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.