Data underlying the publication: Compositional flexibility in irreducible antifluorite electrolytes for next generation battery anodes

DOI:10.4121/fcb46e92-06cd-4241-a97b-3390d6dc1f70.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/fcb46e92-06cd-4241-a97b-3390d6dc1f70

Datacite citation style

Famprikis, Theo; Landgraf, Victor; Wagemaker, Marnix (2024): Data underlying the publication: Compositional flexibility in irreducible antifluorite electrolytes for next generation battery anodes. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/fcb46e92-06cd-4241-a97b-3390d6dc1f70.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Title of the Dataset

Compositional Flexibility in Irreducible Antifluorite Electrolytes for Next Generation Battery Anodes


Authors

Victor Landgraf, Mengfu Tu, Zhu Cheng, Alexandros Vasileiadis, Marnix Wagemaker*, Theodosios Famprikis*


Contact Information

Corresponding Authors:


Marnix Wagemaker

Email: m.wagemaker@tudelft.nl

Institution: Delft University of Technology, Faculty of Applied Sciences, Delft, Netherlands

Theodosios Famprikis

Email: t.famprikis@tudelft.nl

Institution: Delft University of Technology, Faculty of Applied Sciences, Delft, Netherlands


1. General Introduction

This directory contains raw data and scripts used to reproduce the analysis performed in the study titled: Compositional Flexibility in Irreducible Antifluorite Electrolytes for Next Generation Battery Anodes. The data and analysis are related to the investigation of lithium-ion conduction in antifluorite-type materials, with implications for next-generation battery anodes. The dataset is publicly available for further research purposes and to support the reproducibility of the publication.


2. Description of Files in this Directory

Bottleneck_size_calculations/:

This folder contains a Python script (bottleneck_size_analysis.py) used to analyze bottleneck sizes in the electrolyte structures. POSCAR files for molecular dynamics (MD) simulations are also included.

Format: .py, POSCAR


Example_Vasprun/:

A sample vasprun.xml file from one of the MD simulations carried out in this study.

Format: vasprun.xml


Jump_analysis/:

This folder includes a Python script (jump_analysis.py) that analyzes the MD trajectories and extracts individual lithium ion hops. It also contains the MD trajectories in a cached format (.cache) and initial structure files (POSCAR).

Format: .py, .cache, POSCAR


LSV/:

Linear Sweep Voltammetry (LSV) data for the electrolyte samples, presented in .mpr format.

Format: .mpr


Relative_Site_Energy_calculations/:

Python scripts (relative_site_energy_analysis.py) used to analyze the jump library and calculate relative site energies based on the forward and backward jump rates for each type of jump.

Format: .py


VASP_input_files/:

Example VASP input files (INCAR, KPOINTS, POTCAR) necessary to reproduce the MD calculations reported in this study.

Format: INCAR, KPOINTS, POTCAR


XRD_and_EIS/:

This folder includes impedance spectra in .txt format and the associated temperature-dependent analysis (Arrhenius fitting in .xlsx). Diffractograms in .xrdml, .dat, and .raw formats are provided, along with Python scripts (xrd_eis_analysis.py) for generating plots used in the manuscript.

Format: .txt, .xlsx, .xrdml, .dat, .raw, .py


3. Methodological Information

Data Collection and Processing Methods

Molecular Dynamics (MD) Simulations:

MD simulations were conducted using VASP (version 5.4), with the results stored in vasprun.xml and processed using Python scripts to analyze bottleneck sizes, lithium jumps, and relative site energies.


Experimental Data:

Linear Sweep Voltammetry (LSV) and X-Ray Diffraction (XRD) data were collected using commercially available instruments, and the results were processed using Python scripts and Microsoft Excel for temperature-dependent fitting.


Software Used

VASP (version 5.4): Used for MD simulations.

Python (version 3.10): Required to run the analysis scripts.

Microsoft Excel: Used for fitting Arrhenius plots.


Further methodological details in the associated manuscript: https://doi.org/10.26434/chemrxiv-2024-1d7pt


4. Sharing and Access Information

Licenses

Analysis scripts: Licensed under the Apache-2.0 license, allowing open use, modification, and distribution of the scripts.

Data files: Licensed under the CC-BY-NC-4.0 license, permitting reuse and redistribution for non-commercial purposes with proper attribution.

History

  • 2024-10-22 first online, published, posted

Publisher

4TU.ResearchData

Format

python scripts (.py), impedance spectra (.txt), diffractogram files (.raw, .xrdml), VASP input files (INCAR, POSCAR, POTCAR, KPOINTS), VASP output files (.xml, .cache)

Organizations

TU Delft, Faculty of Applied Sciences, Department of Radiation, Science and Technology

DATA

Files (8)