Name: Open Direct Air Capture ODAC2025 Train Filtered
License: CC-BY-4.0

Dataset

Open_Direct_Air_Capture_ODAC2025_Train_Filtered

Download Original Data Files 551.2 GB

Download Dataset Parquet Files 197.6 GB

Download Dataset XYZ Files 281.2 GB

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Species content of dataset

Name :

Open_Direct_Air_Capture_ODAC2025_Train_Filtered

Authors :

Anuroop Sriram, Logan M. Brabson, Xiaohan Yu, Sihoon Choi, Kareem Abdelmaqsoud, Elias Moubarak, Pim de Haan, Sindy Löwe, Johann Brehmer, John R. Kitchin, Max Welling, C. Lawrence Zitnick, Zachary Ulissi, Andrew J. Medford, David S. Sholl

Description :

This is the filtered training split of ODAC25. ODAC25 is a large-scale DFT dataset intended to advance the computational screening of Metal-Organic Framework (MOF) sorbents for direct air capture (DAC) of atmospheric CO2 from humid air. Spanning ~15,000 MOFs, including experimental, defective, synthetic, and amine-functionalized frameworks, the dataset comprises nearly 60 million single-point calculations covering four adsorbates: CO2, H2O, N2, and O2. All calculations were performed with VASP 6.3 using the PBE functional augmented with D3 dispersion corrections (Becke-Johnson damping). Spin-polarized calculations (ISPIN=2) were used throughout. Relative to ODAC23, ODAC25 adds two new adsorbates (N2 and O2), functionalized MOF variants, improved k-point convergence, and re-relaxations of bare MOF cells. Three configuration sets are provided: mof_plus_adsorbate (full DFT relaxations of adsorbate-loaded MOFs), mof (re-relaxations of empty frameworks), and gcmc (DFT single points derived from Grand Canonical Monte Carlo simulations). Structures identified as problematic by Jin et al. (2025) have been excluded (see https://zenodo.org/records/14802658).

DOI :

https://doi.org/None https://commons.datacite.org/doi.org/None

Cite As :

Sriram, A., Brabson, L. M., Yu, X., Choi, S., Abdelmaqsoud, K., Moubarak, E., Haan, P., Löwe, S., Brehmer, J., Kitchin, J. R., Welling, M., Zitnick, C. L., Ulissi, Z., Medford, A. J., and Sholl, D. S. "Open Direct Air Capture ODAC2025 Train Filtered." ColabFit, 2025. https://doi.org/None.

ColabFit ID :

DS_qx9u3v4xzt1f_0

Extended ID :

Open_Direct_Air_Capture_ODAC2025_Train_Filtered__Sriram-Brabson-Yu-Choi-Abdelmaqsoud-Moubarak-Haan-Lowe-Brehmer-Kitchin-Welling-Zitnick-Ulissi-Medford-Sholl__DS_qx9u3v4xzt1f_0

Date Added :

2026-04-24

License :

CC-BY-4.0

Downloads :

454

Num. Configurations :

36,058,136

Num. Atoms :

8,523,144,395

Calculated Property Types :

adsorption_energy atomic_forces energy

Elements :

Ag (0.03%) Al (0.11%) Au (0.02%) B (0.02%) Ba (0.01%) Bi (0.0%) Br (0.03%) C (39.78%) Ca (0.04%) Cd (0.47%) Ce (0.01%) Cl (0.09%) Co (0.34%) Cr (0.01%) Cu (0.65%) Dy (0.01%) Er (0.0%) Eu (0.01%) F (0.14%) Fe (0.44%) Ga (0.01%) Gd (0.03%) H (31.32%) Hf (0.0%) Hg (0.0%) Ho (0.0%) I (0.1%) In (0.0%) La (0.05%) Li (0.04%) Lu (0.01%) Mg (0.31%) Mn (0.22%) Mo (0.0%) N (6.74%) Na (0.02%) Nb (0.0%) Nd (0.01%) Ni (0.41%) Np (0.0%) O (16.54%) P (0.16%) Pd (0.0%) Pr (0.0%) Pt (0.03%) Re (0.0%) Ru (0.0%) S (0.23%) Sc (0.0%) Se (0.0%) Si (0.02%) Sm (0.01%) Sr (0.02%) Tb (0.01%) Ti (0.0%) Tm (0.0%) U (0.0%) V (0.03%) W (0.01%) Y (0.03%) Zn (1.42%) Zr (0.02%)

