Common workflows for computing material properties using different quantum engines
Abstract The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great...
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Nature Portfolio
2021
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oai:doaj.org-article:ef56a83500024ae0acb300450c076df12021-12-02T18:51:46ZCommon workflows for computing material properties using different quantum engines10.1038/s41524-021-00594-62057-3960https://doaj.org/article/ef56a83500024ae0acb300450c076df12021-08-01T00:00:00Zhttps://doi.org/10.1038/s41524-021-00594-6https://doaj.org/toc/2057-3960Abstract The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.Sebastiaan P. HuberEmanuele BosoniMarnik BercxJens BröderAugustin DegommeVladimir DikanKristjan EimreEspen Flage-LarsenAlberto GarciaLuigi GenoveseDominik GreschConrad JohnstonGuido PetrettoSamuel PoncéGian-Marco RignaneseChristopher J. SewellBerend SmitVasily TseplyaevMartin UhrinDaniel WortmannAliaksandr V. YakutovichAustin ZadoksPezhman Zarabadi-PoorBonan ZhuNicola MarzariGiovanni PizziNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492Computer softwareQA76.75-76.765ENnpj Computational Materials, Vol 7, Iss 1, Pp 1-12 (2021) |
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DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 |
| spellingShingle |
Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 Sebastiaan P. Huber Emanuele Bosoni Marnik Bercx Jens Bröder Augustin Degomme Vladimir Dikan Kristjan Eimre Espen Flage-Larsen Alberto Garcia Luigi Genovese Dominik Gresch Conrad Johnston Guido Petretto Samuel Poncé Gian-Marco Rignanese Christopher J. Sewell Berend Smit Vasily Tseplyaev Martin Uhrin Daniel Wortmann Aliaksandr V. Yakutovich Austin Zadoks Pezhman Zarabadi-Poor Bonan Zhu Nicola Marzari Giovanni Pizzi Common workflows for computing material properties using different quantum engines |
| description |
Abstract The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use them. We demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and cross-verification. We introduce design rules for reusable, code-agnostic, workflow interfaces to compute well-defined material properties, which we implement for eleven quantum engines and use to compute various material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer’s expertise of the quantum engine directly available to non-experts. All workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure. |
| format |
article |
| author |
Sebastiaan P. Huber Emanuele Bosoni Marnik Bercx Jens Bröder Augustin Degomme Vladimir Dikan Kristjan Eimre Espen Flage-Larsen Alberto Garcia Luigi Genovese Dominik Gresch Conrad Johnston Guido Petretto Samuel Poncé Gian-Marco Rignanese Christopher J. Sewell Berend Smit Vasily Tseplyaev Martin Uhrin Daniel Wortmann Aliaksandr V. Yakutovich Austin Zadoks Pezhman Zarabadi-Poor Bonan Zhu Nicola Marzari Giovanni Pizzi |
| author_facet |
Sebastiaan P. Huber Emanuele Bosoni Marnik Bercx Jens Bröder Augustin Degomme Vladimir Dikan Kristjan Eimre Espen Flage-Larsen Alberto Garcia Luigi Genovese Dominik Gresch Conrad Johnston Guido Petretto Samuel Poncé Gian-Marco Rignanese Christopher J. Sewell Berend Smit Vasily Tseplyaev Martin Uhrin Daniel Wortmann Aliaksandr V. Yakutovich Austin Zadoks Pezhman Zarabadi-Poor Bonan Zhu Nicola Marzari Giovanni Pizzi |
| author_sort |
Sebastiaan P. Huber |
| title |
Common workflows for computing material properties using different quantum engines |
| title_short |
Common workflows for computing material properties using different quantum engines |
| title_full |
Common workflows for computing material properties using different quantum engines |
| title_fullStr |
Common workflows for computing material properties using different quantum engines |
| title_full_unstemmed |
Common workflows for computing material properties using different quantum engines |
| title_sort |
common workflows for computing material properties using different quantum engines |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/ef56a83500024ae0acb300450c076df1 |
| work_keys_str_mv |
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