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Dataset in support of the journal article 'A workflow for identifying viable crystal structures with partially occupied sites applied to solid electrolyte: Cubic Li$_7$La$_3$Zr$_2$O$_{12}$'

Dataset in support of the journal article 'A workflow for identifying viable crystal structures with partially occupied sites applied to solid electrolyte: Cubic Li$_7$La$_3$Zr$_2$O$_{12}$'
Dataset in support of the journal article 'A workflow for identifying viable crystal structures with partially occupied sites applied to solid electrolyte: Cubic Li$_7$La$_3$Zr$_2$O$_{12}$'
c-LLZO Structures A data set containing all c-LLZO structures that are symmetrically unique and have a Li-Li spacing of over 1.7 angstrom, It is accompanied by a csv file which contains energy and symmetry assignments
c-LLZO, Machine Learning, DFT, Solid Electrolyte, Atomic Structures, Battery, Workflow
University of Southampton
Holland, Julian Oliver
21dba625-6e59-4714-ba08-f63a5af9a411
Skylaris, Chris-Kriton
8f593d13-3ace-4558-ba08-04e48211af61
Holland, Julian Oliver
21dba625-6e59-4714-ba08-f63a5af9a411
Skylaris, Chris-Kriton
8f593d13-3ace-4558-ba08-04e48211af61

Holland, Julian Oliver (2023) Dataset in support of the journal article 'A workflow for identifying viable crystal structures with partially occupied sites applied to solid electrolyte: Cubic Li$_7$La$_3$Zr$_2$O$_{12}$'. University of Southampton doi:10.5258/SOTON/D2704 [Dataset]

Record type: Dataset

Abstract

c-LLZO Structures A data set containing all c-LLZO structures that are symmetrically unique and have a Li-Li spacing of over 1.7 angstrom, It is accompanied by a csv file which contains energy and symmetry assignments

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README.txt - Dataset
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all_cllzo.zip - Dataset
Available under License Creative Commons Attribution.
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dft_results.zip - Dataset
Available under License Creative Commons Attribution.
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scripts.zip - Dataset
Available under License Creative Commons Attribution.
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cllzo_data.csv - Dataset
Available under License Creative Commons Attribution.
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cllzo_data_index.txt - Dataset
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More information

Published date: 4 July 2023
Related URLs:
Keywords: c-LLZO, Machine Learning, DFT, Solid Electrolyte, Atomic Structures, Battery, Workflow
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Identifiers

Local EPrints ID: 480550
URI: http://eprints.soton.ac.uk/id/eprint/480550
DOI: doi:10.5258/SOTON/D2704
PURE UUID: ac35c3a6-1e97-435d-89d7-eacb595265c5
ORCID for Julian Oliver Holland: ORCID iD orcid.org/0000-0001-8959-0112
ORCID for Chris-Kriton Skylaris: ORCID iD orcid.org/0000-0003-0258-3433

Catalogue record

Date deposited: 04 Aug 2023 16:40
Last modified: 11 Nov 2023 02:59

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Contributors

Creator: Julian Oliver Holland ORCID iD
Research team head: Chris-Kriton Skylaris ORCID iD

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