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First-order reversal curve diagrams: a new tool for characterizing the magnetic properties of natural samples

First-order reversal curve diagrams: a new tool for characterizing the magnetic properties of natural samples
First-order reversal curve diagrams: a new tool for characterizing the magnetic properties of natural samples
Paleomagnetic and environmental magnetic studies are commonly conducted on samples containing mixtures of magnetic minerals and/or grain sizes. Major hysteresis loops are routinely used to provide information about variations in magnetic mineralogy and grain size. Standard hysteresis parameters, however, provide a measure of the bulk magnetic properties, rather than enabling discrimination between the magnetic components that contribute to the magnetization of a sample. By contrast, first-order reversal curve (FORC) diagrams, which we describe here, can be used to identify and discriminate between the different components in a mixed magnetic mineral assemblage. We use magnetization data from a class of partial hysteresis curves known as first-order reversal curves (FORCs) and transform the data into contour plots (FORC diagrams) of a two-dimensional distribution function. The FORC distribution provides information about particle switching fields and local interaction fields for the assemblage of magnetic particles within a sample. Superparamagnetic, single-domain, and multidomain grains, as well as magnetostatic interactions, all produce characteristic and distinct manifestations on a FORC diagram. Our results indicate that FORC diagrams can be used to characterize a wide range of natural samples and that they provide more detailed information about the magnetic particles in a sample than standard interpretational schemes which employ hysteresis data. It will be necessary to further develop the technique to enable a more quantitative interpretation of magnetic assemblages; however, even qualitative interpretation of FORC diagrams removes many of the ambiguities that are inherent to hysteresis data.
0148-0227
28461-28475
Roberts, A.P.
4497b436-ef02-428d-a46e-65a22094ba52
Pike, C.R.
a04aa087-b7b8-483b-9c2d-36c748a8c2c3
Verosub, K.L.
71b9c710-71e8-4579-b6c8-5f19c5b1f8f3
Roberts, A.P.
4497b436-ef02-428d-a46e-65a22094ba52
Pike, C.R.
a04aa087-b7b8-483b-9c2d-36c748a8c2c3
Verosub, K.L.
71b9c710-71e8-4579-b6c8-5f19c5b1f8f3

Roberts, A.P., Pike, C.R. and Verosub, K.L. (2000) First-order reversal curve diagrams: a new tool for characterizing the magnetic properties of natural samples. Journal of Geophysical Research, 105 (B12), 28461-28475. (doi:10.1029/2000JB900326).

Record type: Article

Abstract

Paleomagnetic and environmental magnetic studies are commonly conducted on samples containing mixtures of magnetic minerals and/or grain sizes. Major hysteresis loops are routinely used to provide information about variations in magnetic mineralogy and grain size. Standard hysteresis parameters, however, provide a measure of the bulk magnetic properties, rather than enabling discrimination between the magnetic components that contribute to the magnetization of a sample. By contrast, first-order reversal curve (FORC) diagrams, which we describe here, can be used to identify and discriminate between the different components in a mixed magnetic mineral assemblage. We use magnetization data from a class of partial hysteresis curves known as first-order reversal curves (FORCs) and transform the data into contour plots (FORC diagrams) of a two-dimensional distribution function. The FORC distribution provides information about particle switching fields and local interaction fields for the assemblage of magnetic particles within a sample. Superparamagnetic, single-domain, and multidomain grains, as well as magnetostatic interactions, all produce characteristic and distinct manifestations on a FORC diagram. Our results indicate that FORC diagrams can be used to characterize a wide range of natural samples and that they provide more detailed information about the magnetic particles in a sample than standard interpretational schemes which employ hysteresis data. It will be necessary to further develop the technique to enable a more quantitative interpretation of magnetic assemblages; however, even qualitative interpretation of FORC diagrams removes many of the ambiguities that are inherent to hysteresis data.

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Published date: 2000

Identifiers

Local EPrints ID: 1269
URI: https://eprints.soton.ac.uk/id/eprint/1269
ISSN: 0148-0227
PURE UUID: 332bf1a3-ebf3-4dbf-be45-bffbeeb900bb

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Date deposited: 07 Apr 2004
Last modified: 17 Jul 2017 17:17

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Contributors

Author: A.P. Roberts
Author: C.R. Pike
Author: K.L. Verosub

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