This model is a M3GNet potential for 4 elements including H, C, N, O. It has broad applications in the
dynamic simulations of organic molecules.
Training dataset
ANI-1x-Subset: 300K MD simulations and Materials Project ground state calculations.
Training set size: 991735
Validation set size: 248355
Test set size: 248355
Performance metrics
Training and validation errors
MAEs of energies, forces and stresses, respectively
Training: 4.565 meV/atom, 92 meV/A
Validation: 4.592 meV/atom, 93 meV/A
Test: 3.746 meV/atom, 85 meV/A
References
Ko, T.W., Deng, B., Nassar, M. et al. Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. npj Computation Materials 11, 253 (2025).
