SNet-T25 is an MLIP trained on Titan25 dataset. It was designed for general chemical reactivity, including interfacial reactions, and trained on 1.8M data points across 11 elements (C, H, N, O, Ag, Au, Cu, Pd, Pt, Rh, Ru). The evaluation results are available in GAIA paper, which also provides full details of the model architecture and hyperparameters.

The original SNet-T25 was trained with our in-house framework; we provide a converted checkpoint that can be used directly with SevenNet framework. To enable compatibility, the user only need to apply the following minor modifications:

If using this checkpoint, please cite our work as follows:

@article{gaia2025,
  title={Scalable Reactive Atomistic Dynamics with GAIA},
  author={Song, Suhwan and Kim, Heejae and Jang, Jaehee and Cho, Hyuntae and Kim, Gunhee and Kim, Geonu},
  journal={arXiv preprint arXiv:2509.25798},
  year={2025}
}