Encyclopedia of Crystallographic Prototypes

Tutorials

Software Using AFLOW Prototypes

A number of software programs and databases access the AFLOW prototypes, which are available on GitHub under the Apache License, Version 2.0. We list some of them here. More details can be found in (Anderson, 2026).

  • Jmol is a Java/JavaScript application for 3D visualization of molecular and crystal structures. The Encyclopedia uses JSmol to visualize each structure on its web page. Jmol can also visualize structures from the database by AFLOW prototype label. For example, typing
    load =aflowlib/AB_cF8_225_a_b-001 packed
    into the Jmol console will display the sodium chloride structure.

    Jmol can also be used to explore structures:
    load =aflowlib/62.3 packed
    will display the third entry in space group #62 ($Pnma$), currently the FeB ($B27$) structure.

    Typing
    draw spacegroup all
    provides a 3D visualization of the space group operations in the current crystal, complementing the standard published 2D representations of the operations.
  • NOMAD is a web-based application which allows storage and retrieval of materials data from AFLOW and other databases.
  • OpenKIM is a curated repository of conventional and machine learning interatomic potentials. The potentials are validated using a variety of open-source databases, including AFLOW. OpenKIM test drivers can be created using kim-tools.
  • The OPTIMADE (The Open Databases Integration for Materials Design) API implements a common interface for the retrieval of materials data from online databases.
  • pymatgen is an open source python library that identifies the AFLOW prototype label of a given structure.
  • Robocrystallographer is a python toolkit which provides analysis of semi-local crystal environments using the AFLOW prototype library for framework analysis.
  • simmate is a python-based framework for exploration of materials properties, including information from various databases.
  • WyckoffTransformer is an open-source python library which can predict novel crystal structures and their material properties. It is trained using a variety of sources, including AFLOW.

References

  • N. Anderson, M. J. Mehl, H. Eckert, S. Divilov, S. Thiel and X. Campilongo, A. Calzolari, and S. Curtarolo, The AFLOW Library of Crystallographic Prototypes: Part 5. In preparation. (2026)
  • M. L. Evans, J. Bergsma, A. Merkys, C. W. Andersen, O. B. Andersson, D. Beltrán, E. Blokhin, T. M. B. R. C. Balderas, K. Choudhary, A. D. Díaz, R. D. García, H. Eckert, K. Eimre, M. E. F. Montero, A. M. Krajewski, J. J. Mortensen, J. M. Nápoles-Duarte, J. Pietryga, J. Qi, F. T. Carrillo, A. Vaitkus, J. Yu, A. C. Zettel, P. B. de Castro, J. Carlsson, T. F. T. Cerqueira, S. Divilov, H. Hajiyani, F. Hanke, K. Jose, C. Oses, J. Riebesell, J. Schmidt, D. Winston, C. Xie, X. Yang, S. Bonella, S. Botti, S. Curtarolo, C. Draxl, L. E. F. Cobas, A. Hospital, Z.-K. Liu, M. A. L. Marques, N. Marzari, A. J. Morris, S. P. Ong, M. Orozco, K. A. Persson, K. S. Thygesen, C. Wolverton, M. Scheidgen, C. Toher, G. J. Conduit, G. Pizzi, S. Gražulis, G.-M. Rignanese, and R. Armiento, Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange, Digital Discovery 3, 1509–1533 (2024). DOI: 10.1039/D4DD00039K. URL: https://www.optimade.org/.
  • A. M. Ganuse and A. Jain, Robocrystallographer: automated crystal structure text descriptions and analysis, MRS Communications 9, 874-881 (2019). DOI: 10.1557/mrc.2019.94. URL: https://github.com/hackingmaterials/robocrystallographer.
  • R. M. Hanson, Jmol – a paradigm shift in crystallographic information, J. Appl. Crystallogr. 43 1250-1260 (2010). DOI: 10.1107/S0021889810030256. URL: https://jmol.sourceforge.net/.
  • Nikita Kazeev, Wei Nong, Ignat Romanov, Ruiming Zhu, Andrey Ustyuzhanin, Shuya Yamazaki, and Kedar Hippalgaonkar, WyckoffTransformer: Generation of Symmetric Crystals, Proceedings of the 42nd International Conference on Machine Learning, Vancouver, Canada. Proceedings of Machine Learning Research 267 (2025). Preprint DOI: 10.48550/arXiv.2503.02407. Publication URL: https://proceedings.mlr.press/v267/kazeev25a.html. Software URL: https://github.com/SymmetryAdvantage/WyckoffTransformer.
  • S. P. Ong, W. D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V. L. Chevrier, K. A. Persson, and G. Ceder, Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis, Comput. Mater. Sci. 68, 314-319 (2013). DOI: 10.1016/j.commatsci.2012.10.028. URL: https://pymatgen.org/.
  • Markus Scheidgen, Lauri Himanen, Alvin Noe Ladines, David Sikter, Mohammad Nakhaee, Ádám Fekete, Theodore Chang, Amir Golparvar, José A. Márquez, Sandor Brockhauser, Sebastian Brückner, Luca M. Ghiringhelli, Felix Dietrich, Daniel Lehmberg, Thea Denell, Andrea Albino, Hampus Näsström, Sherjeel Shabih, Florian Dobener, Markus Kühbach, Rubel Mozumder, Joseph F. Rudzinski, Nathan Daelman, José M. Pizarro, Martin Kuban, Cuauhtemoc Salazar, Pavel Ondračka, Hans-Joachim Bungartz, Claudia Draxl, NOMAD: A distributed web-based platform for managing materials science research data, Journal of Open Source Software 8, 5388 (2023). DOI: 10.21105/joss.05388. URL: https://nomad-lab.eu/.
  • E. B. Tadmor, R. S. Elliot, J. P. Sethna, R. E. Miller, and C. A. Becker, The potential of atomistic simulations and the knowledgebase of interatomic models, JOM 63, 17 (2011). DOI: 10.1007/s11837-011-0102-6. URL: https://openkim.org/.