Computational Supporting Dataset: Atomic Insights into Aluminium-Ion Insertion in Defective Hydroxyfluorinated Anatase for Batteries

Data collection method:

The VASP output data were parsed and collated using the `vasp_summary` script contained in the `vasppy` Python package. This dataset was then used for subsequent analysis using a combination of Python scripts and Jupyter notebooks. The data parsing and analysis steps are described as a Snakemake workflow.

Technical details and requirements:

All DFT calculations were performed using VASP 5.4.4 (vasp.5.4.4.18Apr17-6-g9f103f2a35). To rerun the DFT calculations in this dataset the appropriate pseudopotentials are needed. These are not included in this dataset due to the VASP license conditions. Each calculation directory contains a corresponding `POTCAR.spec` file that specifies the pseudopotentials used. These calculations use pseudopotentials from the VASP 5.4 set. The data analysis workflow has the following Python package requirements: - vasppy>=0.6.1.0; - snakemake; - numpy; - version_information; - matplotlib; - pymatgen; - tqdm; - jupyter. From the top level directory, the analysis workflow can be run from a *nix command prompt with the following commands: ``` pip install -r requirements.txt snakemake --cores all clean snakemake --cores all ``` Full details are given in the top-level `README.md` file.