Intrinsic paleointensity bias and the long-term history of the geodynamo

Abstract

A key mechanism responsible for a systematic bias in the global geomagnetic paleointensity database.

Influence of static alternating field demagnetization on anisotropy of magnetic susceptibility: Experiments and implications

“…Low-temperature demagnetization appears to be unable to fully remove the effects of a previous AFimpressed anisotropy. This observation is consistent with findings by Smirnov et al [2017], who state that LTD can be inefficient if grains are oxidized, or due to pinning of walls at exsolution boundaries or lattice defects.…”

“…This observation is consistent with findings by Smirnov et al . [], who state that LTD can be inefficient if grains are oxidized, or due to pinning of walls at exsolution boundaries or lattice defects.…”

Analysis of an Updated Paleointensity Database (QPI‐PINT) for 65–200 Ma: Implications for the Long‐Term History of Dipole Moment Through the Mesozoic

“…The MD criterion addresses a fundamental requirement of the Thellier method that the paleointensity signal should ideally be carried by noninteracting single‐domain magnetic grains. The presence of strong interactions and/or multidomain‐like behavior of magnetic grains results in nonlinear Arai plots leading to an intrinsic paleointensity bias that becomes more significant with the increasing grain size (Levi, ; Paterson, ; Smirnov et al, ; Xu & Dunlop, ). We have assigned MD = 1 if the absence of a significant MD bias was explicitly demonstrated by the pTRM‐tail check (Riisager & Riisager, ) and/or the Thellier‐IZZI (Tauxe & Staudigel, ) procedures.…”

Thermoremanent Behavior in Synthetic Samples Containing Natural Oxyexsolved Titanomagnetite

“…The lower temperature section of an Arai plot is commonly used to avoid nonideal behavior that might be caused by alteration at higher temperatures (i.e., Kosterov & Prevot, 1998), but more recent work, e.g., Biggin (2010) and Smirnov et al (2017) has shown that using the low-temperature portion of a concave-up Arai plot from a Thellier-style experiment can lead to large PI overestimations. The lower temperature section of an Arai plot is commonly used to avoid nonideal behavior that might be caused by alteration at higher temperatures (i.e., Kosterov & Prevot, 1998), but more recent work, e.g., Biggin (2010) and Smirnov et al (2017) has shown that using the low-temperature portion of a concave-up Arai plot from a Thellier-style experiment can lead to large PI overestimations.…”

“…Natural samples containing grains comparable to the oxyexsolved sample set used here are commonly used in PI experiments, which means that nonideal behavior could cause overestimations in absolute PI values. The lower temperature section of an Arai plot is commonly used to avoid nonideal behavior that might be caused by alteration at higher temperatures (i.e., Kosterov & Prevot, 1998), but more recent work, e.g., Biggin (2010) and Smirnov et al (2017) has shown that using the low-temperature portion of a concave-up Arai plot from a Thellier-style experiment can lead to large PI overestimations. These experiments indicate that the majority of the nonideal behavior occurs in the low-temperature portion of the Arai plot.…”