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  5. Biquadratic exchange interactions in two-dimensional magnets

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Article
English
2020

Biquadratic exchange interactions in two-dimensional magnets

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English
2020
npj Computational Materials
Vol 6 (1)
DOI: 10.1038/s41524-020-00416-1

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Konstantin ‘kostya’  Novoselov
Konstantin ‘kostya’ Novoselov

The University of Manchester

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Alexey Kartsev
Mathias Augustin
Richard F. L. Evans
+2 more

Abstract

Magnetism in recently discovered van der Waals materials has opened new avenues in the study of fundamental spin interactions in truly two-dimensions. A paramount question is what effect higher-order interactions beyond bilinear Heisenberg exchange have on the magnetic properties of few-atom thick compounds. Here we demonstrate that biquadratic exchange interactions, which is the simplest and most natural form of non-Heisenberg coupling, assume a key role in the magnetic properties of layered magnets. Using a combination of nonperturbative analytical techniques, non-collinear first-principles methods and classical Monte Carlo calculations that incorporate higher-order exchange, we show that several quantities including magnetic anisotropies, spin-wave gaps and topological spin-excitations are intrinsically renormalized leading to further thermal stability of the layers. We develop a spin Hamiltonian that also contains antisymmetric exchanges (e.g. Dzyaloshinskii-Moriya interactions) to successfully rationalize numerous observations currently under debate, such as the non-Ising character of several compounds despite a strong magnetic anisotropy, peculiarities of the magnon spectrum of 2D magnets, and the discrepancy between measured and calculated Curie temperatures. Our results lay the foundation of a universal higher-order exchange theory for novel 2D magnetic design strategies.

How to cite this publication

Alexey Kartsev, Mathias Augustin, Richard F. L. Evans, Konstantin ‘kostya’ Novoselov, Elton J. G. Santos (2020). Biquadratic exchange interactions in two-dimensional magnets. npj Computational Materials, 6(1), DOI: 10.1038/s41524-020-00416-1.

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Publication Details

Type

Article

Year

2020

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

npj Computational Materials

DOI

10.1038/s41524-020-00416-1

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