MAD Massive Atomic Diversity -- ColabFit
Collection
Datasets from Massive Atomic Diversity in ColabFit format • 5 items • Updated
property_id string | property_hash string | last_modified timestamp[us] | dataset_id string | multiplicity int32 | software string | method string | energy float64 | atomic_forces list | cauchy_stress list | cauchy_stress_volume_normalized bool | electronic_band_gap float64 | electronic_band_gap_type string | formation_energy float64 | adsorption_energy float64 | atomization_energy float64 | max_force_norm float64 | mean_force_norm float64 | energy_above_hull float64 | configuration_id string | configuration_hash string | structure_hash string | cell list | positions list | pbc list | chemical_formula_hill string | chemical_formula_reduced string | chemical_formula_anonymous string | elements list | elements_ratios list | atomic_numbers list | nsites int32 | nelements int32 | nperiodic_dimensions int32 | dimension_types list | names list | labels list | property_metadata_path string | configuration_metadata_path string | hash string | configuration_metadata string | property_metadata string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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[
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[
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true,
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[
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true
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[
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[
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End of preview. Expand in Data Studio
Cite this dataset
Mazitov, A., Chorna, S., Fraux, G., Bercx, M., Pizzi, G., De, S., and Ceriotti, M. Massive Atomic Diversity MAD test. ColabFit, 2025. https://doi.org/10.60732/e55c4ce1
Cite this dataset
Mazitov, A., Chorna, S., Fraux, G., Bercx, M., Pizzi, G., De, S., and Ceriotti, M. Massive Atomic Diversity MAD test. ColabFit, 2025. https://doi.org/10.60732/e55c4ce1This dataset has been curated and formatted for the ColabFit Exchange
This dataset is also available on the ColabFit Exchange:
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Dataset Name
Massive Atomic Diversity MAD test
Description
The test split of the MAD (Massive Atomic Diversity) dataset. From the creators: Starting from relatively small sets of stable structures, the dataset is built to contain “massive atomic diversity” (MAD) by aggressively distorting these configurations, with near-complete disregard for the stability of the resulting configurations. The electronic structure details, on the other hand, are chosen to maximize consistency rather than to obtain the most accurate prediction fora given structure, or to minimize computational effort. The MAD dataset we present here, despite containing fewer than 100k structures, has already been shown to enable training universal interatomic potentials that are competitive with models trained on traditional datasets with two to three orders of magnitude more structures.
Dataset authors
Arslan Mazitov, Sofiia Chorna, Guillaume Fraux, Marnik Bercx, Giovanni Pizzi, Sandip De, Michele Ceriotti
Publication
https://doi.org/10.48550/arXiv.2506.19674
Original data link
https://doi.org/10.24435/materialscloud:vd-e8
License
CC-BY-4.0
Number of unique molecular configurations
9546
Number of atoms
259376
Elements included
Ag, Al, Ar, As, Au, B, Ba, Be, Bi, Br, C, Ca, Cd, Ce, Cl, Co, Cr, Cs, Cu, Dy, Er, Eu, F, Fe, Ga, Gd, Ge, H, He, Hf, Hg, Ho, I, In, Ir, K, Kr, La, Li, Lu, Mg, Mn, Mo, N, Na, Nb, Nd, Ne, Ni, O, Os, P, Pb, Pd, Pm, Po, Pr, Pt, Rb, Re, Rh, Rn, Ru, S, Sb, Sc, Se, Si, Sm, Sn, Sr, Ta, Tb, Tc, Te, Ti, Tl, Tm, V, W, Xe, Y, Yb, Zn, Zr
Properties included
energy, atomic forces, cauchy stress
Usage
ds.parquet: Aggregated dataset information.co/directory: Configuration rows each include a structure, calculated properties, and metadata.cs/directory : Configuration sets are subsets of configurations grouped by some common characteristic. Ifcs/does not exist, no configurations sets have been defined for this dataset.cs_co_map/directory : The mapping of configurations to configuration sets (if defined).
ColabFit Exchange documentation includes descriptions of content and example code for parsing parquet files:
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Size of downloaded dataset files:
13 MB
Size of the auto-converted Parquet files:
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Number of rows:
9,547