Unraveling effects of electron correlation in two-dimensional Fe n GeTe2 (n = 3, 4, 5) by dynamical mean field theory

Bibliographic Details
Title: Unraveling effects of electron correlation in two-dimensional Fe n GeTe2 (n = 3, 4, 5) by dynamical mean field theory
Authors: Sukanya Ghosh, Soheil Ershadrad, Vladislav Borisov, Biplab Sanyal
Source: npj Computational Materials, Vol 9, Iss 1, Pp 1-16 (2023)
Publisher Information: Nature Portfolio, 2023.
Publication Year: 2023
Collection: LCC:Materials of engineering and construction. Mechanics of materials
LCC:Computer software
Subject Terms: Materials of engineering and construction. Mechanics of materials, TA401-492, Computer software, QA76.75-76.765
More Details: Abstract The Fe n GeTe2 systems are recently discovered two-dimensional van-der-Waals materials, exhibiting magnetism at room temperature. The sub-systems belonging to Fe n GeTe2 class are special because they show site-dependent magnetic behavior. We focus on the critical evaluation of magnetic properties and electron correlation effects in Fe n GeTe2 (n = 3, 4, 5) (FGT) systems performing first-principles calculations. Three different ab initio approaches have been used primarily, viz., (i) standard density functional theory (GGA), (ii) incorporating static electron correlation (GGA + U) and (iii) inclusion of dynamic electron correlation effect (GGA + DMFT). Our results show that GGA + DMFT is the more accurate technique to correctly reproduce the magnetic interactions, experimentally observed transition temperatures and electronic properties. The inaccurate values of magnetic moments, exchange interactions obtained from GGA + U make this method inapplicable for the FGT family. Correct determination of magnetic properties for this class of materials is important since they are promising candidates for spin transport and spintronic applications at room temperature.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2057-3960
Relation: https://doaj.org/toc/2057-3960
DOI: 10.1038/s41524-023-01024-5
Access URL: https://doaj.org/article/d351b2dd2db9441aaeeb84a8c2ddaee6
Accession Number: edsdoj.351b2dd2db9441aaeeb84a8c2ddaee6
Database: Directory of Open Access Journals
More Details
ISSN:20573960
DOI:10.1038/s41524-023-01024-5
Published in:npj Computational Materials
Language:English