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PO_532b3ae308814547eedf84a2f | 532b3ae308814547eedf84a2f0c7bdc583083afc016749124f2bb2e925ff8a3f1c8814f2f8db464490eaeb4a40bff924a6a16a7649d46c4375cb5f83996f8d98 | 2026-05-21T20:43:43 | DS_7q71mf99le0c_0 | 1 | FHI-aims v250806 | DFT-r2SCAN | -1,281,619.514866 | [
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true
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83,
83
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PO_6faefe7896e378d7aa0fb788f | 6faefe7896e378d7aa0fb788fa4d11084b5efa1447ed6f6db7d29d380000e07e32ebaac31c869d615009d9daeaa412d597add0b71f97fde63ffe89fc1571b31b | 2026-05-21T20:43:43 | DS_7q71mf99le0c_0 | 1 | FHI-aims v250806 | DFT-r2SCAN | -1,251,349.347084 | [
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78
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[
0... | [
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true
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... | [
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true
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true
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8,
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PO_1bdbba79722467c57f02b92c7 | 1bdbba79722467c57f02b92c7088181326728ee8bc67adca23169fdac6c9d1ed8f5861b881498d4b672ac58e5fbef566df55cb35e0be0c13870ada03a7e99d80 | 2026-05-21T20:43:43 | DS_7q71mf99le0c_0 | 1 | FHI-aims v250806 | DFT-r2SCAN | -432,286.017451 | [
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0.... | [
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true,
true
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... | [
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true,
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0.5,
0.5
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27,
27,
52,
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3.89... | [
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true,
true
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PO_910f459c778e3348b193c8614 | 910f459c778e3348b193c861495256547da4cbd36d5bedbfa1e4ed3b153cadae51178d15d0f1bbb0d9c1a1f6f5ffc8eb264be8fbc99922b414afa2faaed4793d | 2026-05-21T20:43:43 | DS_7q71mf99le0c_0 | 1 | FHI-aims v250806 | DFT-r2SCAN | -1,449,448.187432 | [
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... | [
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true
] | Co4In8 | CoIn2 | A2B | [
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0.3333333333333333,
0.6666666666666666
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49,
49,
49,
49,
49,
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49,
27,
27,
27,
27
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PO_1e06cf3111f6d0c8386f4da61 | 1e06cf3111f6d0c8386f4da614862e107f08966296b43bbe9b33774476d9332ba20c19d80c9dd12327e5600687f7350fc32546d89f720cefe88f6235fc7ae9bd | 2026-05-21T20:43:43 | DS_7q71mf99le0c_0 | 1 | FHI-aims v250806 | DFT-r2SCAN | -423,903.804312 | [
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0.0032689
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0.5
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28,
50,
50
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Cite this dataset
Malosso, C., Bigi, F., Pegolo, P., Abbott, J. W., Loche, P., Rossi, M., Ceriotti, M., and Mazitov, A. Massive Atomic Diversity MAD-1.5 r2SCAN Test. ColabFit, 2026. https://doi.org/None
Cite this dataset
Malosso, C., Bigi, F., Pegolo, P., Abbott, J. W., Loche, P., Rossi, M., Ceriotti, M., and Mazitov, A. Massive Atomic Diversity MAD-1.5 r2SCAN Test. ColabFit, 2026. https://doi.org/NoneThis 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-1.5 r2SCAN Test
Description
Test split of the MAD-1.5 (Massive Atomic Diversity version 1.5) dataset, a highly curated collection designed for training broadly applicable atomistic machine-learning models across the full periodic table. MAD-1.5 extends the original MAD dataset with targeted enrichment strategies covering 102 chemical elements (all isotopes with half-life above one day). All 216,803 structures are computed with a single standardized all-electron DFT workflow using the r2SCAN meta-GGA functional in FHI-aims (version 250806), with tight basis sets, 8 Angstrom^-1 k-point density, Gaussian smearing of 0.05 eV, and SCF convergence thresholds of 1e-6 eV (energy), 1e-4 eV/Angstrom (forces), and 1e-5 e*a0^-3 (electron density). The dataset spans molecules (monomers, dimers, trimers, molecular crystals), bulk crystals, surfaces, nanoclusters, and low-dimensional structures organized into 14 subsets. Quality is ensured by two-step outlier removal: heuristic filtering of structures with forces >100 eV/Angstrom, followed by LLPR uncertainty-based filtering. The test split (~10% of cleaned data, excluding monomers, dimers, and trimers which are fixed in the training split) uses a stratified split method consistent with the training and validation splits. Subset-resolved MAE for PET-MAD-1.5-S on this test set is 11.09 meV/atom (energy) and 36.81 meV/Angstrom (forces). A companion PBE-functional dataset (Massive_Atomic_Diversity_MAD-1.5_PBE) was used during model training with separate prediction heads.
Dataset authors
Cesare Malosso, Filippo Bigi, Paolo Pegolo, Joseph W. Abbott, Philip Loche, Mariana Rossi, Michele Ceriotti, Arslan Mazitov
Publication
https://doi.org/10.48550/arXiv.2603.02089
Original data link
https://doi.org/10.24435/materialscloud:jc-9f
License
CC-BY-4.0
Number of unique molecular configurations
18314
Number of atoms
321704
Elements included
Ac, Ag, Al, Am, Ar, As, At, Au, B, Ba, Be, Bi, Bk, Br, C, Ca, Cd, Ce, Cf, Cl, Cm, Co, Cr, Cs, Cu, Dy, Er, Es, Eu, F, Fe, Fm, Fr, Ga, Gd, Ge, H, He, Hf, Hg, Ho, I, In, Ir, K, Kr, La, Li, Lu, Md, Mg, Mn, Mo, N, Na, Nb, Nd, Ne, Ni, No, Np, O, Os, P, Pa, Pb, Pd, Pm, Po, Pr, Pt, Pu, Ra, Rb, Re, Rh, Rn, Ru, S, Sb, Sc, Se, Si, Sm, Sn, Sr, Ta, Tb, Tc, Te, Th, Ti, Tl, Tm, U, V, W, Xe, Y, Yb, Zn, Zr
Properties included
energy, atomization 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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