JpGU-AGU Joint Meeting 2020

講演情報

[J] 口頭発表

セッション記号 S (固体地球科学) » S-EM 固体地球電磁気学

[S-EM18] Paleomagnetism and rock magnetism applied to solving geological and geophysical problems

コンビーナ:Martin Chadima(Institute of Geology of the Czech Academy of Sciences)、Balazs Bradak(神戸大学)、Daniel Pastor-Galan(Center for North East Asian Studies, Tohoku University)、Myriam Annie Claire Kars(Center for Advanced Marine Core Research)

[SEM18-09] Assessment of magnetic techniques for understanding complex mixtures of magnetite and hematite: the Inuyama red chert

*Pengxiang Hu1,2Hirokuni Oda1Xiang Zhao2Richard Harrison3David Heslop2Tetsuro Sato1Adrian Muxworthy4Andrew Roberts2 (1.AIST、2.ANU、3.University of Cambridge、4.Imperial College London)

キーワード:Red chert, Hematite, Rock magnetism

Magnetite and hematite mixtures occur widely in nature. Magnetic unmixing of the signals recorded by these minerals can be important for assessing the origin of their respective paleomagnetic remanences and for extracting geological and paleoenvironmental information. However, unmixing magnetic signals from complex magnetite and hematite mixtures is difficult because of the weak magnetization and high coercivity of hematite. We assess here the relative effectiveness of first-order reversal curve (FORC) and extended FORC-type diagrams, FORC principal component analysis (PCA), isothermal remanent magnetization (IRM) curve decomposition, and PCA of hysteresis loops and remanent hysteretic curves for unmixing magnetic components in samples from the magnetically complex Inuyama red chert from Japan. We also further characterize the domain state and coercivity distributions of both magnetite and hematite with FORC-PCA and IRM acquisition analysis in the red chert. We show that end member identification from IRM curve decomposition can provide valuable component-specific information linked to coercivity, while FORC-PCA enables effective magnetic domain state identification. To identify components in complex magnetite and hematite mixtures, we recommend PCA analysis of hysteresis loops combined with FORC analysis of representative samples to identify domain states and coercivity distributions.