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Deconvolution of the composition of fine-grained pyrite in sedimentary matrix by regression of time-resolved LA-ICP-MS data

Citation

Stepanov, AS and Danyushevsky, LV and Large, RR and Mukherjee, I and Zhukova, IA, Deconvolution of the composition of fine-grained pyrite in sedimentary matrix by regression of time-resolved LA-ICP-MS data, American Mineralogist, 105, (6) pp. 820-832. ISSN 0003-004X (2020) [Refereed Article]

Copyright Statement

Copyright 2020 Mineralogical Society of America

DOI: doi:10.2138/am-2020-7202

Abstract

Pyrite is a common mineral in sedimentary rocks and is the major host for many chalcophile trace elements utilized as important tracers of the evolution of the ancient hydrosphere. Measurement of trace element composition of pyrite in sedimentary rocks is challenging due to fine-grain size and intergrowth with silicate matrix and other sulfide minerals. In this contribution, we describe a method for calculation of trace element composition of sedimentary pyrite from time-resolved LA-ICP-MS data. The method involves an analysis of both pyrite and pyrite-free sediment matrix, segmentation of LA-ICP-MS spectra, normalization to total, regression analysis of dependencies between the elements, and calculation of normalized composition of the mineral. Sulfur is chosen as an explanatory variable, relative to which all regressions are calculated. The S content value used for calculation of element concentrations from the regressions is calculated from the total, eliminating the need for independent constraints. The algorithm allows efficient measurement of concentrations of multiple chalcophile trace elements in pyrite in a wide range of samples, including quantification of detection limits and uncertainties while excluding operator bias. The data suggest that the main sources of uncertainties in pyrite composition are sample heterogeneity and counting statistics for elements of low abundance. The analysis of regression data of time-resolved LA-ICP-MS measurements could provide new insights into the geochemistry of the sedimentary rocks and minerals. It allows quantification of ratios of elements that do not have reference material available (such as Hg) and provides estimates on the content of non-sulfidic Fe in the silicate matrix. Regression analysis of the mixed LA-ICP-MS signal could be a powerful technique for deconvolution of phase compositions in complex multicomponent samples.

Item Details

Item Type:Refereed Article
Keywords:pyrite, LA-ICPMS, gression, detection limits, analytical geochemistry, chalcophile elements, paleo-ocean proxy, understanding paleo-ocean proxies, insights from in situ analyses
Research Division:Earth Sciences
Research Group:Geology
Research Field:Mineralogy and crystallography
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the earth sciences
UTAS Author:Stepanov, AS (Mr Sasha Stepanov)
UTAS Author:Danyushevsky, LV (Professor Leonid Danyushevsky)
UTAS Author:Large, RR (Professor Ross Large)
UTAS Author:Mukherjee, I (Dr Indrani Mukherjee)
UTAS Author:Zhukova, IA (Ms Irina Zhukova)
ID Code:144700
Year Published:2020
Funding Support:Australian Research Council (IH130200004)
Web of Science® Times Cited:3
Deposited By:CODES ARC
Deposited On:2021-06-06
Last Modified:2021-07-28
Downloads:0

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