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Model for TinNet Oxygen dataset

  • Description: This is a benchmark to evaluate how accurately an AI model can predict the energy of adsorption of O using the TinNet dataset. The dataset contains different types of heterogeneous catalysts. Here we use mean absolute error (MAE) to compare models with respect to DFT accuracy. External links: https://www.nature.com/articles/s41467-021-25639-8


Reference(s): https://www.nature.com/articles/s41524-021-00650-1, https://doi.org/10.1038/s41467-021-25639-8, https://pubs.rsc.org/en/content/articlehtml/2023/dd/d2dd00096b

Model benchmarks

Model nameDataset MAE Team name Dataset size Date submitted Notes
MATGL_pretrainedtinnet_O4.9459ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-tinnet_N-test-mae.csv.ziptinnet_O1.1438ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-AGRA_O-test-mae.csv.ziptinnet_O5.458ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-AGRA_OH-test-mae.csv.ziptinnet_O5.2012ALIGNN74501-14-2023CSV, JSON, run.sh, Info
alignn_modeltinnet_O0.3694ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-AGRA_CO-test-mae.csv.ziptinnet_O2.4389ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-AGRA_COOH-test-mae.csv.ziptinnet_O3.911ALIGNN74501-14-2023CSV, JSON, run.sh, Info
alignnff_pretrained_wt0.1tinnet_O1.885JARVIS74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-tinnet_O-test-mae.csv.ziptinnet_O0.2657ALIGNN74501-14-2023CSV, JSON, run.sh, Info
CHGNet_pretrainedtinnet_O6.0983ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-tinnet_OH-test-mae.csv.ziptinnet_O1.7819ALIGNN74501-14-2023CSV, JSON, run.sh, Info
Out-AI-SinglePropertyPrediction-ead-AGRA_CHO-test-mae.csv.ziptinnet_O2.0323ALIGNN74501-14-2023CSV, JSON, run.sh, Info
MACE_pretrainedtinnet_O4.7917ALIGNN74501-14-2023CSV, JSON, run.sh, Info