Publication date: Sep 23, 2024
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.
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File name | Size | Description |
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README.md
MD5md5:7b0d99083467b6cc0a2215d8b07873d7
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6.8 KiB | Description of the dataset |
Jij_table.csv
MD5md5:e73c49c9da7b0653f2de3e0e4466eaa4
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412.7 KiB | Extracted table of Jij values in Bi2Te3 |
Jij_table_Bi2Se3.csv
MD5md5:ee5a576a480383110369d5cd5d5785cc
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129.1 KiB | Extracted table of Jij values in Bi2Se3 |
data_analysis_Bi2Te3.ipynb
MD5md5:690b41fab7da399fd6828b77b36e327a
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1.4 MiB | Jupyter notebook containing data analysis and plotting of the Bi2Te3 results of this work |
data_analysis_Bi2Se3.ipynb
MD5md5:d6becb343f5b88073a822e2458c549f4
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751.5 KiB | Jupyter notebook containing data analysis and plotting of the Bi2Se3 results of this work |
Tcs_Bi2Se3.txt
MD5md5:b1aef8401be53d5e6a47a9f706ca2127
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9.8 KiB | Calculated mean field Tc values for magnetic dopants in Bi2Se3 |
Tcs_Bi2Te3.txt
MD5md5:1c8a734b01a5b6c2aa18e95a0e2ddc49
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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/)
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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/)
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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/)
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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/)
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14.0 GiB | AiiDA export file containing calculations for Bi2Se3 of this dataset |
Bi2Te3.cif
MD5md5:f714130613532a4063571c361bc6dc46
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1.5 KiB | Basic host crystal structure of Bi2Te3 |
Bi2Te3_structure_low_res.png
MD5md5:6809195c59d44c3ad0fe1f41e7b0df7f
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103.6 KiB | Visualization of the host crystal structure |
requirements.txt
MD5md5:dc508fbf3e879913a4f482ec2b6d658f
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6.6 KiB | Python environment used in data creation and analysis |
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 |