Au-Ce-C-O - Model and Dataset

This dataset supports our publication Dynamic Phase Transitions Dictate the Size Effect and Activity of Supported Gold Catalysts. It includes the Au-Ce-C-O model, a machine learning force field (MLFF) developed for simulating supported gold catalysts on Ceria surface in CO and O₂ atmosphere, along with the data and files used in the training and simulation processes.

• Freezed and compressed Au-Ce-C-O model (graph.pb and graph-compress.pb): The fully trained MLFF model used for production simulations in our study.
• Au-Ce-C-O dataset (dataset.tgz): Contains the training datasets for Au/CeO₂ system with CO and O₂ , in DeePMD-kit format (dataset.tgz). Each image is labeled with coordinations (coord.npy) in Å, total energies (energy.npy) in eV, force (force.npy) in eV/Å, and cell parameters (box.npy) in Å.
• DeePMD-kit files (input-auceco.json): Input file example utilized for training using DeePMD-kit.
• LAMMPS files (in.rigid): Input file example utilized for NVT Molecular dynamics simulation.
• VASP files (VASP-au10ceo2-3co-aimd.tgz): Input file example utilized for AIMD simulation.
• DPMD trajectaries (traj.tgz): The full trajectories of the Au/CeO₂ system, with and without CO exposure, with temperature increasing in increments of 25 K.