Emergent half-metal with mixed structural order in (111)-oriented (LaMnO3)2n|(SrMnO3)n superlattices

Fabrizio Cossu, Jùlio Alves Do Nascimento, Stuart A. Cavill, Igor Di Marco, Vlado K. Lazarov, Heung Sik Kim

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Using first-principles techniques, we study the structural, magnetic, and electronic properties of (111)-oriented (LaMnO3)2n|(SrMnO3)n superlattices of varying thickness (n=2,4,6). We find that the properties of the thinnest superlattice (n=2) are similar to the celebrated half-metallic ferromagnetic alloy La2/3Sr1/3MnO3, with quenched Jahn-Teller distortions. At intermediate thickness (n=4), the a-a-a- tilting pattern transitions to the a-a-c+ tilting pattern, driven by the lattice degrees of freedom in the LaMnO3 region. The emergence of the Jahn-Teller modes and the spatial extent needed for their development play a key role in this structural transition. For the largest thickness considered (n=6), we unveil an emergent separation of Jahn-Teller and volume-breathing orders in the ground-state structure with the a-a-c+ tilting pattern, whereas it vanishes in the antiferromagnetic configurations. The ground state of all superlattices is half-metallic ferromagnetic, not affected by the underlying series of structural transitions. Overall, these results outline a thickness-induced crossover between the physical properties of bulk La2/3Sr1/3MnO3 and bulk LaMnO3.

Original languageEnglish
Article number045435
Number of pages10
JournalPhysical Review B
Issue number4
Publication statusPublished - 15 Jan 2024

Bibliographical note

Funding Information:
We are thankful to I. I. Mazin, A. Edström, and A. Akbari for valuable discussions. The computational resources were provided by the Korean Institute of Science and Technology Information (KISTI) national supercomputing center (Project No. KSC-2022-CRE-0358), by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at the Center for High Performance Computing (PDC) in Stockholm, Sweden, partially funded by the Swedish Research Council through Grants No. 2022-06725 and No. 2018-05973; we additionally appreciate the computational support from the University of York High-Performance Computing service, Viking, and the Research Computing team. F.C., H.-S.K., and I.D.M. acknowledge financial support from the National Research Foundation (NRF) funded by the Ministry of Science of Korea (Grants No. 2022R1I1A1A01071974, No. 2020R1C1C1005900, and No. 2020R1A2C101217411, respectively). H.-S.K. acknowledges additional support from the international cooperation program managed by the National Research Foundation of Korea (NRF, Grant No. NRF-2023K2A9A2A12000317). I.D.M. acknowledges financial support from the European Research Council (ERC), Synergy Grant FASTCORR, Project No. 854843. This research is also part of Project No. 2022/45/P/ST3/04247 cofunded by the National Science Centre and the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant No. 945339.

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