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Research data supporting 'Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory'.


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Type

Dataset

Change log

Authors

Tait, Edward 
Hine, Nicholas 

Description

Input and output files for the simulations performed for the publication "Simulation of electron energy loss spectra of nanomaterials with linear-scaling density functional theory" Several software packages were used: onetep (linear Scaling DFT) http://www.onetep.org/ castep (conventional plane wave DFT) http://www.castep.org/ ELK (all electron DFT) http://elk.sourceforge.net/ OptaDoS (computing spectra) http://www.optados.org/ Input files for all simulations are included, as are relevant textual and binary outputs. The data to reproduce the experimental lines is not included, but may be extracted from the publications cited in the paper. Viewers may find the .elnes_bin and .odi files of particular interest as these may be used (together with OptaDoS) to compute new EEL spectra for the atoms studied using different broadening parameters or in polarised geometries (i.e. not isotropically averaged).

Version

Software / Usage instructions

.tar.gz of a directory structure containing the input + output files. All input files and output files are human readable except the .elnes_bin files which are binary and formatted as described in http://www.tcm.phy.cam.ac.uk/~ajm255/optados/files/user_guide_1.2.pdf appendix A.4 *.dat onetep input files (and optados spectra output *_core_edge.dat) *-out.cell castep output cell file, also used as an input by OptaDoS. *.out onetep output files *.bands onetep+castep band energy file *.cell, *.param castep input files *.castep castep output files *.odi *.odo OptaDoS input+output files *.in, ELK input files INFO.OUT ELNES.OUT ELK output files *.py helper python scripts for combining spectra *.gpl GNU plot input files

Keywords

ELNES, EELS, Linear Scaling, DFT, Anatase, Theoretical Spectroscopy

Publisher

University of Cambridge
Sponsorship
This work was supported by the EPSRC [grant number EP/G037221/1].
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