Aim

This model is a M3GNet formation energy model for 89 elements of the periodic table. It contains the formation energy for most materials. This is essentially a retrained version of the M3GNet formation energy model originally implemented in tensorflow.

Training dataset

MP-2018.6.1: Materials Project formation energy as of 2018.6.1.

Training set size: : 62315
Validation set size: 3461
Test set size: 3463

Performance metrics

MAE of formation energy in eV/atom.

Training: 0.007 eV/atom
Validation: 0.019 eV/atom
Test: 0.019 eV/atom

References

Chen, C., Ong, S.P. A universal graph deep learning interatomic potential for the periodic table. Nat Comput Sci,
2, 718–728 (2022). https://doi.org/10.1038/s43588-022-00349-3.

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