Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models

Cortés‐Ortuño, David; Fabian, Karl; Groot, Lennart de

doi:10.1029/2022jb024234

Cited by 5 publications

(8 citation statements)

References 43 publications

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“…Cortés‐Ortuño et al. (2022) showed that PSD state particles present more accurate inversion results when considering the non‐dipolar components for small sample‐sensor distances (<1 μm). For larger sensor distances, the dipole as approximations are remarkably accurate, as the higher‐order moments decay rapidly with distance and therefore have less influence on the particle's magnetic signal.…”

Section: Discussionmentioning

confidence: 99%

Full Vector Inversion of Magnetic Microscopy Images Using Euler Deconvolution as Prior Information

Souza‐Junior,

Uieda,

Trindade

et al. 2024

Geochem Geophys Geosyst

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Paleomagnetic data is collected from bulk samples, containing a mixture of stable and unstable magnetic particles. Recently, magnetic microscopy techniques have allowed the examination of individual magnetic grains. However, accurately determining the magnetic moments of these grains is difficult and time‐consuming due to the inherent ambiguity of the data and the large number of grains in each image. Here we introduce a fast and semi‐automated algorithm that estimates the position and magnetization of dipolar sources solely based on the magnetic microscopy data. The algorithm follows a three‐step process: (a) employ image processing techniques to identify and isolate data windows for each magnetic source; (b) use Euler Deconvolution to estimate the position of each source; (c) solve a linear inverse problem to estimate the dipole moment of each source. To validate the algorithm, we conducted synthetic data tests, including varying particle concentrations and non‐dipolarity. The tests show that our method is able to accurately recover the position and dipole moment of particles that are at least 15 μm apart for a source‐sensor separation of 5 μm. For grain concentrations of 6,250 grains/mm3, our method is able to detect over 60% of the particles present in the data. We applied the method to real data of a speleothem sample, where it accurately retrieved the expected directions induced in the sample. The semi‐automated nature of our algorithm, combined with its low processing cost and ability to determine the magnetic moments of numerous particles, represents a significant advancement in facilitating paleomagnetic applications of magnetic microscopy.

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Section: Discussionmentioning

confidence: 99%

Full Vector Inversion of Magnetic Microscopy Images Using Euler Deconvolution as Prior Information

Souza‐Junior,

Uieda,

Trindade

et al. 2024

Geochem Geophys Geosyst

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“…Therefore the application of the proposed algorithm to natural samples should fail for those PSD particles. Cortés-Ortuño et al (2022) give important insights about the matter, they showed that PSD state particles present more accurate inversion results when considering the non-dipole components for small sample-sensor distances (<1 𝜇m), but for larger sensor distances the dipole as approximations are remarkably accurate, as the higher-order moments decay rapidly with distance and therefore have less influence on the particle's magnetic signal. Thus, our approach can be considered reasonable to work with both particle SD and PSD states signals.…”

Section: Reliability Of Dipole Moment Approximationmentioning

confidence: 99%

“…In order to apply magnetic microscopy to paleomagnetic studies, it is necessary to recover from the magnetic images a large number of individual magnetic moments, corresponding to at least tens of thousands of stable fine-grained grains (< 1 µm), in order to provide statistical significance to the remanence vector (e.g., Berndt et al, 2016). Nowadays, with the development of magnetic microscopy techniques, this task is no longer limited by the resolution of magnetic microscopes (de Groot et al, 2018;Fu et al, 2020;Glenn et al, 2017;Lima et al, 2014;Weiss et al, 2007), but essentially by the intrinsic problem presented by the ambiguity in the inversion of potential field data (Barbosa and Silva, 2011;de Groot et al, 2021;Oliveira Jr. et al, 2015), and ultimately by the lack of a fast and automated way to recover such a large number of individual magnetic moments from a set of magnetic images (Cortés-Ortuño et al, 2022;Lima and Weiss, 2009;Lima et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…This can be obtained, for example, from X-ray computed tomography (microCT; de Groot et al, , 2018Fabian and de Groot, 2019). Nonetheless, the standard microCT techniques do not provide adequate resolution to resolve the finer and more stable magnetic grains (Cortés-Ortuño et al, 2022;de Groot et al, 2021), whereas other more sophisticated techniques such as ptychographic X-ray tomography (e.g., Maldanis et al, 2020) are not readily available and too time-consuming to be routinely used in paleomagnetic studies.…”

Section: Introductionmentioning

confidence: 99%

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Full vector inversion of magnetic microscopy images using Euler deconvolution as a priori information

