Data and trained machine learning interatomic potentials supporting publication "Modeling the inner electric double layer using short-range machine learning potentials: A critical assessment"

Scripts, data and figure code for the benchmark of machine-learned interatomic potentials (DP, DP-MP, GRACE, MACE, eSEN-OC25) for Au/electrolyte interfaces. datasets/ training and test sets, DFT-MD reference, MD initial structures01_ ... 06_ one folder per experiment, in order of the manuscriptS1_ ... S3_ experiments in the SItools/ scripts shared by several experiments (DFT, LAMMPS, trajectory analysis) Experiment 03 is split into five tarballs: one folder for each model architecture, and one folder with scripts to regenerate the figures. Every folder has a README describing its contents.