Published September 12, 2022 | Version 1.0
Dataset Open

Research data supporting "Tin phosphide anodes for potassium-ion batteries: insights from crystal structure prediction"

  • 1. University of Cambridge, UCLouvain
  • 2. University of Birmingham

Description

This dataset contains the output files of crystal structure prediction calculations (density-functional theory relaxations, bandstructures, phonon calculations, GIPAW-NMR calculations) on the ternary K-Sn-P phase diagram. All calculations were performed with the CASTEP DFT package (https://www.castep.org/) and the "matador" Python library (https://github.com/ml-evs/matador).

Contents:

  • "convergence_tests.zip": contains the results of convergence tests on the K-P system at two levels of accuracy "polish" and "searches" on the corresponding edge of the K-Sn-P ternary system
  • "phonons.zip": contains CASTEP output files for phonon calculations on the predicted low-lying phases on the corresponding edge of the K-Sn-P phase diagram
  • "polish.zip": contains CASTEP output files of relaxations on the corresponding edge of the K-Sn-P system at the "polish" level of accuracy using various different xc-functionals or external pressures.
  • "searches.zip": contains ".res" files that provide the relaxed structure from each different crystal structure prediction method on the corresponding edge of the K-Sn-P system.
  • "bulk_modulus.zip" contains CASTEP output files for calculation of E(V) curves for low-lying KP phases with different xc-functionals.
  • "nmr.zip" contains CASTEP output files for GIPAW-NMR calculations of chemical shifts for low-lying K-Sn-P phases.
  • "spectral.zip" contains CASTEP and OptaDOS output files for projected bandstructure and DOS calculations of low-lying K-Sn-P phases.
  • "digests.zip" contains JSON representations of all the structures from polish and searches, broken down into K-P and K-Sn-P specific digests.

Files

bulk_modulus.zip

Files (2.5 GB)

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md5:ce0627f015157abc511318e4f29417b2
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md5:45c137ef721a807040008c2bac62fdca
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md5:1204146718fc558c5b2aa29d23bbf198
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Additional details

Related works

Is supplement to
Journal article: 10.1021/acs.chemmater.2c01570 (DOI)

Funding

EPSRC Centre for Doctoral Training in Computational Methods for Materials Science EP/L015552/1
UK Research and Innovation