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Model for slme

  • Description: This is a benchmark to evaluate how accurately an AI model can predict the Spectroscopic Limited Maximum Efficiency (SLME) 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_3d5.3222kgcnn906209-26-2023CSV, JSON, run.sh, Info
kgcnn_coNGNdft_3d4.4428kgcnn906205-06-2023CSV, JSON, run.sh, Info
matminer_xgboostdft_3d4.9255UofT906205-22-2023CSV, JSON, run.sh, Info
alignn_modeldft_3d4.5207ALIGNN906201-14-2023CSV, JSON, run.sh, Info
kgcnn_megnetdft_3d5.0614kgcnn906205-06-2023CSV, JSON, run.sh, Info
cfid_chemdft_3d6.5321JARVIS906201-14-2023CSV, JSON, run.sh, Info
matminer_lgbmdft_3d5.4242Matminer906201-14-2023CSV, JSON, run.sh, Info
matminer_rfdft_3d5.1235UofT906205-22-2023CSV, JSON, run.sh, Info
kgcnn_coGNdft_3d4.4507kgcnn906205-06-2023CSV, JSON, run.sh, Info
cgcnn_modeldft_3d5.6603CGCNN906201-14-2023CSV, JSON, run.sh, Info
cfiddft_3d6.2607JARVIS906201-14-2023CSV, JSON, run.sh, Info
kgcnn_dimenetPPdft_3d5.6403kgcnn906205-06-2023CSV, JSON, run.sh, Info
kgcnn_cgcnndft_3d5.0139kgcnn906209-26-2023CSV, JSON, run.sh, Info