Dataset for: Vacancy formation energy as a descriptor of the exfoliability of MAX phases to MXenes

This repository contains the data that accompany the paper "Vacancy formation energy as a descriptor of the exfoliability of MAX Phases to MXenes" ( https://doi.org/10.1038/s41699-025-00581-1 ) Contents Archive / file Description ideal.zip DFT data for ideal structures. • ideal_mxene.db – MXene structures • ideal_MAX.db – MAX-phase structures vacancy.zip DFT data for vacancy (defective) structures. • M_vacancy_mxene.db (MXenes)• X_vacancy_mxene.db (MXenes)• A_vacancy_MAX.db (MAX phases) NIST_ATLAS_data.zip CSV files with combined chemical-potential data from the NIST and ATLAS databases, pre-parsed for direct use in Python. muF.csv pH-dependent chemical potential of F, generated from F⁻ and HF₂⁻ (see the paper’s Supplementary Information). elements.db DFT reference data for elemental phases (required to compute formation enthalpies). script.zip Two self-contained Jupyter notebooks—vacancy_mxene.ipynb and vacancy_max.ipynb—plus the custom Python libraries they depend on. Note All DFT data are stored in ASE SQLite databases (*.db). They can be opened in Python (import ase.db) or via the command-line tool ase db <filename>.db on Linux/macOS. For details, consult the ASE database documentation. Quick-start guide Create a working directory and place every item from this repository into it. Unzip all .zip archives in the same folder (keep the unzipped and standalone files together). Open one of the notebooks inside script/ in Jupyter or VS Code. The first cell lists the Python packages you may need to install (typically via pip). Run the notebook from top to bottom. The second last cell displays a plot of vacancy-formation energies. The final cell writes the results to disk as a dataframe.