EELS method for mapping iron valence ratios in oxide minerals

Micron 37 (2006) 301–309 www.elsevier.com/locate/micron

A STEM/EELS method for mapping iron valence ratios in oxide minerals Lisa Cave´ a, Tom Al a,*, Diana Loomer a, Steven Cogswell b, Louise Weaver b b

a Department of Geology, University of New Brunswick, Fredericton, NB, Canada E3B 5A3 Microscopy and Microanalysis Facility, University of New Brunswick, Fredericton, NB, Canada E3B 5A3

Abstract The valence state of iron in minerals has useful applications in the geosciences for estimating redox conditions during mineral formation or reequilibration. STEM/EELS techniques offer the advantage over other methods of being able to measure Fe valence with very high spatial resolution across mineral grains and grain boundaries. We have modified an EELS method for point analyses of iron valence ratios (Fe3C/SFe) making it possible to generate line scans and maps of Fe valence. We demonstrate this method with measurements at an interface between ironbearing oxides in a finely intergrown sample of magnetite and ilmenite. The STEM/EELS method is based on a calibrated relationship between Fe3C/SFe and the relative intensities of the Fe L3 and L2 white lines in core energy-loss spectra for oxide and silicate minerals. Our method overcomes problems of energy drift in spectrum images by aligning energy-loss edges at a fixed energy position prior to background removal. An automated routine for batch processing of core loss spectra, including additional background removal and calculation of Fe L3/L2 intensity ratios, allows for rapid Fe3C/SFe determinations of multiple point analyses or spectrum images and the preparation of Fe valence maps, with an analytical error of G0.05 to G0.09 in the Fe3C/SFe measurements. q 2005 Elsevier Ltd. All rights reserved. Keywords: Electron energy-loss spectroscopy; EELS; Iron valence state; Ilmenite; Magnetite; Spectrum imaging; Valence maps

1. Introduction Iron is the fourth most abundant element in Earth’s crust. Iron-bearing minerals are found in a large variety of geologic environments, ranging from high pressure and temperature deep within the crust and mantle, to low temperature and pressure at Earth’s surface. In Earth’s crust, iron occurs mainly in two valences, ferrous (Fe2C) and ferric (Fe3C), and it cycles between these states in response to prevailing reduction– oxidation (redox) conditions. Consequently, measurements of iron valence ratios (Fe3C/SFe) in minerals can provide a useful measure of past redox states in geologic systems. For example, measurements of Fe3C/SFe in minerals and silicate glasses allow petrologists to investigate oxygen fugacity in the mantle (Bezos & Humler, 2005; Williams et al., 2004; McCanta et al., 2004), and to estimate temperature and pressure conditions for igneous and metamorphic rocks using geothermometers and geobarometers based on Fe2C/Mg2C exchange reactions between ferromagnesian silicates (Wu et al., 2004; Holdaway et al., 1997; Schumacher, 1991) and oxide minerals (Andersen et al., 1991). In low temperature environments, for example, * Corresponding author. Tel.: C1 506 447 3189; fax: C1 506 453 5055. E-mail address: [email protected] (T. Al).

0968-4328/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.micron.2005.10.006

measurements of the Fe3C/SFe ratio provide a tool for estimating the depth of infiltration of oxygenated groundwater into bedrock, which has applications in fields such as climate change studies and the safe siting of geological repositories for nuclear waste disposal. Traditional methods of quantifying Fe 3C/SFe have involved wet chemical analysis, Mo¨ssbauer spectroscopy or calculations from microprobe data using mineral stoichiometry and charge balance considerations. One of the challenges of these bulk methods has been the problem of spatial resolution, especially in fine-grained samples or those showing spatial heterogeneity. Advances in X-ray microbeam and synchrotron methods have allowed Fe3C/SFe measurements to be made on individual mineral grains using techniques such as X-ray photoelectron spectroscopy (XPS) (Raeburn et al., 1997), X-ray absorption spectroscopy (XAS) (Dyar et al., 2002; Cressey et al., 1993) and synchrotron Mo¨ssbauer spectroscopy (SMS) (Jackson et al., 2005). In recent years, XPS and XAS techniques have evolved to allow spectra to be collected at a spatial resolution in the order of 10!10 mm2 (Blomfield, 2005; Dyar et al., 2002). However, the best spatial resolution to date for measuring Fe3C/SFe ratios has been obtained from electron energy-loss spectroscopy (EELS) in the transmission electron microscope (TEM) environment (van Aken & Liebscher, 2002; van Aken et al., 1998; Garvie & Buseck, 1998). Spatial resolution is governed by probe size in the TEM and can be as

