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Recent developments in the Inorganic Crystal Structure Database: theoretical crystal structure data and related features
Open accessAbstract
The Inorganic Crystal Structure Database (ICSD) is the world's largest database of fully evaluated and published crystal structure data, mostly obtained from experimental results. However, the purely experimental approach is no longer the only route to discover new compounds and structures. In the past few decades, numerous computational methods for simulating and predicting structures of inorganic solids have emerged, creating large numbers of theoretical crystal data. In order to take account of these new developments the scope of the ICSD was extended in 2017 to include theoretical structures which are published in peer-reviewed journals. Each theoretical structure has been carefully evaluated, and the resulting CIF has been extended and standardized. Furthermore, a first classification of theoretical data in the ICSD is presented, including additional categories used for comparison of experimental and theoretical information.
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Cites
The Cambridge Structural Database
Groom, C. R., Bruno, I. J., Lightfoot, M. P., & Ward, S. C. (2016) · Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials · doi:10.1107/s2052520616003954 · Cited by 10,297
The high-throughput highway to computational materials design
Curtarolo, S., Hart, G. L. W., Nardelli, M. B., Mingo, N., Sanvito, S., & Levy, O. (2013) · Nature Materials · doi:10.1038/nmat3568 · Cited by 2,053
Belsky, A., Hellenbrandt, M., Karen, V. L., & Luksch, P. (2002) · Acta Crystallographica Section B Structural Science · doi:10.1107/s0108768102006948 · Cited by 1,379
Curtarolo, S., Setyawan, W., Wang, S., Xue, J., Yang, K., Taylor, R. H., Nelson, L. J., Hart, G. L. W., Sanvito, S., Buongiorno-Nardelli, M., et al. (2012) · Computational Materials Science · doi:10.1016/j.commatsci.2012.02.002 · Cited by 1,148
Hautier, G., Fischer, C. C., Jain, A., Mueller, T., & Ceder, G. (2010) · Chemistry of Materials · doi:10.1021/cm100795d · Cited by 580
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A foundation model for atomistic materials chemistry
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A generative model for inorganic materials design
Zeni, C., Pinsler, R., Zügner, D., Fowler, A., Horton, M., Fu, X., Wang, Z., Shysheya, A., Crabbé, J., Ueda, S., et al. (2025) · Nature · doi:10.1038/s41586-025-08628-5 · Cited by 518
Wide Band Gap Chalcogenide Semiconductors
Woods-Robinson, R., Han, Y., Zhang, H., Ablekim, T., Khan, I., Persson, K. A., & Zakutayev, A. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00600 · Cited by 513
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Metadata
- Authors
- Zagorac, D., Müller, H., Ruehl, S., Zagorac, J., & Rehme, S.
- Venue
- Journal of Applied Crystallography
- Published
- 2019-09-23
- Volume
- 52
- Issue
- 5
- Pages
- 918-925
- ISSN
- 0021-8898 (ISSN-L)
- 1600-5767
- OpenAlex
- W2975270375
- Cited by
- 744
- References
- 5
- FWCI
- 11.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Zagorac, D., Müller, H., Ruehl, S., Zagorac, J., & Rehme, S. (2019). Recent developments in the Inorganic Crystal Structure Database: theoretical crystal structure data and related features. Journal of Applied Crystallography. https://doi.org/10.1107/s160057671900997x
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