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

This dataset contains DFT calculation inputs and outputs and analysis codes for calculations of Al intercalation into (OH,F)-substituted anatase TiO2. More details on these calculations and analysis are given in the paper by Legein et al., "Atomic Insights into Aluminium-Ion Insertion in Defective Anatase for Batteries".

Keywords:
Polyvalent Ion Batteries, Solid-State NMR
Subjects:

Cite this dataset as:
Morgan, B., 2020. Computational Supporting Dataset: Atomic Insights into Aluminium-Ion Insertion in Defective Hydroxyfluorinated Anatase for Batteries. Bath: University of Bath Research Data Archive. Available from: https://doi.org/10.15125/BATH-00815.

Export

[QR code for this page]

Data

Al_F_OH_TiO2.zip
application/zip (1GB)
Creative Commons: Attribution 4.0

DFT calculation inputs and output, and analysis code to support the computational results in "Atomic Insights into Aluminium-Ion Insertion in Defective Anatase for Batteries" by Legein et al. DOI: 10.1002/anie.202007983.

Creators

Contributors

University of Bath
Rights Holder

Documentation

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.

Documentation Files

README.md
text/plain (4kB)
Creative Commons: Attribution 4.0

Markdown README file

Funders

Dr B Morgan URF - Modelling Collective Lithium-Ion Dynamics in Battery Materials
UF130329

Computational Discovery of Conduction Mechanisms in Lithium-Ion Solid Electrolytes
URF\R\191006

Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266

Materials Chemistry High End Computing Consortium
EP/L000202/1

Publication details

Publication date: 10 July 2020
by: University of Bath

Version: 1

DOI: https://doi.org/10.15125/BATH-00815

URL for this record: https://researchdata.bath.ac.uk/id/eprint/815

Related papers and books

Legein, C., Morgan, B. J., Fayon, F., Koketsu, T., Ma, J., Body, M., Sarou‐Kanian, V., Wei, X.‐K., Heggen, M., Borkiewicz, O. J., Strasser, P., and Dambournet, D., 2020. Atomic Insights into Aluminium‐Ion Insertion in Defective Anatase for Batteries. Angewandte Chemie International Edition, 59(43), 19247-19253. Available from: https://doi.org/10.1002/anie.202007983.

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Departments:

Faculty of Science
Chemistry