An automatically curated first-principles database of ferroelectrics

Smidt, Tess E.; Mack, Stephanie A.; Reyes-Lillo, Sebastian E.; Jain, Anubhav; Neaton, Jeffrey B.

doi:10.1038/s41597-020-0407-9

Title: An automatically curated first-principles database of ferroelectrics

Journal Article · Tue Mar 03 00:00:00 EST 2020 · Scientific Data

DOI:https://doi.org/10.1038/s41597-020-0407-9· OSTI ID:1619167

Smidt, Tess E. ^[1]; Mack, Stephanie A. ^[1];

^[2];

^[3]; Neaton, Jeffrey B. ^[4]

Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. Andres Bello, Santiago (Chile)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kavli Energy NanoScience Institute, Berkeley, CA (United States)

Ferroelectric materials have technological applications in information storage and electronic devices. The ferroelectric polar phase can be controlled with external fields, chemical substitution and size-effects in bulk and ultrathin film form, providing a platform for future technologies and for exploratory research. In this work, we integrate spin-polarized density functional theory (DFT) calculations, crystal structure databases, symmetry tools, workflow software, and a custom analysis toolkit to build a library of known, previously-proposed, and newly-proposed ferroelectric materials. With our automated workflow, we screen over 67,000 candidate materials from the Materials Project database to generate a dataset of 255 ferroelectric candidates, and propose 126 new ferroelectric materials. We benchmark our results against experimental data and previous first-principles results. The data provided includes atomic structures, output files, and DFT values of band gaps, energies, and the spontaneous polarization for each ferroelectric candidate. Finally, we contribute our workflow and analysis code to the open-source python packages atomate and pymatgen so others can conduct analogous symmetry driven searches for ferroelectrics and related phenomena.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division; National Science Foundation (NSF); FONDECYT Iniciacion en Investigacion

Grant/Contract Number:: AC02-05CH11231; DGE 1106400; 11180590

OSTI ID:: 1619167

Journal Information:: Scientific Data, Vol. 7, Issue 1; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 32 works

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