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Fabrication of Magnetic Nanostructures on Silicon Nitride Membranes for Magnetic Vortex Studies Using Transmission Microscopy Techniques
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Vortex dynamics and frequency splitting in vertically coupled nanomagnets.

M E Stebliy1, S Jain2,3, A G Kolesnikov1

  • 1School of Natural Sciences, Far Eastern Federal University, Vladivostok, 690091, Russia.

Scientific Reports
|April 27, 2017
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Summary
This summary is machine-generated.

We studied two magnetic vortex cores interacting via dipole forces. Their frequencies split, tunable by magnetic fields, showing potential for multi-state nanomagnets in memory devices.

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Area of Science:

  • Condensed Matter Physics
  • Materials Science
  • Nanotechnology

Background:

  • Vortex cores in circular nanomagnets exhibit unique dynamic responses.
  • Interactions between magnetic structures can lead to novel phenomena.
  • Understanding these dynamics is crucial for advanced magnetic storage.

Purpose of the Study:

  • To investigate the dynamic response of a vortex core coupled to another.
  • To explore the influence of dipole-dipole interaction on vortex core frequencies.
  • To assess the potential for multi-state magnetic memory applications.

Main Methods:

  • Experimental manipulation of dipole-dipole interaction between two vortex cores.
  • Utilizing micromagnetic simulations to model the system's behavior.
  • Analyzing frequency splitting and resonance frequencies under external magnetic fields.

Main Results:

  • Observed clear frequency splitting corresponding to the gyrofrequencies of both vortex cores.
  • Demonstrated tunability of resonance frequencies by controlling external magnetic field.
  • Found frequency spectra dependence on nanomagnet chirality and asymmetry with bias field.

Conclusions:

  • Strong dynamic dipole-dipole interaction between vortex cores is responsible for observed effects.
  • The distance and chirality significantly influence the coupled vortex core dynamics.
  • Vertically coupled multi-state nanomagnets show promise for magnetoresistive memory applications.