Identifying useful sorbent materials for direct air capture (DAC) from humid air remains a challenge. We present the Open DAC 2025 (ODAC25) dataset, a significant expansion and improvement upon ODAC23 (Sriram et al., ACS Central Science, 10 (2024) 923), comprising nearly 60 million DFT single-point calculations for CO2, H2O, N2, and O2 adsorption in 15,000 MOFs. ODAC25 introduces chemical and configurational diversity through functionalized MOFs, high-energy GCMC-derived placements, and synthetically generated frameworks. ODAC25 also significantly improves upon the accuracy of DFT calculations and the treatment of flexible MOFs in ODAC23. Along with the dataset, we release new state-of-the-art machine-learned interatomic potentials trained on ODAC25 and evaluate them on adsorption energy and Henry's law coefficient predictions.
@article{arxiv.2508.03162,
title = {The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture},
author = {Anuroop Sriram and Logan M. Brabson and Xiaohan Yu and Sihoon Choi and Kareem Abdelmaqsoud and Elias Moubarak and Pim de Haan and Sindy Löwe and Johann Brehmer and John R. Kitchin and Max Welling and C. Lawrence Zitnick and Zachary Ulissi and Andrew J. Medford and David S. Sholl},
journal= {arXiv preprint arXiv:2508.03162},
year = {2025}
}