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High-throughput magnetic co-doping and design of exchange interactions in topological insulators

Rubel Mozumder1, Johannes Wasmer1, David Antognini Silva1, Stefan Blügel1, Philipp Rüßmann1,2*

1 Peter Grünberg Institute (PGI-1), Forschungszentrum Jülich, 52425 Jülich, Germany

2 Institute for Theoretical Physics and Astrophysics, University of Würzburg, 97074 Würzburg, Germany

* Corresponding authors emails: philipp.ruessmann@uni-wuerzburg.de
DOI10.24435/materialscloud:b7-6k [version v2]

Publication date: Sep 23, 2024

How to cite this record

Rubel Mozumder, Johannes Wasmer, David Antognini Silva, Stefan Blügel, Philipp Rüßmann, High-throughput magnetic co-doping and design of exchange interactions in topological insulators, Materials Cloud Archive 2024.141 (2024), https://doi.org/10.24435/materialscloud:b7-6k

Description

Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical topological insulators (TIs) Bi₂Te₃ and Bi₂Se₃. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of non-magnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian. We uncover chemical trends in the exchange coupling constants and discuss the impurities' potential with respect to magnetic order in the fields of quantum anomalous Hall insulators. In particular, we predict that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs.

Materials Cloud sections using this data

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Files

File name Size Description
README.md
MD5md5:7b0d99083467b6cc0a2215d8b07873d7
6.8 KiB Description of the dataset
Jij_table.csv
MD5md5:e73c49c9da7b0653f2de3e0e4466eaa4
412.7 KiB Extracted table of Jij values in Bi2Te3
Jij_table_Bi2Se3.csv
MD5md5:ee5a576a480383110369d5cd5d5785cc
129.1 KiB Extracted table of Jij values in Bi2Se3
data_analysis_Bi2Te3.ipynb
MD5md5:690b41fab7da399fd6828b77b36e327a
1.4 MiB Jupyter notebook containing data analysis and plotting of the Bi2Te3 results of this work
data_analysis_Bi2Se3.ipynb
MD5md5:d6becb343f5b88073a822e2458c549f4
751.5 KiB Jupyter notebook containing data analysis and plotting of the Bi2Se3 results of this work
Tcs_Bi2Se3.txt
MD5md5:b1aef8401be53d5e6a47a9f706ca2127
9.8 KiB Calculated mean field Tc values for magnetic dopants in Bi2Se3
Tcs_Bi2Te3.txt
MD5md5:1c8a734b01a5b6c2aa18e95a0e2ddc49
9.8 KiB Calculated mean field Tc values for magnetic dopants in Bi2Te3
export_all.aiida
MD5md5:a0420830661cdf8aad769abb5a179766
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
43.0 GiB AiiDA export file containing calculations for Bi2Te3 of this dataset
export_DOS.aiida
MD5md5:3851f38ea8c29637fdcd11e5341823db
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
356.8 MiB AiiDA export file containing DOS calculations for single impurities in Bi2Te3
export_k_convergence.aiida
MD5md5:540b228d33dcc13ad4f5c5101b852e73
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
2.2 GiB AiiDA export file containing calculations proving convergence of the results
export_Bi2Se3.aiida
MD5md5:0b9ec4591397cb0e0ddd1b3129447dbb
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
14.0 GiB AiiDA export file containing calculations for Bi2Se3 of this dataset
Bi2Te3.cif
MD5md5:f714130613532a4063571c361bc6dc46
1.5 KiB Basic host crystal structure of Bi2Te3
Bi2Te3_structure_low_res.png
MD5md5:6809195c59d44c3ad0fe1f41e7b0df7f
103.6 KiB Visualization of the host crystal structure
requirements.txt
MD5md5:dc508fbf3e879913a4f482ec2b6d658f
6.6 KiB Python environment used in data creation and analysis

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Preprint (Preprint where the data is discussed)
Software (Source code for the AiiDA-KKR plugin)
Journal reference (AiiDA-KKR method paper)
P. Rüßmann, F. Bertoldo, and S. Blügel, The AiiDA-KKR plugin and its application to high-throughput impurity embedding into a topological insulator. npj Comput Mater 7, 13 (2021) doi:10.1038/s41524-020-00482-5
Software (Source code of the JuKKR code)

Keywords

DFT topological materials topological insulator quantum anomalous Hall magnetic doping co-doping JuKKR

Version history:

2024.141 (version v2) [This version] Sep 23, 2024 DOI10.24435/materialscloud:b7-6k
2024.103 (version v1) Jul 04, 2024 DOI10.24435/materialscloud:c9-9x