Publication date: Dec 01, 2021
Landau-Lifshitz-Gilbert (LLG) spin-dynamics calculations based on the extended Heisenberg Hamiltonian is an important tool in computational materials science involving magnetic materials. LLG simulations allow to bridge the gap from expensive quantum mechanical calculations with small unit cells to large supercells where the collective behavior of millions of spins can be studied. In this work we present the AiiDA-Spirit plugin that connects the spin-dynamics code Spirit to the AiiDA framework. AiiDA provides a Python interface that facilitates performing high-throughput calculations while automatically augmenting the calculations with metadata describing the data provenance between calculations in a directed acyclic graph. The AiiDA-Spirit interface thus provides an easy way for high-throughput spin-dynamics calculations. The interface to the AiiDA infrastructure furthermore has the advantage that input parameters for the extended Heisenberg model can be extracted from high-throughput first-principles calculations including a proper treatment of the data provenance that ensures reproducibility of the calculation results in accordance to the FAIR principles. We describe the layout of the AiiDA-Spirit plugin and demonstrate its capabilities using selected examples for LLG spin-dynamics and Monte Carlo calculations. Furthermore, the integration with first-principles calculations through AiiDA is demonstrated at the example of gamma-Fe, where the complex spin-spiral ground state is investigated.
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File name | Size | Description |
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README.md
MD5md5:517038b1ca8909c3a1d9db41fb06becf
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1.8 KiB | Description of this dataset |
requirements.txt
MD5md5:12e38feb8503803471b4ddb45cb32b4f
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4.4 KiB | Python environment used in this work |
1-LLG-skyrmions.ipynb
MD5md5:c70e33c21fc819412ec23aae2e9ca0dc
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20.0 KiB | jupyter notebook for data generation and analysis of LLG calculations |
2-MonteCarlo.ipynb
MD5md5:08ad8117d1f6a913c6271e50d558d606
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12.5 KiB | jupyter notebook for data generation and analysis of Monte Carlo simulations |
3-gamma-Fe.ipynb
MD5md5:f9fdf063293d353b1ab0028976b05df3
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47.2 KiB | jupyter notebook for data generation and analysis of multi-scale modelling (DFT+LLG) simulations of gamma-Fe |
util1.py
MD5md5:5eea276e7fbb591df7925e149028f505
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6.0 KiB | utilities used in 1-LLG-skyrmions.ipynb |
util3.py
MD5md5:8f0f1cf68c2ac338b040159ba7ca5369
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10.9 KiB | utilities used in 3-gamma-Fe.ipynb |
cpa_jijs.py
MD5md5:728eb9eff8ed19f628078b9b34a79e0b
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24.0 KiB | utilities for parsing and postprocessing of Jij output from AiiDA-KKR |
LLG_toy_model.aiida
MD5md5:7453e44885645127c3d985413562ade0
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
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1.2 GiB | AiiDA export file for the data generated in 1-LLG-skyrmions.ipynb |
MC_toy_model.aiida
MD5md5:51078a18e7e004992e027f1c7302c0e2
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
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105.4 KiB | AiiDA export file for the data generated in 2-MonteCarlo.ipynb |
gamma_Fe.aiida
MD5md5:036f6ac9498578af1bf2a7364578562d
Open this AiiDA archive on renkulab.io (https://renkulab.io/)
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1.1 GiB | AiiDA export file for the data generated in 3-gamma-Fe.ipynb |
2021.203 (version v1) [This version] | Dec 01, 2021 | DOI10.24435/materialscloud:9s-tx |