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Dynamically‐driven emergence in a nanomagnetic system

DOI: 10.1002/adfm.202008389 DOI Help

Authors: Richard W. Dawidek (University of Sheffield) , Thomas J. Hayward (University of Sheffield) , Ian T. Vidamour (University of Sheffield) , Thomas J. Broomhall (University of Sheffield) , Guru Venkat (University of Sheffield) , Mohanad Al Mamoori (University of Sheffield) , Aidan Mullen (University of Sheffield) , Stephan J. Kyle (University of Sheffield) , Paul W. Fry (University of Sheffield) , Nina-Juliane Steinke (ISIS Neutron and Muon Source) , Joshaniel F. K. Cooper (ISIS Neutron and Muon Source) , Francesco Maccherozzi (Diamond Light Source) , Sarnjeet S. Dhesi (Diamond Light Source) , Lucia Aballe (ALBA Synchrotron Light Facility) , Michael Foerster (ALBA Synchrotron Light Facility) , Jordi Prat (ALBA Synchrotron Light Facility) , Eleni Vasilaki (University of Sheffield) , Matthew O. A. Ellis (University of Sheffield) , Dan A. Allwood (University of Sheffield)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Advanced Functional Materials , VOL 320

State: Published (Approved)
Published: February 2021
Diamond Proposal Number(s): 24205

Open Access Open Access

Abstract: Emergent behaviors occur when simple interactions between a system's constituent elements produce properties that the individual elements do not exhibit in isolation. This article reports tunable emergent behaviors observed in domain wall (DW) populations of arrays of interconnected magnetic ring‐shaped nanowires under an applied rotating magnetic field. DWs interact stochastically at ring junctions to create mechanisms of DW population loss and gain. These combine to give a dynamic, field‐dependent equilibrium DW population that is a robust and emergent property of the array, despite highly varied local magnetic configurations. The magnetic ring arrays’ properties (e.g., non‐linear behavior, “fading memory” to changes in field, fabrication repeatability, and scalability) suggest they are an interesting candidate system for realizing reservoir computing (RC), a form of neuromorphic computing, in hardware. By way of example, simulations of ring arrays performing RC approaches 100% success in classifying spoken digits for single speakers.

Journal Keywords: emergent behavior; magnetic domain walls; magnetic nanowires; reservoir computing

Diamond Keywords: Ferromagnetism

Subject Areas: Materials, Physics


Instruments: I06-Nanoscience

Other Facilities: Offspec beamline at ISIS

Added On: 18/02/2021 08:55

Documents:
adfm.202008389.pdf

Discipline Tags:

Materials Science Quantum Materials Physics Electronics Magnetism Nanoscience/Nanotechnology

Technical Tags:

Microscopy Electron Microscopy (EM) PhotoEmmission Electron Microscopy (PEEM)