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Model for magnetic moment of 2D materials using chemical formula

  • Description: This is a benchmark to evaluate how accurately an AI model can predict the total magnetic moment of a 2D magnet from chemical formula using the DFT dataset: https://archive.materialscloud.org/record/2019.0020/v1. Here we use mean absolute error (MAE) to compare models with respect to DFT accuracy. External links: https://www.nature.com/articles/s41598-020-72811-z


Reference(s): https://www.nature.com/articles/s41524-023-01012-9;https://hackingmaterials.lbl.gov/matminer, https://hackingmaterials.lbl.gov/matminer/, https://dl.acm.org/doi/abs/10.1145/3292500.3330703, https://doi.org/10.1038/s41598-020-72811-z, https://epubs.siam.org/doi/abs/10.1137/1.9781611977172.39, https://doi.org/10.1103/PhysRevMaterials.2.083801, https://www.nature.com/articles/s41598-018-35934-y

Model benchmarks

Model name Dataset MAE Team name Dataset size Date submitted Notes
ElemNet1mag2d_chem0.4605NorthWestern_University22601-14-2023CSV, JSON, run.sh, Info
matminer_xgboostmag2d_chem0.3472UofT22605-22-2023CSV, JSON, run.sh, Info
element_fraction_descmag2d_chem1.0267JARVIS22601-14-2023CSV, JSON, run.sh, Info
BNetmag2d_chem0.3203NorthWestern_University22601-14-2023CSV, JSON, run.sh, Info
ElemNet2_SCmag2d_chem0.4477NorthWestern_University22601-14-2023CSV, JSON, run.sh, Info
cfid_chemmag2d_chem0.4236JARVIS22601-14-2023CSV, JSON, run.sh, Info
matminer_lgbmmag2d_chem0.4261Matminer22601-14-2023CSV, JSON, run.sh, Info
matminer_rfmag2d_chem0.3455UofT22605-22-2023CSV, JSON, run.sh, Info
BRNetmag2d_chem0.3304NorthWestern_University22601-14-2023CSV, JSON, run.sh, Info
IRNet_EFmag2d_chem0.3774NorthWestern_University22601-14-2023CSV, JSON, run.sh, Info
ElemNet2_TLmag2d_chem0.2997NorthWestern_University22601-14-2023CSV, JSON, run.sh, Info