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

TLDR

Paleomagnetic studies on mixed magnetic mineral samples typically rely on bulk hysteresis loops, which reveal overall magnetic properties but cannot distinguish individual mineral components. This study introduces first‑order reversal curve (FORC) diagrams as a tool to identify and discriminate the distinct magnetic components within a mixed assemblage. FORC data are collected from partial hysteresis curves and transformed into two‑dimensional contour plots that map particle switching and interaction fields. FORC diagrams characterize a wide range of natural samples, offering more detailed information than standard hysteresis analysis and reducing ambiguities, though quantitative interpretation still requires further development.

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.