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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Fe-Co-Zr Magnetic Materials: A DFT and Machine Learning Dataset

Authors: Xia, Weiyi; Moraru, Maxim; Li, Ying Wai; Liao, Timothy; Chelikowsky, James; Wang, Cai-Zhuang;

Fe-Co-Zr Magnetic Materials: A DFT and Machine Learning Dataset

Abstract

This dataset contains the key computational data, structural information, and validation files supporting the findings presented in the manuscript: "Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing." The data were generated using a high-throughput, machine learning-guided discovery framework (exa-AMD) coupled with first-principles calculations. This dataset is provided to facilitate open science, reproducible research, and further exploration of the Fe-Co-Zr ternary system for rare-earth-free permanent magnets. This repository includes: Crystallographic Information Files (CIFs):The 9 newly discovered thermodynamically stable Fe-Co-Zr compounds. The 2 engineered phases, Fe₅Co₁₈Zr₆ and Fe₅Co₁₆Zr₆Mn₄, derived from local atomic substitutions 3. The 81 unique, low-energy metastable Fe-Co-Zr compounds (with formation energies within 0.1 eV/atom above the convex hull). Dynamic Stability Data:Raw data files for the phonon dispersion calculated for the 11 key stable and derived compounds. Raw data files from the ab initio molecular dynamics (AIMD) simulation of FeCo₅Zr₁₂, including energy trajectory and radial distribution function (RDF) data. Model Validation Data: Raw data used to generate the comparison plot of ML-predicted vs. DFT-calculated formation energies for the converged structures.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average