Machine-learning-enabled ab initio study of quantum phase transitions in SrTiO3

DOI

<p>We use the self-consistent harmonic approximation (SSCHA) with machine learning interatomic potentials to calculate the effect of <sup>18</sup>O substitution on the properties of quantum paraelectric SrTiO<sub>3</sub> (STO). We find that calculations including both quantum and anharmonic effects are able to reproduce the experimentally observed isotope effect, in which the replacement of <sup>16</sup>O by <sup>18</sup>O induces the ferroelectric state, and we demonstrate that the ferroelectric phase transition in ST<sup>18</sup>O can be reproduced in a purely displacive description. We calculate the ferroelectric soft mode frequency as a function of volume, lattice parameters, and temperature for ST<sup>16</sup>O and ST<sup>18</sup>O and find that the phase space in which ST<sup>16</sup>O shows quantum<br>paraelectric behavior, while ST<sup>18</sup>O becomes ferroelectric, is narrow. Our Letter shows that machine learning interatomic potentials enable temperature-dependent simulations that include quantum and anharmonic phonon effects and that quantitative prediction of the phase diagram in the case of STO is limited by the accuracy of the underlying electronic structure method.</p> <p>This dataset contains the inputs/and outputs from the SSCHA calculations. </p>

Identifier
DOI https://doi.org/10.24435/materialscloud:ra-x7
Related Identifier https://doi.org/10.1103/4293-1g2r
Related Identifier https://archive.materialscloud.org/communities/mcarchive
Related Identifier https://doi.org/10.24435/materialscloud:yj-5b
Metadata Access https://archive.materialscloud.org/oai2d?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:jatqz-bah71
Provenance
Creator Schmidt, Jonathan; Spaldin, Nicola A.
Publisher Materials Cloud
Contributor Schmidt, Jonathan
Publication Year 2026
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type info:eu-repo/semantics/other
Format text/markdown; application/gzip
Discipline Materials Science and Engineering