Phase transitions of LaMnO3 and SrRuO3 from DFT+U based machine learning force fields simulations

Thies Jansen*, Geert Brocks, Menno Bokdam

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Perovskite oxides are known to exhibit many magnetic, electronic, and structural phases as function of doping and temperature. These materials are theoretically frequently investigated by the DFT+U method, typically in their ground state structure at T=0. We show that by combining machine learning force fields (MLFFs) and DFT+U based molecular dynamics, it becomes possible to investigate the crystal structure of complex oxides as function of temperature and U. Here, we apply this method to the magnetic transition metal compounds LaMnO3 and SrRuO3. We show that the structural phase transition from orthorhombic to cubic in LaMnO3, which is accompanied by the suppression of a Jahn-Teller distortion, can be simulated with an appropriate choice of U. For SrRuO3, we show that the sequence of orthorhombic to tetragonal to cubic crystal phase transitions can be described with great accuracy. We propose that the U values that correctly capture the temperature-dependent structures of these complex oxides can be identified by comparison of the MLFF simulated and experimentally determined structures.

Original languageEnglish
Article number235122
Number of pages9
JournalPhysical Review B
Volume108
Issue number23
DOIs
Publication statusPublished - 5 Dec 2023

Keywords

  • 2024 OA procedure

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