Model for hmof_co2¶
- Description: This is a benchmark to evaluate how accurately an AI model can predict the CO2 gas uptake of metal-organic frameworks using the hypothetical MOF (hMOF) dataset. The dataset contains different types of chemical formula and atomic structures. Here we use mean absolute error (MAE) to compare models with respect to GCMC accuracy.
Reference(s): https://github.com/atomgptlab/jarvis_leaderboard, https://doi.org/10.1038/nchem.1192, https://github.com/atomgptlab/alignn
Model benchmarks
| Model name | Dataset | MAE | Team name | Dataset size | Date submitted | Notes |
|---|---|---|---|---|---|---|
| baseline_mean | hmof | 2.2327 | AtomGPTLab | 137652 | 07-31-2026 | CSV, JSON, run.sh, Info |
| alignn2_knn | hmof | 0.4687 | AtomGPTLab | 137652 | 07-30-2026 | CSV, JSON, run.sh, Info |