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An Improved Algorithm for Unmixing First-Order Reversal Curve Diagrams Using Principal Component Analysis

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dc.contributor.author Harrison, Richard J. en
dc.contributor.author Muraszko, Joy en
dc.contributor.author Heslop, David en
dc.contributor.author Lascu, Ioan en
dc.contributor.author Muxworthy, Adrian R. en
dc.contributor.author Roberts, Andrew P. en
dc.date.accessioned 2018-10-12T02:04:25Z
dc.date.available 2018-10-12T02:04:25Z
dc.date.issued 2018
dc.identifier.citation Harrison, Richard J., Muraszko, Joy, Heslop, David, Lascu, Ioan, Muxworthy, Adrian R., and Roberts, Andrew P. 2018. "<a href="https://repository.si.edu/handle/10088/94527">An Improved Algorithm for Unmixing First‐Order Reversal Curve Diagrams Using Principal Component Analysis</a>." <em>Geochemistry, Geophysics, Geosystems</em>. 19 (5):1595&ndash;1610. <a href="https://doi.org/10.1029/2018GC007511">https://doi.org/10.1029/2018GC007511</a> en
dc.identifier.issn 1525-2027
dc.identifier.uri https://hdl.handle.net/10088/94527
dc.description.abstract First-order reversal curve (FORC) diagrams of synthetic binary mixtures with single-domain, vortex state, and multidomain end-members (EMs) were analyzed using principal component analysis (FORC-PCA). Mixing proportions derived from FORC-PCA are shown to deviate systematically from the known weight percent of EMs, which is caused by the lack of reversible magnetization contributions to the FORC distribution. The error in the mixing proportions can be corrected by applying PCA to the raw FORCs, rather than to the processed FORC diagram, thereby capturing both reversible and irreversible contributions to the signal. Here we develop a new practical implementation of the FORC-PCA method that enables quantitative unmixing to be performed routinely on suites of FORC diagrams with up to four distinct EMs. The method provides access not only to the processed FORC diagram of each EM, but also to reconstructed FORCs, which enables objective criteria to be defined that aid identification of physically realistic EMs. We illustrate FORC-PCA with examples of quantitative unmixing of magnetic components that will have widespread applicability in paleomagnetism and environmental magnetism.<br/> <br/> en
dc.relation.ispartof Geochemistry, Geophysics, Geosystems en
dc.title An Improved Algorithm for Unmixing First-Order Reversal Curve Diagrams Using Principal Component Analysis en
dc.type Journal Article en
dc.identifier.srbnumber 148824
dc.identifier.doi 10.1029/2018GC007511
rft.jtitle Geochemistry, Geophysics, Geosystems
rft.volume 19
rft.issue 5
rft.spage 1595
rft.epage 1610
dc.description.SIUnit NH-Mineral Sciences en
dc.description.SIUnit NMNH en
dc.citation.spage 1595
dc.citation.epage 1610

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