VII. About

Contributors

• Miguel Marques (rcFEMS, ICAMS, Ruhr University Bochum)
• Silvana Botti (rcFEMS, ICAMS, Ruhr University Bochum)
• Tiago Cerqueira (University of Coimbra)
• Jonathan Schmidt
• Aldo H. Romero (West Virginia University)
• Théo Cavignac (rcFEMS, ICAMS, Ruhr University Bochum)
• Pierre-Paul De Breuck (rcFEMS, ICAMS, Ruhr University Bochum)
• Hai-Chen Wang (rcFEMS, ICAMS, Ruhr University Bochum)
• Antoine Loew (rcFEMS, ICAMS, Ruhr University Bochum)
• Giulio Benedini (Software for Chemistry & Materials, Vrije Universiteit Amsterdam)

License

Alexandria is available for use under the terms of the Creative Commons Attribution 4.0 License. Under this license you are free to share and adapt the data, but you must give appropriate credit to Alexandria, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

Citing Alexandria

If you use Alexandria in your work, please cite:

Th. Cavignac, J. Schmidt, P.-P. De Breuck, A. Loew, T. F. T. Cerqueira, H.-C. Wang, A. Bochkarev, Y. Lysogorskiy, A. H. Romero, R. Drautz, S. Botti and M. A. L. Marques, AI-Driven expansion and application of the Alexandria database, J. Phys. Mater. 9, 025014 (2026). doi:10.1088/2515-7639/ae6620

@article{Cavignac2026Alexandria,
  author  = {Cavignac, Th{\'e}o and Schmidt, Jonathan and De Breuck, Pierre-Paul and Loew, Antoine
             and Cerqueira, Tiago F. T. and Wang, Hai-Chen and Bochkarev, Anton
             and Lysogorskiy, Yury and Romero, Aldo H. and Drautz, Ralf and Botti, Silvana
             and Marques, Miguel A. L.},
  title   = {{AI}-Driven expansion and application of the {A}lexandria database},
  journal = {Journal of Physics: Materials},
  year    = {2026},
  volume  = {9},
  number  = {2},
  pages   = {025014},
  doi     = {10.1088/2515-7639/ae6620},
  url     = {https://doi.org/10.1088/2515-7639/ae6620}
}

More references — for the individual sub-databases, computational methods, and generative models — can be found in the Datasets panel.