journal article·2023-04

FORC diagram features of Co particles due to reversal by domain nucleation

Leoni Breth, Johann Fischbacher, Alexander Kovacs, Harald Oezelt, Thomas Schrefl, Hubert Brueckl, Christoph Czettl, Saskia Kührer, Julia Pachlhofer, Maria Schwarz

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Abstract

First Order Reversal Curve (FORC) diagrams are a popular tool in geophysics and materials science for the characterization of magnetic particles of natural and synthetic origin. However, there is still a lot of controversy about the rigorous interpretation of the origin of certain features in a FORC diagram. In this study, we analyze FORCs computed by micromagnetic simulations of Co cubes with dimensions of 50, 100 and 150 nm and uniaxial magnetocrystalline anisotropy. For the larger cubes we observe the formation of a stable two-domain state. The nucleation of a reversed domain and its subsequent annihilation are clearly visible as separate peaks in the FORC diagram. They spread out along the coordinate axis in the FORC diagram, which is associated with the bias field $H_U$ of a Preisach hysteron. Based on our findings, we state that a FORC diagram peak spreading along the $H_U$ axis can have its origin in the step-wise magnetization reversal driven by nucleation of domains in a single particle. This means that we have identified another mechanism apart from the well-known magnetostatic interaction between a set of particles that leads to features in the FORC diagram extending along the $H_U$-axis. Our study demonstrates that if FORCs shall be used as a quantitative tool to assess the microstructure of samples containing magnetic material, more information from other methods will be required to identify the correct physical mechanism by which a certain "fingerprint" in a FORC diagram is produced.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Magnetic Properties and Applications · Geomagnetism and Paleomagnetism Studies · Magnetic properties of thin films

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References (36)

Show source-provided references
1. In situ magnetic identification of giant, needle-shaped magnetofossils in Paleocene–Eocene Thermal Maximum sediments10.1073/pnas.2018169118 ↗
2. Introduction to ’Magnetic iron minerals in sediments and their relation to geologic processes, climate, and the geomagnetic field’10.1016/j.gloplacha.2013.10.009 ↗
3. Extracting the intrinsic switching field distribution in perpendicular media: A comparative analysis10.1063/1.2176598 ↗
4. Cemented carbide microstructures: a review10.1016/j.ijrmhm.2018.12.004 ↗
5. An observation of the binder microstructure in WC-(Co+Ru) cemented carbides using transmission Kikuchi diffraction10.1016/j.scriptamat.2020.03.010 ↗
6. Mathematical models of hysteresis10.1109/TMAG.1986.1064347 ↗
7. Über die magnetische Nachwirkung10.1007/BF01349418 ↗
8. Analysis and simulations of magnetic materials
9. Effect of interaction on the magnetization of single-domain particles10.1109/TAU.1966.1161852 ↗
10. On the Preisach function of ferromagnetic hysteresis10.1063/1.338563 ↗
11. Generalized Preisach model of hysteresis10.1109/20.43892 ↗
12. Magnetic characterization of geologic materials with first-order reversal curves
13. Characterizing interactions in fine magnetic particle systems using first order reversal curves10.1063/1.370176 ↗
14. First-order reversal curve diagram analysis of a perpendicular nickel nanopillar array10.1103/PhysRevB.71.134407 ↗
15. Micromagnetic behavior of electrodeposited cylinder arrays10.1103/PhysRevB.65.144417 ↗
16. From nano to micro: evolution of magnetic domain structures in multidomain magnetite10.1029/2019GC008319 ↗
17. Nonlinear conjugate gradient methods in micromagnetics10.1063/1.4981902 ↗
18. Numerical methods in micromagnetics (finite element method)
19. Magnetic microstructure machine learning analysis
20. Micromagnetism
21. FORCinel: An improved algorithm for calculating first-order reversal curve distributions using locally weighted regression smoothing10.1029/2008GC001987 ↗
22. VARIFORC: An optimized protocol for calculating non-regular first-order reversal curve (FORC) diagrams10.1016/j.gloplacha.2013.08.003 ↗
23. Magnetic domain state diagnosis using hysteresis reversal curves10.1002/2016JB013683 ↗
24. Avoiding the zero-coercivity anomaly in first order reversal curves: FORC+10.1063/1.5080101 ↗
25. Waiting for forcot: accelerating FORC processing 100× using a fast-fourier-transform algorithm10.1029/2019GC008380 ↗
26. doFORC tool for calculating first-order reversal curve diagrams of noisy scattered data10.1063/1.5066445 ↗
27. An investigation of magnetic reversal in submicron-scale Co dots using first order reversal curve diagrams10.1063/1.370177 ↗
28. Magnetic states of small cubic particles with uniaxial anisotropy10.1016/S0304-8853(98)00328-X ↗
29. Interpreting first-order reversal curves beyond the Preisach model: An experimental permalloy microarray investigation10.1103/PhysRevB.99.064401 ↗
30. Influence of magnetostatic interactions on first-order-reversal-curve (FORC) diagrams: a micromagnetic approach10.1111/j.1365-246X.2004.02358.x ↗
31. Micromagnetic and Preisach analysis of the First Order Reversal Curves (FORC) diagram10.1063/1.1557656 ↗
32. An investigation of multi-domain hysteresis mechanisms using FORC diagrams10.1016/S0031-9201(01)00241-2 ↗
33. Preisach diagrams and anhysteresis: do they measure interactions?10.1016/0031-9201(90)90076-A ↗
34. The vortex state in geologic materials: a micromagnetic perspective10.1029/2018JB015909 ↗
35. Resolving the origin of pseudo-single domain magnetic behavior10.1002/2017JB014860 ↗
36. Micromagnetic modeling of first-order reversal curve (FORC) diagrams for single-domain and pseudo-single-domain magnetite10.1016/S0012-821X(03)00320-0 ↗