Time‐Asymmetric FORC Diagrams: A New Protocol for Visualizing Thermal Fluctuations and Distinguishing Magnetic Mineral Mixtures

Abstract

First‐order reversal curves (FORCs) are nowadays routinely used to assess domain states and magnetostatic interactions of magnetic minerals. While a huge step forward from bulk magnetic measurements in terms of sample characterization, there is a missing link between the FORC diagrams and remanence behavior: FORC diagrams mainly reveal domain states, while remanence behavior is largely controlled by thermal activations. We present a new tool to visualize thermal fluctuations in so‐called time‐asymmetric (TA) FORC diagrams. TA‐FORCs differ from traditional FORCs in that they maintain the reversal field Ha for a longer time (minutes) than the FORC measurement field Hb (milliseconds). During this extended hold time, thermal activations cause some magnetic grains to change their magnetization, giving rise to an upward shift in the FORC diagram. The magnitude of this shift gives insight into the thermoviscous stability of the mineral and its remanence acquisition behavior. This not only allows to distinguish thermoviscous effects in FORC diagrams from magnetostatic (i.e., interactions/domain state related) effects but also provides a way to separate mixtures of magnetic minerals: two minerals with similar coercivity spectra that would totally overlap in traditional FORC diagrams show different upward shifts in TA‐FORC diagrams, which in some cases enable complete separation of the minerals visually. This effectively provides two independent FORC signatures for two magnetic constituents in a sample such as two grain populations of different grain sizes, grain shapes, and/or mineral.

Key Signatures of Magnetofossils Elucidated by Mutant Magnetotactic Bacteria and Micromagnetic Calculations

“…The large energy barrier generated by axial magnetostatic interactions ensures that field-induced transitions between the two stable states of single-stranded chains occur in proximity of the theoretical switching fields predicted by micromagnetic models that neglect thermal activations, such as the one used here and those of Harrison and Lascu (2014) and Berndt et al (2020) . Nevertheless, thermal activations are still sufficiently large to produce a measurable vertical offset of the central ridge ( Egli, 2013 , 2021 ), due to the intrinsic time asymmetry of the FORC measurement protocol ( Berndt et al, 2018 ). The central ridge offset of high-resolution FORC measurements of magnetofossil-rich sediments, which is of the order of 0.3–0.5 mT ( Egli et al, 2010 ; Ludwig et al, 2013 ; Wagner et al, 2021 ), can be explained by a Stoner-Wohlfarth model of thermally activated UNISD particles ( Berndt et al, 2018 ; Lanci & Kent, 2018 ) with β 0 ≈ 400–600.…”

“…Each of these criteria, if taken singularly, is fulfilled by an equivalent assemblage of isolated SD particles with appropriated equivalent anisotropy, but all known natural examples other than magnetofossils do not fulfill all of them. For instance, titanomagnetite needles in the Tiva Canyon Tuff do possess a central ridge (Berndt et al, 2018), but the associated coercivity distribution and vertical offset Ludwig et al, 2013). (b) FORC diagram of a simulated composite obtained from the six micromagnetically modeled chain structures, with the following relative contributions to the saturation magnetization, chosen for a visual match with the FORC diagram in (a): 1/3 single-stranded chains of equant magnetosomes, 1/6 single-stranded chains of prismatic magnetosomes, 1/3 native double-stranded chains of equant magnetosomes, 1/6 native double-stranded chains of prismatic magnetosomes, 1/3 fold-collapsed chains of equant magnetosomes, 1/6 fold-collapsed chains of prismatic magnetosomes.…”

In situ magnetic identification of giant, needle-shaped magnetofossils in Paleocene–Eocene Thermal Maximum sediments

“…The isolated central ridge of the WL35950b FORC diagram is characterized by a small, B c -dependent vertical offset δB u (dashed line in Fig. 1E) caused by the effect of thermal activations on the switching field (B sw ) of single-domain particles (34). Larger offsets are caused by smaller energy barriers which, in magnetite, correspond to smaller blocking volumes.…”

“…More time is effectively spent at B r than near −B r , which requires a slightly larger field B = −B r + ΔB fluc to switch all particles back to positive saturation. ΔB fluc is the difference between fluctuation fields for thermally assisted switching at ±B r (34,48).…”

Waiting for Forcot: Accelerating FORC Processing 100× Using a Fast‐Fourier‐Transform Algorithm

“…Looking into the future, processing and/or analyzing FORC diagrams in Fourier space, as opposed to ( H a , H b ) space may have advantages for further new applications such as FORC‐FFT‐PCA (Lascu et al, ), or quantitative analysis of time‐asymmetric (TA) FORC diagrams (Berndt et al, ): In FFT space, the position of a FORC distribution peak is represented by phase angles, its intensity by magnitudes. For FORC‐PCA, for example, end‐members with variable coercivity‐peaks could be detected, for example, a biogenic end‐member with a characteristic central‐ridge signature and a detrital end‐member with a characteristic vortex/multi‐domain signature, even when both components show some variations in coercivity throughout a core.…”