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˚ in a dedicated scanning transmission electron small as 3 A microscope (STEM) (Garvie & Buseck, 1998), although practical considerations, such as counting statistics and sample damage under the beam, may necessitate working at larger probe sizes. The nanometer-scale resolution of STEM/EELS allows measurements of Fe3C/SFe to be made near and across mineral interfaces to characterize mineral diffusion-reaction processes at a spatial resolution consistent with the scale of the reactions. In this paper, we describe a method for mapping the distribution of Fe valence in oxide minerals using coupled STEM/EELS. Working in STEM mode gives very high spatial resolution, on the order of a few nanometers, and allows precise selection of the area to be analyzed. The Fe3C/SFe ratios are measured by a calibrated relationship between Fe L3 and L2 white line intensity ratios in EEL spectra and Fe valence, modified from the procedures developed by van Aken et al. (1998). Our modifications make it possible to apply the technique to samples of unknown iron valence. Mapping is facilitated by automated line and map scanning tools (spectrum imaging) for the collection of EEL spectra and the use of customized processing software. The method is demonstrated by spectrum images of the Fe3C/SFe changes occurring across mineral interfaces between ilmenite and magnetite in a sample with microscale exsolution lamellae. 2. STEM/EELS Fe3C/SFe method 2.1. Sample preparation and characterization Fe valence measurements were calibrated using Fe-bearing mineral standards of known valence state: fayalite (Fe2CSiO4), 3C magnetite (Fe2CFe3C 2 O4 ) and hematite (Fe2 O3 ) (Table 1). 2C Samples of ilmenite (Fe TiO3), goethite (Fe3CO(OH)) and a different sample of hematite were prepared as check standards and analyzed as unknowns to verify that the method produced

reliable results for samples of known iron valence. Grain mounts of the calibration standards were examined by scanning electron microscopy (SEM) and analyzed by energy dispersive X-ray spectroscopy (EDS) to confirm their purity. Carboncoated samples were analyzed using a JEOL JSM 6400 SEM and EDAX Genesis X-ray microanalyzer with Si(Li) detector. EDS spectra for quantitative analysis were collected at an accelerating voltage of 15 kV and beam current of 1.5 nA using 50–80 s collection times. The EDAX Genesis software was used to remove spectral background and calculate quantitative wt% oxide values from peak intensities. Rutile was used as a standard to set the beam current factor and diopside, hortonolite olivine (Fo36) and hematite of known composition were used as calibration standards for EDS. Mineral standards were prepared for STEM/EELS work by grinding to a fine powder in an agate mortar and pestle. Only a small amount of fayalite was available, so the crystals were crushed to powder between glass slides. Crushed material was suspended in 100% ethanol and sonicated. The suspension was withdrawn during sonication using a micropipette and dropped on a holey-carbon molybdenum TEM grid. The standards were lightly carbon coated for TEM analysis. This method provides areas on the edges of crushed grains, which are thin enough for EELS analysis. An intergrown magnetite/ilmenite sample from the University of New Brunswick Mineral Collection (Sample UNB451078) was used for Fe valence mapping. This magnetite is a different sample from that used as a calibration standard. A double-polished, 30 mm petrographic thin section was prepared on a glass slide and areas of finely intergrown magnetite and ilmenite identified under reflected light. Copper 800 mm aperture TEM grids were epoxy-mounted over selected areas, which were then cut and removed from the slide along with the area of interest. The TEM samples were thinned using a Gatan Model 691 Precision Ion Polishing System until small holes were milled through the areas of interest along mineral grain

Table 1 Mineral composition (wt% oxidesGone standard deviation) and measured EELS Fe L3/L2 ratios (mean valuesGone standard deviation) for Fe calibration standards Origin

Fayalite Coso Hot Springs, California Excalibur Mineral Co.

