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doi:10.2204/iodp.proc.324.204.2013

Materials and methods

A total of 17.2 m sediment over a stratigraphic interval of ~60 m (Cores 324-U1347A-3R through 10R) was retrieved from Hole U1347A before entering basaltic basement at 157.6 meters below seafloor (mbsf). The recovered material is dominated by volcaniclastic silt and sandstone with varying proportions of biogenic material (radiolarians and foraminifers) and mainly micritic carbonate (see the “Site U1347” chapter [Expedition 324 Scientists, 2010]). The sediment recovered from the 80.5–99.8 mbsf depth interval (Cores 3R and 4R) is composed of mildly silicified radiolarian-bearing glauconitic limestone and sandstone with occasional occurrences of chert. Radiolarians are very common throughout the entire depth interval. The sediments derived from the 99.8–149.1 mbsf depth interval (Cores 5R–10R) consist of alternating layers of volcaniclastic sandy siltstone (Fig. F2, Thin Sections 324-U1347A-6R-2, 10–11 and 59–62 cm) and silty sandstone (Fig. F2, Thin Section 324-U1347A-6R-1, 38–42 cm) with intercalated very fine grained layers occurring throughout the entire cored interval (Fig. F2, Thin Section 324-U1347A-6R-2, 81–84 cm) (Fig. F3). Both lithologies contain biogenic material (radiolarians and foraminifers) and micritic carbonate in varying amounts. The very fine grained layers are mainly composed of smectite, completely replacing the fresh glass particles, and minor amounts of micritic carbonate. The volcaniclastic silty sandstone is mainly composed of volcanic particles (including altered plagioclase) being to variable amounts replaced by dark brown clay minerals mixed with biogenic material and micritic carbonate. As much as 25% of the material in this silty sandstone is of nonvolcanic origin. Black oxides (probably Mn oxide) can be found on particle rims. The volcaniclastic sandy siltstone is also composed of the same components as the volcaniclastic silty sandstone. However, the amount of biogenic material and micritic carbonate is much higher than in the volcaniclastic silty sandstone (up to 60%). Radiolarians are common throughout the entire interval, even though in some of the coarser intervals the radiolarians are replaced by secondary calcite.

The material described above has been analyzed between 80.59 mbsf and 149.13 mbsf (68.54 m) for the Si, Al, Fe, Ca, K, Cl, and Mn contents using a third-generation Avaatech X-ray fluorescence (XRF) scanner with a Canberra X-PIPS silicon drift detector (SDD), model SXD 15C-150-500, 150 eV resolution X-ray detector located at the IODP Gulf Coast Repository in College Station, Texas (USA) (odases.tamu.edu/index.php/research-facilities/). The X-ray tube and detector are mounted on a moving track so that multiple spots at different depths can be analyzed on a split core during the scanning run. Multiple scans with different settings can be automatically programmed (Richter et al., 2006). Precision of the measurement positioning is 0.1 mm. For Hole U1347A core scans, the sample spacing along each core section was set at 1 cm intervals. The scans were performed at 10 kV using an Al filter. The voltage used for elements measured is determined by the energy needed to excite the appropriate characteristic X-rays. While measuring, the detector registers the emission line energies of the irradiated sample material and their frequency over the predefined measure time (30 s) as element intensities in counts, which are proportional to the element concentrations. The scan was run down the center of the split core half (6.8 cm total diameter). The tube current was set to 2 mA; the dead time of the XRF scanner is between 20% and 40%. Each core section was removed from refrigeration at least 2 h prior to scanning. To protect the detector face from becoming sediment covered and contaminated during the scan, the cores were covered ~15 min before scanning with 4 ?m thick Ultralene plastic film (SPEX Centriprep, Inc.).

The processing software used, WinAxil of Canberra, applies background subtraction, sum-peak correction, escapes peak correction, and peak integration of the XRF spectrum. It uses an interactive least-squares fitting procedure of a Gaussian function to approximate the fluorescence lines. The goodness-of-fit of a process model increases if the model identifies all peaks present in the XRF spectrum, as the program does not look at individual peaks but at groups of peaks.

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