Dataset and codes for: Analysis of Magnetocrystalline Anisotropy from Atom Pair Statistics in Tetragonally Strained Fe-Based Alloys: A First-Principles and Machine Learning Study

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Authors: Wen-Chuang Shang
Cited by: 0

Abstract

This Zenodo record contains the data and codes used to reproduce paper Figures 3–8. The data are derived VASP outputs (in CSV form). The full extraction workflow for the CSV data and implementation details are documented in the README. For size and reproducibility reasons, raw VASP outputs (OUTCAR/PROCAR/vasprun.xml, etc.) are not included. Contents: Data: FeSi/ and FeX_SiGeGaAl/ CSV files Utilities: data_utils.py, feature_utils.py Plot scripts: fig3_*.py–fig8_*.py, which generate the corresponding PDF figures Environment and reproduction: Python 3.8+ with numpy, pandas, matplotlib, scikit-learn environment.yml (conda) and README instructions are provided Run the scripts from this directory (e.g., python3 fig*.py) to reproduce Figures 3–8

Fields of Study & Subjects

Machine Learning in Materials Science Magnetic Properties of Alloys Magnetic Properties and Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
10 January 2026
Document type
Dataset