Abstract
Using an atomistic model that treats both translational and spin degrees of freedom, we have performed combined molecular and spin dynamics simulations to study dynamic properties of BCC iron with varying vacancy concentrations. Atomic interactions are described by an empirical many-body potential while spin interactions are handled with a Heisenberg-like Hamiltonian with a coordinate dependent exchange interaction. By calculating the Fourier transform of spatial and temporal correlation functions, vibrational and magnetic excitations have been studied. The creation of vacancies in the material has shown splitting of the characteristic transverse spin-wave excitations, indicating the production of additional excitation modes. By merging two vacancies to form a nearest neighbor pair, we find that these modes become more distinct. Investigation of longitudinal spin-wave excitations reveals interactions between constituent components of the split transverse excitations.
| Original language | English |
|---|---|
| Article number | 012007 |
| Journal | Journal of Physics: Conference Series |
| Volume | 921 |
| Issue number | 1 |
| DOIs | |
| State | Published - Nov 19 2017 |
| Event | 30th Workshop on Recent Developments in Computer Simulation Studies in Condensed Matter Physics - Athens, United States Duration: Feb 20 2017 → Feb 24 2017 |
Funding
This material is based upon work (M.M.) supported by the U. S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists, Office of Science Graduate Student Research (SCGSR) Program. The SCGSR Program is administered by the Oak Ridge Institute for Science and Education for the DOE under contract name DE-SC0014664. Part of this work (M.E. and G. M. S.) was supported by the Materials Sciences & Engineering Division of the Office of Basic Energy Sciences, U.S. Department of Energy. This study was supported in part by resources and technical expertise from the Georgia Advanced Computing Resource Center, a partnership between the University of Georgia’s Office of the Vice President for Research and Office of the Vice President for Information Technology. This research used resources of the Oak Ridge Leadership Computing Facility at ORNL, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.