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Coupled spin-lattice dynamics from the tight-binding electronic structure
Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, AlbaNova University Center, Stockholm, Sweden; Instituto de Física, Universidade Federal Fluminense, Niterói RJ, Brazil.
Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden.
Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, AlbaNova University Center, Stockholm, Sweden.
Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden.ORCID iD: 0000-0003-2977-255X
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2024 (English)In: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 109, no 14, article id 144303Article in journal (Refereed) Published
Abstract [en]

We developed a method which performs the coupled adiabatic spin and lattice dynamics based on the tight-binding electronic structure model, where the intrinsic magnetic field and ionic forces are calculated from the converged self-consistent electronic structure at every time step. By doing so, this method allows us to explore limits where the physics described by a parameterized spin-lattice Hamiltonian is no longer accurate. We demonstrate how the lattice dynamics is strongly influenced by the underlying magnetic configuration, where disorder is able to induce significant lattice distortions. The presented method requires significantly less computational resources than ab initio methods, such as time-dependent density functional theory (TD-DFT). Compared to parameterized Hamiltonian-based methods, it also describes more accurately the dynamics of the coupled spin and lattice degrees of freedom, which becomes important outside of the regime of small lattice and spin fluctuations.

Place, publisher, year, edition, pages
American Physical Society , 2024. Vol. 109, no 14, article id 144303
National Category
Condensed Matter Physics
Identifiers
URN: urn:nbn:se:oru:diva-114064DOI: 10.1103/PhysRevB.109.144303ISI: 001229873700003Scopus ID: 2-s2.0-85190437482OAI: oai:DiVA.org:oru-114064DiVA, id: diva2:1867346
Funder
Knut and Alice Wallenberg Foundation, 2018.0060; 2021.024; 2022.0108Swedish Research Council, 2019-03666; 2016-05980; 2019-05304; 2022-06725; 2018-05973eSSENCE - An eScience CollaborationStandUpSwedish National Infrastructure for Computing (SNIC)
Note

This work was financially supported by the Knut and Alice Wallenberg (KAW) Foundation through Grants No. 2018.0060, No. 2021.024, and No. 2022.0108. O.E. acknowledges support by the Swedish Research Council (VR) , the European Research Council (854843-FASTCORR) , eSSENCE and STandUP. D.T. acknowledges financial support from the Swedish Research Council (Vetenskapsradet, VR) , Grant No. 2019-03666. A.D. acknowledges financial support from the Swedish Research Council (Vetenskapsradet, VR) , Grant No. 2016-05980 and No. 2019-05304. A.D. and O.E. acknowledge support from the Wallenberg Initiative Materials Science for Sustainability (WISE) funded by the Knut and Alice Wallenberg Foundation (KAW) , R.C. acknowledges financial support from FAPERJ-Fundac & atilde;o Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Grant No. E-26/205.956/2022 and No. 205.957/2022 (282056). The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at NSC and PDC, partially funded by the Swedish Research Council through grant agreements No. 2022-06725 and No. 2018-05973.

Available from: 2024-06-10 Created: 2024-06-10 Last updated: 2024-06-10Bibliographically approved

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