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Google Colab Notebooks

Ready-to-run Colab notebooks covering installation, property prediction, force-field training, and pretrained-model usage. Click the badge in any row to open the notebook in Colab.

Notebook Open in Colab Description
Regression task (graph-wise prediction) Open In Colab Single-output regression model for exfoliation energies of 2D materials.
ML force-field training from scratch Open In Colab Train an ALIGNN-FF machine-learning force-field for Silicon.
ALIGNN-FF: relaxation, EV curve, phonons, interfaces Open In Colab Using the pretrained ALIGNN-FF for structure relaxation, EV curves, phonons, interface gamma surfaces, and interface separation.
Scaling / timing comparison Open In Colab Analyze scaling/timing of universal MLFFs.
Melt-Quench MD Open In Colab Generate amorphous structures via molecular dynamics.
Miscellaneous training tasks Open In Colab Single-output (formation energy, bandgap), multi-output (phonon/electron DOS), classification (metal vs non-metal), and pretrained-model usage.
Superconductor Tc Open In Colab Train a model for superconductor transition temperature.
Build id_prop.json from VASP runs Open In Colab Compile vasprun.xml files into an id_prop.json for ALIGNN-FF training.