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

Title of the DatasetCompositional Flexibility in Irreducible Antifluorite Electrolytes for Next Generation Battery Anodes<br>AuthorsVictor Landgraf, Mengfu Tu, Zhu Cheng, Alexandros Vasileiadis, Marnix Wagemaker*, Theodosios Famprikis*<br>Contact InformationCorresponding Authors:<br>Marnix WagemakerEmail: [e-mail]: Delft University of Technology, Faculty of Applied Sciences, Delft, NetherlandsTheodosios FamprikisEmail: [e-mail]: Delft University of Technology, Faculty of Applied Sciences, Delft, Netherlands<br>1. General IntroductionThis 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.<br>2. Description of Files in this DirectoryBottleneck_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<br>Example_Vasprun/:A sample vasprun.xml file from one of the MD simulations carried out in this study.Format: vasprun.xml<br>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<br>LSV/:Linear Sweep Voltammetry (LSV) data for the electrolyte samples, presented in .mpr format.Format: .mpr<br>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<br>VASP_input_files/:Example VASP input files (INCAR, KPOINTS, POTCAR) necessary to reproduce the MD calculations reported in this study.Format: INCAR, KPOINTS, POTCAR<br>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<br>3. Methodological InformationData Collection and Processing MethodsMolecular 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.<br>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.<br>Software UsedVASP (version 5.4): Used for MD simulations.Python (version 3.10): Required to run the analysis scripts.Microsoft Excel: Used for fitting Arrhenius plots.<br>Further methodological details in the associated manuscript: https://doi.org/10.26434/chemrxiv-2024-1d7pt<br>4. Sharing and Access InformationLicensesAnalysis 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.