Pivotal role of intersite Hubbard interactions in Fe-doped α-MnO₂

We present a first-principles investigation of the structural, electronic, and magnetic properties of the pristine and Fe-doped α-MnO₂ using density-functional theory with extended Hubbard functionals. The onsite U and intersite V Hubbard parameters are determined from first principles and self-consistently using density-functional perturbation theory in the basis of Löwdin-orthogonalized atomic orbitals. First, we analyze the pristine α-MnO₂ and show that the C2-AFM spin configuration is the most energetically favorable, in agreement with the experimentally observed antiferromagnetic state. For the Fe-doped α-MnO₂ two types of doping are considered: Fe insertion in the 2 × 2 tunnels and partial substitution of Fe for Mn. The calculated formation energies show that the experimentally observed Fe insertion is energetically favorable only when intersite Hubbard interactions are taken into account. Moreover, we find that both types of doping preserve the C2-AFM spin configuration of the host lattice only when Hubbard V corrections are included. The oxidation state of Fe is found to be +2 and +4 in the case of the interstitial and substitutional doping, respectively, while the oxidation state of Mn is +4 in both cases. This work opens a door for accurate studies of other Mn oxides and complex transition-metal compounds when the localization of 3d electrons occurs in the presence of strong covalent interactions with ligands.

Identifier
Source https://archive.materialscloud.org/record/2022.83
Metadata Access https://archive.materialscloud.org/xml?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:1392
Provenance
Creator Mahajan, Ruchika; Kashyap, Arti; Timrov, Iurii
Publisher Materials Cloud
Publication Year 2022
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 Dataset
Discipline Materials Science and Engineering