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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Laurson, Lasse
Tampere University
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (19/19 displayed)
- 2024Magnetic domain wall dynamics studied by in-situ lorentz microscopy with aid of custom-made Hall-effect sensor holdercitations
- 2024Barkhausen noise in disordered striplike ferromagnetscitations
- 2024Magnetic domain walls interacting with dislocations in micromagnetic simulationscitations
- 2024Magnetic behavior of steel studied by in-situ Lorentz microscopy, magnetic force microscopy and micromagnetic simulations
- 2024Barkhausen noise in disordered striplike ferromagnets : Experiment versus simulationscitations
- 2023Machine learning dislocation density correlations and solute effects in Mg-based alloyscitations
- 2023Predicting elastic and plastic properties of small iron polycrystals by machine learningcitations
- 2023Multi-instrumental approach to domain walls and their movement in ferromagnetic steels – Origin of Barkhausen noise studied by microscopy techniquescitations
- 2022Novel utilization of microscopy and modelling to better understand Barkhausen noise signal
- 2021Mimicking Barkhausen noise measurement by in-situ transmission electron microscopy - effect of microstructural steel features on Barkhausen noisecitations
- 2020Propagating bands of plastic deformation in a metal alloy as critical avalanchescitations
- 2020Machine learning depinning of dislocation pileupscitations
- 2019Bloch-line dynamics within moving domain walls in 3D ferromagnetscitations
- 2018Effects of precipitates and dislocation loops on the yield stress of irradiated ironcitations
- 2016Predicting sample lifetimes in creep fracture of heterogeneous materialscitations
- 2016Glassy features of crystal plasticitycitations
- 2014Influence of material defects on current-driven vortex domain wall mobilitycitations
- 2013A numerical approach to incorporate intrinsic material defects in micromagnetic simulations
- 2013Influence of disorder on vortex domain wall mobility in magnetic nanowires
Places of action
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article
Barkhausen noise in disordered striplike ferromagnets
Abstract
<p>In this work, we present a systematic comparison of the results obtained from the low-frequency Barkhausen noise recordings in nanocrystalline samples with those from the numerical simulations of the random-field Ising model systems. We performed measurements at room temperature on a field-driven metallic glass stripe made of VITROPERM 800 R, a nanocrystalline iron-based material with an excellent combination of soft and magnetic properties, making it a cutting-edge material for a wide range of applications. Given that the Barkhausen noise emissions emerging along a hysteresis curve are stochastic and depend in general on a variety of factors (such as distribution of disorder due to impurities or defects, varied size of crystal grains, type of domain structure, driving rate of the external magnetic field, sample shape and temperature, etc.), adequate theoretical modeling is essential for their interpretation and prediction. Here the Random field Ising model, specifically its athermal nonequilibrium version with the finite driving rate, stands out as an appropriate choice due to the material's nanocrystalline structure and high Curie temperature. We performed a systematic analysis of the signal properties and magnetization avalanches comparing the outcomes of the numerical model and experiments carried out in a two-decade-wide range of the external magnetic field driving rates. Our results reveal that with a suitable choice of parameters, a considerable match with the experimental results is achieved, indicating that this model can accurately describe the Barkhausen noise features in nanocrystalline samples.</p>