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.
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