How to verify the precision of density-functional-theory implementations via reproducible and universal workflows
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"title": "How to verify the precision of density-functional-theory implementations via reproducible and universal workflows",
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"publication_date": "May 26, 2023, 17:52:57",
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{
"comment": "Journal paper",
"doi": "10.1038/s42254-023-00655-3",
"citation": "E. Bosoni et al., How to verify the precision of density-functional-theory implementations via reproducible and universal workflows, Nat. Rev. Phys. 6, 45 (2024)",
"url": "",
"type": "Journal reference"
},
{
"comment": "Interactive visualization of the data generated in the paper",
"citation": "E. Bosoni et al., Verification of the precision of DFT implementations via AiiDA common workflows, Materials Cloud (2023)",
"url": "https://acwf-verification.materialscloud.org",
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}
],
"description": "In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). This data entry contains all data to reproduce the results, as well as the resulting curated all-electron dataset and the scripts to generate the figures of the paper.",
"status": "published",
"license": "Creative Commons Attribution 4.0 International",
"conceptrecid": "1769",
"is_last": true,
"mcid": "2023.81",
"edited_by": 24,
"id": "1770",
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"doi": "10.24435/materialscloud:s4-3h"
},
"revision": 45,
"created": "2023-05-24T09:01:54.113373+00:00"
}