Methods :

DFT-PBE+D3

Software :

VASP 6.3

Publication Link :

https://doi.org/10.48550/arXiv.2508.03162

Data Source Link :

https://huggingface.co/facebook/ODAC25

Other Links :

https://open-dac.github.io/

Spec File :

colabfitspec.json

Configuration Sets by Name :

Configuration Sets by ID :

Name: Open_Direct_Air_Capture_ODAC2025_Train_Filtered Extended ID: Open_Direct_Air_Capture_ODAC2025_Train_Filtered__Sriram-Brabson-Yu-Choi-Abdelmaqsoud-Moubarak-Haan-Lowe-Brehmer-Kitchin-Welling-Zitnick-Ulissi-Medford-Sholl__DS_qx9u3v4xzt1f_0 Description: This is the filtered training split of ODAC25. ODAC25 is a large-scale DFT dataset intended to advance the computational screening of Metal-Organic Framework (MOF) sorbents for direct air capture (DAC) of atmospheric CO2 from humid air. Spanning ~15,000 MOFs, including experimental, defective, synthetic, and amine-functionalized frameworks, the dataset comprises nearly 60 million single-point calculations covering four adsorbates: CO2, H2O, N2, and O2. All calculations were performed with VASP 6.3 using the PBE functional augmented with D3 dispersion corrections (Becke-Johnson damping). Spin-polarized calculations (ISPIN=2) were used throughout. Relative to ODAC23, ODAC25 adds two new adsorbates (N2 and O2), functionalized MOF variants, improved k-point convergence, and re-relaxations of bare MOF cells. Three configuration sets are provided: mof_plus_adsorbate (full DFT relaxations of adsorbate-loaded MOFs), mof (re-relaxations of empty frameworks), and gcmc (DFT single points derived from Grand Canonical Monte Carlo simulations). Structures identified as problematic by Jin et al. (2025) have been excluded (see https://zenodo.org/records/14802658). Authors: Anuroop Sriram Logan M. Brabson Xiaohan Yu Sihoon Choi Kareem Abdelmaqsoud Elias Moubarak Pim de Haan Sindy Löwe Johann Brehmer John R. Kitchin Max Welling C. Lawrence Zitnick Zachary Ulissi Andrew J. Medford David S. Sholl DOI: None Calculated Property Types: adsorption_energy atomic_forces energy Elements: Ag (0.03%) Al (0.11%) Au (0.02%) B (0.02%) Ba (0.01%) Bi (0.0%) Br (0.03%) C (39.78%) Ca (0.04%) Cd (0.47%) Ce (0.01%) Cl (0.09%) Co (0.34%) Cr (0.01%) Cu (0.65%) Dy (0.01%) Er (0.0%) Eu (0.01%) F (0.14%) Fe (0.44%) Ga (0.01%) Gd (0.03%) H (31.32%) Hf (0.0%) Hg (0.0%) Ho (0.0%) I (0.1%) In (0.0%) La (0.05%) Li (0.04%) Lu (0.01%) Mg (0.31%) Mn (0.22%) Mo (0.0%) N (6.74%) Na (0.02%) Nb (0.0%) Nd (0.01%) Ni (0.41%) Np (0.0%) O (16.54%) P (0.16%) Pd (0.0%) Pr (0.0%) Pt (0.03%) Re (0.0%) Ru (0.0%) S (0.23%) Sc (0.0%) Se (0.0%) Si (0.02%) Sm (0.01%) Sr (0.02%) Tb (0.01%) Ti (0.0%) Tm (0.0%) U (0.0%) V (0.03%) W (0.01%) Y (0.03%) Zn (1.42%) Zr (0.02%) Methods: DFT-PBE+D3 Software: VASP 6.3 Number of Configurations: 36,058,136 Number of Atoms: 8,523,144,395 Publication Link: https://doi.org/10.48550/arXiv.2508.03162 Data Source Link: https://huggingface.co/facebook/ODAC25 Other Links: https://open-dac.github.io/

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