Application of Fourier Transform Infrared Spectroscopy (FTIR) for assessing biogenic silica sample purity in geochemical analyses and palaeoenvironmental research

Abstract

Abstract. The development of a rapid and non-destructive method to assess purity levels in samples of biogenic silica prior to geochemical/isotope analysis remains a key objective in improving both the quality and use of such data in environmental and palaeoclimatic research. Here a Fourier Transform Infrared Spectroscopy (FTIR) mass-balance method is demonstrated for calculating levels of contamination in cleaned sediment core diatom samples from Lake Baikal, Russia. Following the selection of end-members representative of diatoms and contaminants in the analysed samples, a mass-balance model is generated to simulate the expected FTIR spectra for a given level of contamination. By fitting the sample FTIR spectra to the modelled FTIR spectra and calculating the residual spectra, the optimum best-fit model and level of contamination is obtained. When compared to X-ray Fluorescence (XRF) the FTIR method portrays the main changes in sample contamination through the core sequence, permitting its use in instances where other, destructive, techniques are not appropriate. The ability to analyse samples of < 1 mg enables, for the first time, routine analyses of small sized samples. Discrepancies between FTIR and XRF measurements can be attributed to FTIR end-members not fully representing all contaminants and problems in using XRF to detect organic matter external to the diatom frustule. By analysing samples with both FTIR and XRF, these limitations can be eliminated to accurately identify contaminated samples. Future, routine use of these techniques in palaeoenvironmental research will therefore significantly reduce the number of erroneous measurements and so improve the accuracy of biogenic silica/diatom based climate reconstructions.

Inter-laboratory comparison of oxygen isotope compositions from biogenic silica

“…The number of studies using this technique has increased in the last decade and the discipline has been recently reviewed (Leng and Barker, 2006;Swann and Leng, 2009). Significant advances have been made in the cleaning of sediment samples (Morley et al, 2004;Rings et al, 2004;Swann et al, 2006;Crespin et al, 2008) and in the ability to quantify and correct for residual contamination (Lamb et al, 2007;Brewer et al, 2008;Swann and Patwardhan, 2011). Perhaps the greatest remaining analytical issue concerns removal (or the controlled isotopic exchange and then removal = "fixing") of the exchangeable oxygen contained in hydrous groups during oxygen isotope analyses of biogenic silica.…”

A 250 ka oxygen isotope record from diatoms at Lake El'gygytgyn, far east Russian Arctic

“…The preparation of the samples (e.g. JuilletLeclerc and Labeyrie, 1987;Shemesh et al, 1995;Morley et al, 2004), contamination assessment (Lamb et al, 2007;Brewer et al, 2008;Mackay et al, 2011;Swann and Patwardhan, 2011) as well as the oxygen isotope analysis for diatoms are often challenging and time-consuming (Leng and Barker, 2006;Swann and Leng, 2009). Recently, improved protocols have been developed for the purification of small fractions and a more reliable contamination correction .…”

“…Focusing on wavelengths < 1500 cm −1 allows only the silica bonds from the diatom frustules to be examined. Common peak centres for amorphous silica are 450 cm −1 , 800 cm −1 and 1100 cm −1 for various modes of siloxane bonds and 945 cm −1 for silanol bonds (GendronBadou et al, 2003;Swann and Patwardhan, 2011). In our study the data was baseline-corrected and normalised, so that the area under each curve adds up to 100 %, with individual peaks separated by applying a Gaussian peak fitting (Fig.…”

“…silanol bonds: Si-OH; H 2 O) over a certain wavelength window (Schmidt et al, 2001;Gendron-Badou et al, 2003;Moschen et al, 2006;Leng et al, 2009;Swann and Patwardhan, 2011 (Vogel et al, 2008;Rosén et al, 2010). Sixteen (16) purified diatom samples from different core depths (first sample at 0.09 m, last sample at 12.35 m) were selected and scanned (64 scans per sample) with measurements taken every 4 cm −1 for the spectral region between 3750 and 400 cm −1 .…”

“…In our study the data was baseline-corrected and normalised, so that the area under each curve adds up to 100 %, with individual peaks separated by applying a Gaussian peak fitting (Fig. 4a) (Swann and Patwardhan, 2011) using the software Fytik, Version 0.9.3 (http://fityk.nieto.pl/). Peak types were then assigned (Si-OH and Si-O-Si) and the percentages calculated from the respective areas.…”