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Model for magmom_oszicar

  • Description: This is a benchmark to evaluate how accurately an AI model can predict the total magnetic moment (from the OSZICAR output file of VASP) using the JARVIS-DFT (dft_3d) 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 DFT accuracy.


Reference(s): https://www.nature.com/articles/s41524-023-01012-9;https://hackingmaterials.lbl.gov/matminer, https://hackingmaterials.lbl.gov/matminer/, https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.120.145301, https://www.nature.com/articles/s41524-021-00650-1, https://doi.org/10.1103/PhysRevMaterials.2.083801, https://doi.org/10.48550/arXiv.2305.11842, https://www.nature.com/articles/s41524-020-00440-1, https://github.com/aimat-lab/gcnn_keras

Model benchmarks

Model nameDataset MAE Team name Dataset size Date submitted Notes
kgcnn_schnetdft_3d0.7755kgcnn5221009-26-2023CSV, JSON, run.sh, Info
kgcnn_coNGNdft_3d0.2437kgcnn5221005-06-2023CSV, JSON, run.sh, Info
matminer_xgboostdft_3d0.3645UofT5221005-22-2023CSV, JSON, run.sh, Info
alignn_modeldft_3d0.2574ALIGNN5221001-14-2023CSV, JSON, run.sh, Info
kgcnn_megnetdft_3d0.7753kgcnn5221005-06-2023CSV, JSON, run.sh, Info
cfid_chemdft_3d0.5806JARVIS5221001-14-2023CSV, JSON, run.sh, Info
matminer_lgbmdft_3d0.3987Matminer5221001-14-2023CSV, JSON, run.sh, Info
matminer_rfdft_3d0.3595UofT5221005-22-2023CSV, JSON, run.sh, Info
kgcnn_coGNdft_3d0.2502kgcnn5221005-06-2023CSV, JSON, run.sh, Info
cgcnn_modeldft_3d0.3543CGCNN5221001-14-2023CSV, JSON, run.sh, Info
cfiddft_3d0.4748JARVIS5221001-14-2023CSV, JSON, run.sh, Info
kgcnn_dimenetPPdft_3d0.3995kgcnn5221005-06-2023CSV, JSON, run.sh, Info
kgcnn_cgcnndft_3d0.3065kgcnn5221009-26-2023CSV, JSON, run.sh, Info