Towards a Higher Comparability of Geothermometric Data obtained by Raman Spectroscopy of Carbonaceous Material. Part I: Evaluation of Biasing Factors. Issue 1 (March 2014)

• Record Type: Journal Article
• Authors: Lünsdorf, Nils K.; Dunkl, Istvan; Schmidt, Burkhard C.; Rantitsch, Gerd; von, Hilmar
• Is Part Of: Geostandards and geoanalytical research. Volume 38:Issue 1(2014)
• Page Start: 73
• Page End: 94
• Publication Date: 2014-03
• Subjects: Analytical geochemistry -- Periodicals; Géochimie analytique -- Périodiques; 551.9
• DOI: 10.1111/j.1751-908X.2013.00249.x
• Languages: English
• ISSNs: 1639-4488

Abstract

<abstract abstract-type="main" id="ggr12011-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Raman spectroscopy of carbonaceous material (RSCM) is frequently used to determine metamorphic peak temperatures from the structural order of carbonaceous material enclosed in metasediments. This method provides a quick, robust and relatively cheap geothermometer. However, the comparability of the RSCM parameter is low as there are at least three major sources of biasing factors. These sources are the spectral curve‐fitting procedure, the sample characteristics itself and the experimental design including the used Raman system. To assess the impacts of the biasing factors on RSCM, a series of experiments was performed. The experiments showed that curve‐fitting is strongly influenced by individual operator‐bias and the degrees of freedom in the model, implying the need for a standardised curve‐fitting procedure. Due to the diversity of components (optics, light detection device, gratings, etc.) and their combinations within the Raman systems, different Raman instruments generally give differing results. Consequently, to estimate comparable metamorphic temperatures from RSCM data, every Raman instrument needs its own calibration. This demands a reference material series that covers the entire temperature calibration range. Although sample heterogeneity will still induce some variation, a reference material series combined with standardised curve‐fitting procedures will significantly increase the overall comparability of RSCM data from different laboratories.</p> </abstract>