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On-the-fly assessment of diffusion barriers of disordered transition metal oxyfluorides using local descriptors

Jin Hyun Chang1, Peter Bjørn Jørgensen1, Simon Loftager1, Arghya Bhowmik1, Juan María García Lastra1, Tejs Vegge1*

1 Department of Energy Conversion and Storage, Technical University of Denmark, Kgs. Lyngby, DK-2800, Denmark

* Corresponding authors emails: teve@dtu.dk
DOI10.24435/materialscloud:9v-3q [version v1]

Publication date: May 03, 2021

How to cite this record

Jin Hyun Chang, Peter Bjørn Jørgensen, Simon Loftager, Arghya Bhowmik, Juan María García Lastra, Tejs Vegge, On-the-fly assessment of diffusion barriers of disordered transition metal oxyfluorides using local descriptors, Materials Cloud Archive 2021.69 (2021), doi: 10.24435/materialscloud:9v-3q.

Description

The dataset contains the result of 48 Nudged Elastic Band calculations of Li(2-x)VO2F diffusion barriers in the format of Atomic Simulation Environment (ASE) trajectories. The NEB was performed with VASP, using projector augmented-wave (PAW) method to describe electron-ion interaction. The disordered rock salt cells were created using a 3 x 4 x 4 supercell containing 96 atoms (in case of no vacancies). PBE is used as XC functional while a rotationally invariant Hubbard U correction was applied to the d orbital of V with a U value of 3.25 eV. See more details in the paper.

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Files

File name Size Description
trajectories.tar.gz
MD5md5:ede113e0ed91965c6f2982276b0c9bfc
755.5 KiB Contains the result of 48 NEB calculations in the form of ASE trajectory files
parse_traj.py
MD5md5:4c29c3b8b79ccebd545fa17ab0abce54
7.8 KiB Python script to parse the trajectory files and create the features used for the machine learning model as a json file.

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Journal reference (Paper in which the data is described and a prediction model is devised based on the data.)
J. H. Chang, P. B. Jørgensen, S. Loftager, A. Bhowmik, J. M. G. Lastra, T. Vegge, Electrochima Acta 388, 138551 (2021) doi:10.1016/j.electacta.2021.138551

Keywords

FET-OPEN BIG-MAP LiRichFCC Villum Foundation Young Investigator Programme machine learning nudged elastic band lithium diffusion

Version history:

2021.69 (version v1) [This version] May 03, 2021 DOI10.24435/materialscloud:9v-3q