Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session Q53: Magnetism in Correlated Electron Systems II: Experiment & Theory
3:00 PM–5:48 PM,
Wednesday, March 16, 2022
Room: McCormick Place W-475B
Sponsoring
Units:
GMAG DCMP
Chair: Saikat Banerjee, Los Alamos National Laboratory
Abstract: Q53.00012 : Re-examining the giant magnetization density in α′′-Fe16N2 with the SCAN +U formalism*
5:12 PM–5:24 PM
Presenter:
Assa Aravindh Sasikala Devi
(Univ of Oulu)
Authors:
Assa Aravindh Sasikala Devi
(Univ of Oulu)
Johannes S Nokelainen
(Northeastern University)
Bernardo Barbiellini
(Northeastern University)
Murali Devaraj
(IIITDM, Kurnool, India)
Arun Bansil
(Northeastern University)
Matti Alatalo
(University of Oulu)
An in-depth investigation of the magnetic ground state of α′′-Fe16N2 within the frame work of the density functional theory (DFT) is carried out. The exchange-correlation effects are treated using a variety of schemes, including the local-spin-density approximation, the generalized-gradient approximation, and the Strongly-Constrained-and-Appropriately-Normed (SCAN) scheme. The effects of adding an on-site interaction parameter U on the Fe sites is tested and delineated. Among all the schemes considered, only SCAN + U is found to capture the surprisingly large magnetization density in α′′-Fe16N2 that has been observed experimentally. Our study shows how the combination of SCAN and different self-interaction corrections applied on the system through the parameter U can reproduce both the correct equilibrium volume and the giant magnetization density of α′′-Fe16N2.
*S. A. A. acknowledges support from Academy of Finland grant (311934). Authors gratefully acknowledge CSC-IT, Finland, for computational resources and J. N.acknowledges support from the INERCOM LUT platform. The work at Northeastern University was supported by the US Department of Energy (DOE), Office ofScience, Basic Energy Sciences grant number DE-FG02-07ER46352, and benefited from Northeastern University’s Advanced Scientific Computation Center (ASCC) and the NERSC supercomputing center through DOE grant number DE-AC02-05CH11231.
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