New Dataset Accelerates Direct Air Capture Research
Researchers have released a new open dataset, Open DAC 2025 (ODAC25), containing data on gas adsorption in deformable metal–organic frameworks (MOFs). The dataset is intended to improve the efficiency of direct air capture (DAC) processes, a technology aimed at removing carbon dioxide from the atmosphere.
What is the Open DAC 2025 Dataset?
ODAC25 comprises nearly 60 million density functional theory (DFT) single-point calculations. These calculations cover the adsorption of carbon dioxide (CO2), water (H2O), nitrogen (N2), and oxygen (O2) within approximately 15,000 different MOFs.
Key Features of ODAC25
- The dataset includes functionalized MOFs, high-energy adsorbate placements, and synthetically generated frameworks.
- It aims to increase the versatility of machine learning models used to predict material properties.
- The data improves the accuracy of DFT calculations compared to previous work.
- It incorporates engineering intuition regarding how adsorbate-induced flexibility affects MOFs.
Using the Dataset
The researchers have released state-of-the-art machine-learned interatomic potentials trained on ODAC25. These potentials are used to predict Henry’s coefficient, a measure of gas adsorption strength.
Impact and Future Applications
ODAC25 enables more detailed screening of MOFs for DAC applications than previously possible. This improved resolution allows for the identification of promising materials more efficiently.
Accessing the Dataset
Access to the dataset is currently limited to subscribers through your institution. Details on receiving 12 digital issues and online access are available through the publisher’s website.
Source: Nature. Featured image credit: Nature.
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