c-bone/alex_mp_20

Dataset Card for Alex-MP-20

Alex-MP-20 crystal structures without property labels.

Dataset Details

• Curated by: Bone et al. (University College London)
• Source data: Alex-MP-20 (MatterGen, from Alexandria and MP-20)
• Used to train: c-bone/CrystaLLM-pi_ft_alex_mp_20-text, c-bone/CrystaLLM-pi_alex_mp_20_base
• Paper: Discovery and recovery of crystalline materials with property-conditioned transformers (arXiv:2511.21299)
• Repository: GitHub: CrystaLLM-pi
• License: CC BY 4.0, following the source data

Dataset Structure

Column	Description
material_id	Material identifier in the source database
formula_reduced	Reduced chemical formula
CIF	Crystal structure in CrystaLLM-π augmented CIF format
n_tokens	Number of CrystaLLM-π tokens in the CIF

Split	Rows
train	607,675
validation	67,520

Dataset Creation

The structures come from the Alex-MP-20 training data released with MatterGen, with at most 20 atoms per unit cell and an energy above the hull of at most 0.1 eV/atom. The dataset uses a random 90:10 train:validation split, with CIFs longer than 1024 tokens removed.

Citation

@misc{bone2025discoveryrecoverycrystallinematerials,
      title={Discovery and recovery of crystalline materials with property-conditioned transformers},
      author={Cyprien Bone and Matthew Walker and Bradley A. A. Martin and Kuangdai Leng and Luis M. Antunes and Ricardo Grau-Crespo and Amil Aligayev and Javier Dominguez and Keith T. Butler},
      year={2025},
      eprint={2511.21299},
      archivePrefix={arXiv},
      primaryClass={cond-mat.mtrl-sci},
      url={https://arxiv.org/abs/2511.21299},
}

@article{zeni2025mattergen,
      title={A generative model for inorganic materials design},
      author={Zeni, Claudio and Pinsler, Robert and Z{\"u}gner, Daniel and Fowler, Andrew and Horton, Matthew and Fu, Xiang and Wang, Zilong and Shysheya, Aliaksandra and Crabb{\'e}, Jonathan and Ueda, Shoko and Sordillo, Roberto and Sun, Lixin and Smith, Jake and Nguyen, Bichlien and Schulz, Hannes and Lewis, Sarah and Huang, Chin-Wei and Lu, Ziheng and Zhou, Yichi and Yang, Han and Hao, Hongxia and Li, Jielan and Yang, Chunlei and Li, Wenjie and Tomioka, Ryota and Xie, Tian},
      journal={Nature},
      volume={639},
      pages={624--632},
      year={2025},
      doi={10.1038/s41586-025-08628-5},
}

@misc{schmidt2022alexandria,
      title={Large-scale machine-learning-assisted exploration of the whole materials space},
      author={Schmidt, Jonathan and Hoffmann, Noah and Wang, Hai-Chen and Borlido, Pedro and Carri{\c{c}}o, Pedro J. M. A. and Cerqueira, Tiago F. T. and Botti, Silvana and Marques, Miguel A. L.},
      publisher={Materials Cloud},
      year={2022},
      doi={10.24435/materialscloud:m7-50},
}

@article{jain2013materialsproject,
      title={Commentary: The Materials Project: A materials genome approach to accelerating materials innovation},
      author={Jain, Anubhav and Ong, Shyue Ping and Hautier, Geoffroy and Chen, Wei and Richards, William Davidson and Dacek, Stephen and Cholia, Shreyas and Gunter, Dan and Skinner, David and Ceder, Gerbrand and Persson, Kristin A.},
      journal={APL Materials},
      volume={1},
      number={1},
      pages={011002},
      year={2013},
      doi={10.1063/1.4812323},
}