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doi:10.2204/iodp.proc.320321.203.2012

X-ray fluorescence analytical technique

X-ray fluorescence is an analytical technique that uses the characteristic fluorescence of elements exposed to high-energy X-ray illumination as a means to estimate a sample’s chemical composition. High-energy X-ray photons eject inner-shell electrons from atoms being illuminated by the X-rays (Jansen et al., 1998). Outer shell electrons in higher energy levels then occupy these lower energy levels, releasing the excess energy as characteristic XRF for each element. The intensity of the fluorescence from a sample can be used to determine the abundance of different elements.

XRF is a volume and not a mass measurement, however. A conventional chemical analysis measures the amount of an element in a standard mass of total material; a sample with 8 wt% Fe has, for example, 8 g Fe per 100 g sample. For XRF, in contrast, the X-ray source illuminates a certain volume of sediment, and the amount of X-rays returned in part depends on the mass of sediment in that volume. Low atomic weight elements emit lower energy X-rays than high atomic weight elements, and these low-energy X-rays are more easily absorbed by other elements as they pass out of the sample. For this reason, light elements have a smaller characteristic emission volume than heavy elements (Tjallingii et al., 2007), causing problems if the sample is not homogeneous.

For unconsolidated sediments, part of the illuminated volume is occupied by pore space, so that the volume XRF return is less than that from a pure solid. Because scanning XRF is a volume measurement, there is a correlation between XRF-scan raw X-ray peak areas and wet bulk density (Fig. F2). Low wet bulk density marks samples with high porosity and low solid mass per sample, in contrast to samples with high bulk density. The volume effect most strongly affects the most abundant elements in the samples—in the case of carbonate-rich equatorial Pacific sediments, the correlation is best found with Ca.

In order to remove the volume effect, the data must be normalized before calibration. The normalization method used in this paper (normalized median-scaled sums) is described in “Data reduction methods for later calibration: normalized median-scaled method” later in this data report.

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