Magnetite Mineville, New York Wards Scientific 49-5906

Hematite University of New Brunswick Collection D306#15

MgO MnO SiO2 Fetotal FexOy Total n Formula Fe3C/SFeb L3/L2 intensity ratio Precision of EELS Fe3C/SFec n

0.3G0.1 4.4G0.2 29.2G0.2 51.3G0.5 66.0G0.6 (x,yZ1) 100.3G0.8 10 ðFe2C 1:9 Mn0:1 ÞSiO4 0.00 4.22G0.06 G0.09 25

nda nd 0.4G0.1 72.6G0.4 100.4G0.6 (xZ3,yZ4) 101.3G0.8 10 Fe2CFe3C 2 O4 0.67 5.00G0.09 G0.05 18

nd nd 1.0G0.1 67.2G0.6 96.1G0.9 (xZ2,yZ3) 98.3G0.8 12 Fe3C 2 O3 1.00 5.64G0.10 G0.05 20

Elemental composition data were acquired from point analyses by SEM/EDS. a nd indicates no signal detected above background. b Fe3C/SFe calculated from mineral stoichiometry. c Precision estimates were calculated from the standard deviation of repeat L3/L2 measurements converted to Fe3C/SFe values using the second order polynomial calibration function.

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interfaces. Grid-mounted samples of magnetite/ilmenite were carbon coated for examination by SEM and point analyses made by EDS on a grain mount of the same sample, to determine average chemical composition of the minerals. The TEM grids were then transferred to the STEM for EELS measurements. 2.2. EELS data collection EELS microanalysis data were collected on a JEOL 2011 STEM with a LaB6 cathode operated at 200 kV, and a postcolumn Gatan Image Filter (GIF). EEL spectra were collected in STEM mode. The same instrument settings and spectrum analysis procedures were used for all mineral standards and samples. Mineral standards and samples were analyzed at ambient temperatures, with the exception of the magnetite/ilmenite sample, which was cooled to K174 8C with a liquid nitrogen holder, to overcome problems with hydrocarbon contamination. EEL spectra were acquired using a 10 nm probe and 110 mA beam current at 0.2 eV/channel energy dispersion. A 50 mm condenser aperture, 4 cm camera length and 2 mm EELS spectrometer entrance aperture gave an 18 mrad convergence angle (2a) and 26 mrad collection angle (2b). Core energy-loss spectra were measured from 580 to 780 eV. Point analyses were conducted using a 20 s collection time for core loss spectra (2 s!10 repetitions with 4 y-binning). Between 7 and 25 point spectra were collected to calculate averages for each sample or standard. Line and map spectrum images were collected using an automated software routine for spectrum imaging within the Gatan Microscopy Suite (GMS). Spectrum images were set up to collect spectra at 10 nm intervals along lines and across rectangular areas, giving approximately continuous coverage with the 10 nm probe. Collection times were decreased to 4 s for each core loss spectrum in the line scans and 2 s in the maps. Spectrum images were also restricted to lengths of less than 800 nm or maps of maximum 150!150 nm2. Low energy-loss spectra, including the zero loss peak, were collected for the energy-loss range K20 to 160 eV for several points in each area chosen for analysis, in order to estimate the log-ratio relative thickness of the sample region. This was done to check that the sample thickness was less than one mean free path (l) and ensure that the probability of interference from multiple inelastic scattering interactions would be low.