Souza¹,

Uieda²,

Trindade³

et al. 2023

Preprint

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Paleomagnetic data are usually obtained from whole cylindric samples, where the signal results from the sum of magnetic moments from hundreds of thousands to millions of magnetic particles within the sample volume. This usually includes both stable and unstable remanence carriers.Recently, magnetic microscopy techniques allowed the investigation of individual grains by directly imaging their magnetic field. However, the determination of the magnetic moments of individual grains is hindered by the intrinsic ambiguity in the inversion of potential field data, as well as by the large number of grains found in any one microscopy image. We present a fast, semi-automated algorithm capable of estimating the position and magnetization of each ferromagnetic (l.s) source using only the magnetic microscopy data. Our algorithm works in three steps: (i) we first apply image processing techniques to identify and isolate data window boundaries for each source; (ii) with these window boundaries, the position of the sources is estimated using Euler deconvolution; and finally (iii) using the position information, the algorithm is able to estimate the magnetic dipole moment direction and intensity for each source through an overdetermined linear inverse problem using a dipolar approximation. The method does not require any type of additional information about the sample or the sources. Sensitivity tests were run to estimate the stability of our routine to the depth of particles, signal-to-noise ratio, and non-dipolarity of the sources. Tests with simple synthetic data show the high effectiveness of the methodology for recovering the position and magnetic information for both dipolar and non-dipolar sources. More complex synthetic data including over 100 different magnetic particles were devised to emulate real rock data. Results obtained on these data also show the feasibility and robustness of the algorithm to semi-automatically estimate the position and magnetic moment of a large number of particles. This is further confirmed through an application to real data in which we are able to retrieve the expected bimodal isothermal remanent directions that were induced in the sample. Given its semi-automatic nature, its low processing cost, and the possibility of simultaneous inversion of the magnetic moment of a great number of magnetic particles, the methodology here proposed is a step forward in enabling paleomagnetic applications of magnetic microscopy.

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“…Although these individual point sources very rarely correspond to the actual magnetization distribution within a magnetic material producing the measured magnetic field, they possess useful mathematical properties and can sometimes be related to physical quantities of interest [see, for instance, Cortes‐Ortuno et al. (2021, 2022) for an application of low‐order multipoles to constrain the internal magnetization structure of magnetic grains analyzed with micromagnetic tomography]. Two drawbacks of multipole expansions are that (a) multipoles with orders higher than that of a dipole are strongly dependent on the location of the origin, making their physical interpretation challenging (Lowes, 1994), and (b) multipoles are inefficient for representing extended sources, especially those with asymmetrical dimensions, because a very large number of terms is required to adequately reproduce the magnetic field of such source configurations.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Net Magnetic Moment of Geological Samples From Planar Field Maps Using Multipoles

Lima

Weiss

Borlina

et al. 2023

Geochem Geophys Geosyst

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Recent advances in magnetic microscopy have enabled studies of geological samples whose weak and spatially nonuniform magnetizations were previously inaccessible to standard magnetometry techniques. A quantity of central importance is the net magnetic moment, which reflects the mean direction and the intensity of the magnetization states of numerous ferromagnetic crystals within a certain volume. The planar arrangement of typical magnetic microscopy measurements, which originates from measuring the field immediately above the polished surface of a sample to maximize sensitivity and spatial resolution, makes estimating net moments considerably more challenging than with spherically distributed data. In particular, spatially extended and nonuniform magnetization distributions often cannot be adequately approximated by a single magnetic dipole. To address this limitation, we developed a multipole fitting technique that can accurately estimate net moment using spherical harmonic multipole expansions computed from planar data. Given that the optimal location for the origin of such expansions is unknown beforehand and generally unconstrained, regularization of this inverse problem is critical for obtaining accurate moment estimates from noisy experimental magnetic data. We characterized the performance of the technique using synthetic sources under different conditions (noiseless data, data corrupted with simulated white noise, and data corrupted with measured instrument noise). We then validated and demonstrated the technique using superconducting quantum interference device microscopy measurements of impact melt spherules from Lonar crater, India and dusty olivine chondrules from the CO chondrite meteorite Dominion Range 08006.

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Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models

Cited by 5 publications

References 43 publications

Full Vector Inversion of Magnetic Microscopy Images Using Euler Deconvolution as Prior Information

Full Vector Inversion of Magnetic Microscopy Images Using Euler Deconvolution as Prior Information

Full vector inversion of magnetic microscopy images using Euler deconvolution as a priori information

Estimating the Net Magnetic Moment of Geological Samples From Planar Field Maps Using Multipoles

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