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Copy file name to clipboardExpand all lines: paper/paper.bib
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@@ -90,7 +90,6 @@ @article{Popescu:2009
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year = {2012},
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note = {Publisher: American Physical Society},
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pages = {085201},
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file = {Popescu_Zunger_2012_Extracting \$E\$ versus \$-stackrel P-vec k \$ effective band structure from.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\Physical Review B\\Popescu_Zunger_2012_Extracting \$E\$ versus \$-stackrel P-vec k \$ effective band structure from.pdf:application/pdf},
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}
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@@ -131,7 +130,6 @@ @article{huang:2022
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note = {Number: 1
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Publisher: Nature Publishing Group},
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keywords = {easyunfold, Electronic materials, Solar cells},
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file = {Huang et al_2022_Strong absorption and ultrafast localisation in NaBiS2 nanocrystals with slow.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\Nature Communications2022\\Huang et al_2022_Strong absorption and ultrafast localisation in NaBiS2 nanocrystals with slow.pdf:application/pdf},
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}
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@article{nicolson:2023,
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date = {2023-05-30},
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note = {Publisher: American Chemical Society},
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keywords = {easyunfold},
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file = {ACS Full Text Snapshot:C\:\\Users\\zhubo\\Zotero\\storage\\XAU4UB2M\\jacs.html:text/html;Nicolson et al_2023_Interplay of Static and Dynamic Disorder in the Mixed-Metal Chalcohalide.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\Journal of the American Chemical Society2023\\Nicolson et al_2023_Interplay of Static and Dynamic Disorder in the Mixed-Metal Chalcohalide.pdf:application/pdf},
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}
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@article{wang:2022,
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note = {Number: 3
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Publisher: Nature Publishing Group},
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keywords = {easyunfold, Quantum dots, Solar cells},
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file = {Wang et al_2022_Cation disorder engineering yields AgBiS2 nanocrystals with enhanced optical.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\Nature Photonics2022\\Wang et al_2022_Cation disorder engineering yields AgBiS2 nanocrystals with enhanced optical.pdf:application/pdf},
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}
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@article{huber:2020,
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title = {{AiiDA} 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance},
abstract = {The ever-growing availability of computing power and the sustained development of advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA’s workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with external simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.},
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language = {en},
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number = {1},
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urldate = {2021-05-06},
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journal = {Scientific Data},
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author = {Huber, Sebastiaan P. and Zoupanos, Spyros and Uhrin, Martin and Talirz, Leopold and Kahle, Leonid and Häuselmann, Rico and Gresch, Dominik and Müller, Tiziano and Yakutovich, Aliaksandr V. and Andersen, Casper W. and Ramirez, Francisco F. and Adorf, Carl S. and Gargiulo, Fernando and Kumbhar, Snehal and Passaro, Elsa and Johnston, Conrad and Merkys, Andrius and Cepellotti, Andrea and Mounet, Nicolas and Marzari, Nicola and Kozinsky, Boris and Pizzi, Giovanni},
file = {arXiv.org Snapshot:C\:\\Users\\zhubo\\Zotero\\storage\\EL4M6KNU\\2003.html:text/html;Huber et al_2020_AiiDA 1.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\arXiv2003.12476 [cond-mat]\\Huber et al_2020_AiiDA 1.pdf:application/pdf;Huber et al_2020_AiiDA 1.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\Scientific Data\\Huber et al_2020_AiiDA 1.pdf:application/pdf;Snapshot:C\:\\Users\\zhubo\\Zotero\\storage\\XQX3Y89C\\s41597-020-00638-4.html:text/html},
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month = sep,
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year = {2020},
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note = {Number: 1
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Publisher: Nature Publishing Group},
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pages = {300},
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}
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@article{wilkinson:2016,
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urldate = {2023-06-15},
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date = {2017-11-01},
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langid = {english},
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file = {Mathew et al_2017_Atomate.pdf:C\:\\Users\\zhubo\\Dropbox (UCL)\\Zotero\\Computational Materials Science2017\\Mathew et al_2017_Atomate.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\zhubo\\Zotero\\storage\\A7B86F72\\S0927025617303919.html:text/html},
file = {ACS Full Text Snapshot:/Users/kavanase/Zotero/storage/RLFR4VF8/acs.jpcc.html:text/html},
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}
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@article{Ganose_2018, doi = {10.21105/joss.00717}, url = {https://doi.org/10.21105/joss.00717}, year = {2018}, publisher = {The Open Journal}, volume = {3}, number = {28}, pages = {717}, author = {Alex M. Ganose and Adam J. Jackson and David O. Scanlon}, title = {sumo: Command-line tools for plotting and analysis of periodic *ab initio* calculations}, journal = {Journal of Open Source Software} }
Copy file name to clipboardExpand all lines: paper/paper.md
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@@ -39,9 +39,9 @@ The electronic band structure is an important property for
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understanding and designing solid crystalline materials in many fields
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such as photovoltaic, catalytic, thermoelectric and transparent-conducting
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materials. Obtaining the band structure for an ideal crystal through first-principles
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density functional theory (DFT) calculations is a well-established routine operation[@Ganose_2018].
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density functional theory (DFT) calculations is a well-established routine operation[@Ganose_2018].
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However, the materials of interest are often complex and the simulation cells may contain multiple primitive
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cells of the archetypal structure when, for example, modelling disordered or defective materials[@Kim_2020].
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cells of the archetypal structure when, for example, modelling disordered or defective materials[@Kim_2020].
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Repeating the unit cell in real space results in folded band structures, as illustrated in \autoref{fig:figure1}, complicating its interpretation and analysis.
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Band structure unfolding maps the electronic structure from supercell calculations back to the reciprocal lattice of the primitive cell,
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thereby enabling researchers to understand structure-property relationships and compare the effect of various crystal imperfections on an equal footing.
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`easyunfold` is written in Python with a focus on user-friendliness, data provenance, reproducibility, and publication-quality figure generation.
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An example output of the effective band structure produced is shown in \autoref{fig:figure2} for a $2\times2\times2$ $\mathrm{MgO}$ supercell containing a neutral oxygen vacancy.
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\autoref{fig:figure3} shows the orbital-projected effective band structure of a $\mathrm{Cs_2(Sn_{0.5},Ti_{0.5})Br_6}$ vacancy-ordered perovskite alloy [@kavanagh_frenkel_2022; @liga_mixed-cation_2023], in the Brillouin zone of the primitive $Fm\bar{3}m$ unit cell.
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A key feature of `easyunfold` is to provide data serialization compliant with the FAIR principles [@wilkinson:2016].
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A key feature of `easyunfold` is to provide data serialisation compliant with the FAIR principles [@wilkinson:2016].
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Both the input settings and calculated outputs are stored in a single JSON file.
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This enables the unfolded band structure to be re-plotted and further analysed without reprocessing the wave function data, which can be time-consuming and require large storage space.
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