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2.3. EEL spectrum processing Shifts in the energy scale during data collection complicate background removal from spectrum images. Automated procedures are available in GMS software to fit a background function to one spectrum and extend this background to all spectra in the parent spectrum image, but this can introduce large errors if the energy scales of the spectra are not aligned. In order to provide consistency in background removal and subsequent calculations, we reprocessed spectrum images using a realignment program developed in the Gatan Digital Micrographe scripting language. The program searches for energy-loss edge onset within a user-specified energy range, using criteria for the first derivative from a Savitzky-Golay smoothing filter to locate the edge. Savitzky-Golay methods produce datasets with reduced noise, but attempt to preserve the height and width of peaks (Press et al., 1992; Gerald & Wheatley, 1990). After the edge positions are located for all spectra in a spectrum image, a new dataset is created with appropriate offsets for individual spectra, such that the edge of interest is aligned at a user-specified energy channel. Datasets are padded at the extrema of energy ranges to provide continuous data suitable for further processing in GMS. Although the smoothing is used for locating edges, the processed dataset contains the raw, unsmoothed, but aligned data. The realignment program was used to search for the Fe L3 edge over a 25 eV energy range either side of the expected position near 708 eV and to align the edge at 708 eV (Fig. 1). Zero loss peaks in low loss spectrum images were also aligned at 0 eV. Following realignment, an inverse power law background function was fit over a region of 12–20 eV preceding the Fe L3 edge and intensities below the inverse power law function were subtracted for all spectra. A double arctangent function (van Aken & Liebscher, 2002) was then used to remove additional background intensity and isolate the Fe L3 and L2 white lines (Fig. 2). The relative intensities of the Fe L3 and L2 white lines are a function of the Fe valence state, so the intensity ratio (L3/L2) can be used to quantify Fe3C/SFe. L3/L2 ratios were obtained from background-subtracted spectra by integrating across two narrow energy windows, each 2 eV wide (Fig. 3). The core loss spectra were aligned, as described above, but the energy scale was not calibrated. The first window was centered on the L3 peak maximum, and the second window set at a fixed distance

Fig. 1. Spectrum image realignment for a line data set across a magnetite/ilmenite boundary: (a) shows the raw data, demonstrating typical drift in energy position of white lines during data acquisition and (b) the spectral data following realignment at 708 eV, (c) is an annular dark field STEM image showing where the spectrum image data were collected. Variations in the iron content of the two minerals accounts for the change in intensity of the Fe L3 and L2 white lines across the spectrum image.

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Fig. 4. Calibration curve relating Fe3C/SFe in minerals to variations in L3/L2 intensity ratios. Error bars indicate one standard deviation.

Fig. 2. Removal of background intensity from core loss EEL spectrum for hematite: (a) shows the fitting of an inverse power law function to remove preedge background. Post-edge background is then removed with a double arctangent step function (shown in (b)) to produce the isolated Fe L3 and L2 white lines used in the Fe3C/SFe measurement.

of 12.8 eV higher. This separation maximizes the integrated area under the Fe2CL2 peak, but integrates slightly off the L2 peak for Fe3C minerals, improving the sensitivity of the method (van Aken & Liebscher, 2002). To improve the speed and ease of EEL spectrum processing, a second GMS script was written to remove the double arctangent background function and calculate L3/L2 intensity ratios for point spectra and spectrum images. This routine also employs a 2nd or 4th order Savitzky-Golay polynomial

smoothing of the spectra (Press et al., 1992; Gerald & Wheatley, 1990) before searching for the L3 and L2 peak maxima and the post-peak minima within defined energy ranges. A graphical user interface enables customized peak search ranges, background removal parameters and selection of the size and position of integration windows. Options are available to use smoothed data for calculating L3/L2 ratios, or to smooth only for locating peak maxima. The script also calculates Fe3C/SFe based on user-defined calibration functions for L3/L2 ratios (Fig. 4). In addition, data files can be processed in batch mode, requiring less interaction from the user for large numbers of files.

3. Results and discussion 3.1. Fe3C/SFe calibration Point analyses of EELS L3/L2 ratios from unsmoothed data for mineral standards (Table 1) were compiled to produce a second order polynomial calibration curve (Fig. 4), which was used to calculate unique Fe3C/SFe values for unknowns. Point analyses for the check standards gave results close to the anticipated ratios (Table 2). The hematite and goethite check standards display Fe3C/SFe values equal to the theoretical value of 1.0, within the precision of the measurements. The results suggest that ilmenite may contain 11% Fe3C/SFe, which could be attributed to substitution for Fe2C and Ti4C in the ilmenite lattice (Nesse, 1991), however this value is close to the estimated precision for the Fe2C Table 2 Measured Fe3C/SFe ratios for mineral check standards from University of New Brunswick Mineral collection

Fig. 3. Integration windows used to calculate the L3/L2 intensity ratio, from which Fe3C/SFe is determined. The first 2 eV window is centered on the L3 peak maximum and the second at an energy range of 11.8–13.8 eV above the L3 peak.

