Devi, A. A. S., Nokelainen, J., Barbiellini, B., Devaraj, M., Alatalo, M., & Bansil, A. (2022). Re-examining the giant magnetization density in α′′-Fe 16 N 2 with the SCAN+ U method. Physical Chemistry Chemical Physics, 24(29), 17879–17884. https://doi.org/10.1039/D2CP01734B
Re-examining the giant magnetization density in α′′-Fe16N2 with the SCAN+U method
|Author:||Sasikala Devi, Assa Aravindh1; Nokelainen, Johannes2,3; Barbiellini, Bernardo2,3;|
1Nano and Molecular Systems Research Unit, University of Oulu, P.O. Box 8000, FI-90014, Finland
2Lappeenranta-Lahti University of Technology (LUT), FI-53851 Lappeenranta, Finland
3Department of Physics, Northeastern University, Boston, MA 02115, USA
4Department of Sciences, Indian Institute of Information Technology Design and Manufacturing, Kurnool, Andhra Pradesh, India
|Online Access:||PDF Full Text (PDF, 0.9 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022112266509
Royal Society of Chemistry,
|Publish Date:|| 2022-11-22
We present an in-depth discussion of the magnetic ground state of α′′-Fe16N2 within the framework of the density functional theory (DFT). 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. We also delineate effects of adding an on-site interaction parameter U on the Fe sites. 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 self-interaction corrections applied on different Fe sites through the parameter U can reproduce both the correct equilibrium volume and the giant magnetization density of α′′-Fe16N2.
PCCP. Physical chemistry chemical physics
|Pages:||17879 - 17884|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
116 Chemical sciences
114 Physical sciences
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 of Science, 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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