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Selenium Concentrations in Twenty‐Six Geological Reference Materials: New Determinations and Proposed Values
Author(s) -
Savard Dany,
Bédard L. Paul,
Barnes SarahJane
Publication year - 2009
Publication title -
geostandards and geoanalytical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.037
H-Index - 73
eISSN - 1751-908X
pISSN - 1639-4488
DOI - 10.1111/j.1751-908x.2009.00003.x
Subject(s) - outlier , reference values , selenium , certified reference materials , standard deviation , base (topology) , mineralogy , statistics , chemistry , mathematics , geology , detection limit , medicine , mathematical analysis , organic chemistry
The interest in selenium concentrations in whole rocks is growing, in part because it is a useful tool for base and precious metal exploration. Selenium is often neglected in whole rock geochemistry because of the inability of most laboratories to make reliable determinations of this element. A consequence of these difficulties is a paucity of assigned or certified values for Se in international geological reference materials, so that the “best practice” proposed by Kane and Potts (2007) to obtain robust values for such reference materials cannot be followed. In order to address this problem, we have determined Se by pre‐concentration on thiol‐cotton fibre followed by INAA (Se/TCF‐INAA technique) in twenty‐six international geological reference materials, and one quality control material (KPT‐1). These values were used, in conjunction with a set of published values, to estimate Se concentrations for these twenty‐seven reference samples. Robust statistics were developed for seven of the RMs, with standard deviations equal to or less than precisions calculated using the Horwitz function and so that consensus values could be proposed. For three of the RMs, the presence of outliers gave less robust results, and suggested values are proposed. For seventeen of the RMs, only information values are provided, because either insufficient determinations were available or because large standard deviations of the data were derived.

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