Discovering rare-earth-free magnetic materials through the development of a database

Masahiro Sakurai, Renhai Wang, Timothy Liao, Chao Zhang, Huaijun Sun, Yang Sun, Haidi Wang, Xin Zhao, Songyou Wang, Balamurugan Balasubramanian, Xiaoshan Xu, David J. Sellmyer, Vladimir Antropov, Jianhua Zhang, Cai Zhuang Wang, Kai Ming Ho, James R. Chelikowsky

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


We develop an open-access database that provides a large array of datasets specialized for magnetic compounds as well as magnetic clusters. Our focus is on rare-earth-free magnets. Available datasets include (i) crystallography, (ii) thermodynamic properties, such as the formation energy, and (iii) magnetic properties that are essential for magnetic-material design. Our database features a large number of stable and metastable structures discovered through our adaptive genetic algorithm (AGA) searches. Many of these AGA structures have better magnetic properties when compared to those of the existing rare-earth-free magnets and the theoretical structures in other databases. Our database places particular emphasis on site-specific magnetic data, which are obtained by high-throughput first-principles calculations. Such site-resolved data are indispensable for machine-learning modeling. We illustrate how our data-intensive methods promote efficiency of the experimental discovery of new magnetic materials. Our database provides massive datasets that will facilitate an efficient computational screening, machine-learning-assisted design, and the experimental fabrication of new promising magnets.

Original languageEnglish (US)
Article number114408
JournalPhysical Review Materials
Issue number11
StatePublished - Nov 11 2020

ASJC Scopus subject areas

  • Materials Science(all)
  • Physics and Astronomy (miscellaneous)


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