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Model for heat capacity

  • Description: This is a benchmark to evaluate how accurately an AI model can predict the heat capacity 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://www.nature.com/articles/s41524-020-00440-1, https://doi.org/10.48550/arXiv.2305.11842, https://github.com/aimat-lab/gcnn_keras, https://www.nature.com/articles/s41524-021-00650-1

Model benchmarks

Model name Dataset MAE Team name Dataset size Date submitted Notes
kgcnn_coGNdft_3d6.1125kgcnn1205405-06-2023CSV, JSON, run.sh, Info
alignn_modeldft_3d9.6064ALIGNN1205401-14-2023CSV, JSON, run.sh, Info
matminer_xgboostdft_3d5.47UofT1205405-22-2023CSV, JSON, run.sh, Info
kgcnn_cgcnndft_3d12.9364kgcnn1205409-26-2023CSV, JSON, run.sh, Info
kgcnn_schnetdft_3d17.7707kgcnn1205409-26-2023CSV, JSON, run.sh, Info
kgcnn_coNGNdft_3d7.8127kgcnn1205405-06-2023CSV, JSON, run.sh, Info
kgcnn_megnetdft_3d6.0443kgcnn1205405-06-2023CSV, JSON, run.sh, Info
matminer_rfdft_3d5.2757UofT1205405-22-2023CSV, JSON, run.sh, Info
kgcnn_dimenetPPdft_3d23.3618kgcnn1205405-06-2023CSV, JSON, run.sh, Info