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

Micromagnetic tomography (MMT) is a technique that combines X‐ray micro computed tomography and scanning magnetometry data to obtain information about the magnetic potential of individual grains embedded in a sample. Recovering magnetic signals of individual grains in natural and synthetic samples p...

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Autores principales: Cortés‐Ortuño, David, Fabian, Karl, de Groot, Lennart V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286423/
https://www.ncbi.nlm.nih.gov/pubmed/35865147
http://dx.doi.org/10.1029/2022JB024234
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author Cortés‐Ortuño, David
Fabian, Karl
de Groot, Lennart V.
author_facet Cortés‐Ortuño, David
Fabian, Karl
de Groot, Lennart V.
author_sort Cortés‐Ortuño, David
collection PubMed
description Micromagnetic tomography (MMT) is a technique that combines X‐ray micro computed tomography and scanning magnetometry data to obtain information about the magnetic potential of individual grains embedded in a sample. Recovering magnetic signals of individual grains in natural and synthetic samples provides a new pathway to study the remanent magnetization that carries information about the ancient geomagnetic field and is the basis of all paleomagnetic studies. MMT infers the magnetic potential of individual grains by numerical inversion of surface magnetic measurements using spherical harmonic expansions. The magnetic potential of individual particles in principle is uniquely determined by MMT, not only by the dipole approximation, but also more complex, higher order, multipole moments. Here, we show that such complex magnetic information together with both particle shape and mineral properties severely constrains the internal magnetization structure of an individual grain. To this end, we apply a three dimensional micromagnetic model to predict the multipole signal from magnetization states of different local energy minima. We show that for certain grains it is even possible to uniquely infer the magnetic configuration from the inverted magnetic multipole moments. This result is crucial to discriminate single‐domain particles from grains in more complex configurations such as multi‐domain or vortex states. As a consequence, our investigation proves that by MMT it is feasible to select statistical ensembles of magnetic grains based on their magnetization states, which opens new possibilities to identify and characterize stable paleomagnetic recorders in natural samples.
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spelling pubmed-92864232022-07-19 Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models Cortés‐Ortuño, David Fabian, Karl de Groot, Lennart V. J Geophys Res Solid Earth Research Article Micromagnetic tomography (MMT) is a technique that combines X‐ray micro computed tomography and scanning magnetometry data to obtain information about the magnetic potential of individual grains embedded in a sample. Recovering magnetic signals of individual grains in natural and synthetic samples provides a new pathway to study the remanent magnetization that carries information about the ancient geomagnetic field and is the basis of all paleomagnetic studies. MMT infers the magnetic potential of individual grains by numerical inversion of surface magnetic measurements using spherical harmonic expansions. The magnetic potential of individual particles in principle is uniquely determined by MMT, not only by the dipole approximation, but also more complex, higher order, multipole moments. Here, we show that such complex magnetic information together with both particle shape and mineral properties severely constrains the internal magnetization structure of an individual grain. To this end, we apply a three dimensional micromagnetic model to predict the multipole signal from magnetization states of different local energy minima. We show that for certain grains it is even possible to uniquely infer the magnetic configuration from the inverted magnetic multipole moments. This result is crucial to discriminate single‐domain particles from grains in more complex configurations such as multi‐domain or vortex states. As a consequence, our investigation proves that by MMT it is feasible to select statistical ensembles of magnetic grains based on their magnetization states, which opens new possibilities to identify and characterize stable paleomagnetic recorders in natural samples. John Wiley and Sons Inc. 2022-05-23 2022-05 /pmc/articles/PMC9286423/ /pubmed/35865147 http://dx.doi.org/10.1029/2022JB024234 Text en © 2022 The Authors. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Article
Cortés‐Ortuño, David
Fabian, Karl
de Groot, Lennart V.
Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
title Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
title_full Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
title_fullStr Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
title_full_unstemmed Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
title_short Mapping Magnetic Signals of Individual Magnetite Grains to Their Internal Magnetic Configurations Using Micromagnetic Models
title_sort mapping magnetic signals of individual magnetite grains to their internal magnetic configurations using micromagnetic models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286423/
https://www.ncbi.nlm.nih.gov/pubmed/35865147
http://dx.doi.org/10.1029/2022JB024234
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