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.
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
2000
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), .
(doi:10.1029/2000JB900326).
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.
This record has no associated files available for download.
More information
Published date: 2000
Identifiers
Local EPrints ID: 1269
URI: http://eprints.soton.ac.uk/id/eprint/1269
ISSN: 0148-0227
PURE UUID: 332bf1a3-ebf3-4dbf-be45-bffbeeb900bb
Catalogue record
Date deposited: 07 Apr 2004
Last modified: 15 Mar 2024 04:42
Export record
Altmetrics
Contributors
Author:
A.P. Roberts
Author:
C.R. Pike
Author:
K.L. Verosub
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics