Cu-C-O - Model and Dataset

This dataset supports our publication Reactant-Induced Dynamic Active Sites on Cu Catalysts During the Water-Gas Shift Reaction .It includes the Cu-C-O model, a machine learning force field (MLFF) developed for simulating CO-induced surface reconstruction of Cu(111), along with the data and files used in the training and simulation processes.

Freezed and compressed Cu-C-O model (graph-compress.pb): The fully trained MLFF model used for production simulations in our study.

Cu-C-O dataset (Dataset.tgz): Contains the complete datasets of various structures appearing in the process of CO-induced Cu (111) surface reconstruction, 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.

DPMD trajectories (DPMD_trajectory.tgz): The full trajectories of Cu(111) surface with/without CO adsorption; evolution of adatoms with/without CO adsorption at different adatom coverages and temperatures.

Input_files (Input_Files.tgz): Examples of input files used for AIMD simulations and SCF calculations with VASP, for training with DeePMD-kit, and for NVT molecular dynamics simulations with LAMMPS.