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Curation and featurization of multiple topological materials databases |
| Yuqing He(贺雨晴)1, Matteo Giantomassi2, Gian-Marco Rignanese2,3,4,†, and Hongming Weng(翁红明)1,‡ |
1 Beijing National Laboratory for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China;
2 Institute of Condensed Matter and Nanosciences, UCLouvain, Chemin des Étoiles 8, 1348 Louvain-la-Neuve, Belgium;
3 WEL Research Institute, Avenue Pasteur 6, 1300 Wavre, Belgium;
4 School of Materials Science and Engineering, Northwestern Polytechnical University, Xi'an 710072, China |
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Abstract The discovery of topological materials has advanced rapidly due to high-throughput computation and machine learning, but research progress is hampered by inconsistent classification standards and fragmented data resources. Existing databases differ in computational methods, material coverage, and labeling criteria, making it difficult to compare findings across studies. To overcome these challenges, we present a unified topological materials dataset that systematically combines and reconciles two major databases: Materiae and the Topological Materials Database. This dataset provides consistent topological classifications for 35608 materials, accessible through the Materials Galaxy platform for interactive exploration and available for bulk download via MatElab. We describe the featurization methodology that converts crystal structures into 4710 machine-learning-ready descriptors and present a comprehensive analysis of topological material distributions. This work serves as a complete guide for accessing, utilizing, and interpreting this unified resource, designed to enable reproducible machine learning applications and accelerate the discovery of topological materials.
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Received: 27 October 2025
Revised: 11 December 2025
Accepted manuscript online: 12 December 2025
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PACS:
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07.05.Kf
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(Data analysis: algorithms and implementation; data management)
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| Fund: Y. H. and H. W. acknowledge financial support from the National Key Research and Development Program of China (Grant No. 2022YFA1403800), the National Natural Science Foundation of China (Grant Nos. 12188101 and 11925408), and the Chinese Academy of Sciences (Grant No. XDB33000000). |
Corresponding Authors:
Gian-Marco Rignanese,E-mail:gian-marco.rignanese@uclouvain.be;Hongming Weng,E-mail:hmweng@iphy.ac.cn
E-mail: gian-marco.rignanese@uclouvain.be;hmweng@iphy.ac.cn
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Cite this article:
Yuqing He(贺雨晴), Matteo Giantomassi, Gian-Marco Rignanese, and Hongming Weng(翁红明) Curation and featurization of multiple topological materials databases 2026 Chin. Phys. B 35 050701
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