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Quantitative X-ray powder diffraction and the illite polytype analysis method for direct fault rock dating: A comparison of analytical techniques

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Boles,  Austin
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Schleicher,  Anja Maria
3.1 Inorganic and Isotope Geochemistry, 3.0 Geochemistry, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Solum,  John
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van der Pluijm,  Ben
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Boles, A., Schleicher, A. M., Solum, J., van der Pluijm, B. (2018): Quantitative X-ray powder diffraction and the illite polytype analysis method for direct fault rock dating: A comparison of analytical techniques. - Clays and Clay Minerals, 66, 3, 220-232.
https://doi.org/10.1346/CCMN.2018.064093


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_3430891
Abstract
This study presents a comparison of three quantitative X-ray powder diffraction (Q-XRPD) methodologies for illite polytype quantification for the practical application of directly dating clay-rich fault rocks and constraining the provenance of deformation-related fluids in clay-rich brittle rocks of the upper crust. These methods are WILDFIRE© modeling, End-member Standards Matching and Rietveld whole-pattern matching (BGMN®). Each technique was applied to a suite of synthetic mixtures of known composition as well as to a sample of natural clay gouge. Analytical uncertainty achieved for these synthetic samples using WILDFIRE© modeling, End-member Standards Matching, and Rietveld methods were ±4-5%, ±1%, and ±6%, respectively, with the caveat that the end-member clay mineral used for matching was the exact mineral used in the test mixture. Grain size aliquots of the gouge were additionally investigated by Transmission Electron Microscopy (TEM) for polytypism, 22 as well as laser particle size analysis for grain size distributions. The three analytical techniques produce similar 40Ar/3923 Ar ages of authigenesis after unmixing, indicating that any of the methods can be used to directly date fault-related authigenic illite formation. Descriptions are included for pre-calculated WILDFIRE© illite polytype diffractogram libraries, fitting model end-members to experimental data with a least-squares algorithm, and mixing spreadsheet programs for end-member natural standards matching.