UNB number

Ilmenite 53–507

Goethite 46–1046

Hematite D306#21

Fe3C/SFetheory Fe3C/SFemeas n

0.00 0.11G0.09 12

1.00 1.04G0.04 14

1.00 0.99G0.06 14

Mean valuesGone standard deviation.

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Fig. 5. SEM Backscattered electron images of the magnetite/ilmenite sample (UNB45-1078) mounted on a 3 mm copper TEM grid. Brighter grey areas are magnetite, with darker grey exsolution lamellae of ilmenite. The sample also contains inclusions of spinel, which appear as black spots on the image. The large dark area in the centre of the main image is a hole created by argon ion milling. The inset shows an enlarged view of the working areas around three smaller holes where EELS data were acquired.

standard fayalite (9%) and it may simply reflect analytical error. 3.2. Magnetite/ilmenite The sample of finely intergrown magnetite and ilmenite (Fig. 5) was ideal for developing Fe valence mapping and testing the spatial sensitivity of the technique, because the exsolution lamellae provide sharp boundaries between zones of markedly different Fe valence states. Ilmenite lamellae in the sample range in width from 1 to O100 mm. Data for the average composition of ilmenite (Table 3) suggest that there is substitution of Mn2C and Mg2C for Fe2C and that about 10% of the Ti4C sites are occupied by Fe3C. Numerous irregularlyshaped inclusions of spinel were evident from optical microscopy and SEM, particularly within the ilmenite. Trace quantities of Al, Ti and Cr may substitute within the magnetite structure, but these elements could also be present in the form of spinel and ilmenite inclusions, which are not resolved at the scale of the SEM/EDS analysis. Before acquiring spectrum images, point determinations of Fe3C/SFe were made on magnetite and ilmenite in working areas 1 and 3, shown on Fig. 5. The data for the point measurements are annotated on the STEM images in Fig. 6. Magnetite Fe3C/SFe values cover a small range, with a mean of 0.67G0.03 (meanGone standard deviation), which is in agreement with the theoretical value for magnetite. Ilmenite Fe3C/SFe measurements have slightly greater scatter, indicating that Fe3C represents between approximately 0 and 20% of the total Fe in this mineral.

An example of a Fe3C/SFe line scan, obtained using our STEM/EELS method, is shown in Fig. 7. The method can also be used to make two-dimensional maps of the Fe valence in minerals, as shown in Fig. 8. EELS spectrum image data were collected across a 15!15 point grid to generate this map. Line scan data are shown as a scatter plot of Fe3C/SFe versus distance along the spectrum image, while the map uses the shading intensity to represent ranges of Fe3C/SFe across the two-dimensional grid. The data demonstrate that the Fe valence in magnetite is relatively constant, consistent with the theory that the magnetite structure does not allow substitution of Fe2C in the Fe3C site or vice versa. Variations in the Fe3C/SFe for Table 3 Mineral composition (wt% oxidesGone standard deviation) for intergrown Febearing oxide minerals (Sample UNB45-1078)

MgO MnO Al2O3 SiO2 TiO2 Cr2O3 Fetotal FexOy Total n Formula Fe3C/SFeb

Magnetite

Ilmenite

0.5G0.1 nd 0.9G0.3 0.2G0.1 1.1G0.3 0.8G0.3 70.1G0.3 96.9G0.5(xZ3,yZ4) 100.6G0.9 8 Fe2CFe3C 2 O4 0.67

4.2G0.4 1.4G0.2 nd nd 54.6G0.9 nd 31.4G0.5 40.4G0.6(x,yZ1) 101.2G1.0 9 3C ðMg0:1 Mn0:4 Fe2C 0:6 Þ$ðTi0:9 Fe0:1 ÞO3 0.18G0.02

Elemental composition data were acquired from point analyses by SEM/EDS. a nd indicates no signal detected above background b Fe3C/SFe calculated from mineral stoichiometry.

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Fig. 6. Annular dark field STEM images of intergrown magnetite and ilmenite showing point measurements of Fe3C/SFe.

magnetite may arise from substitutions in the magnesioferrite-jacobsite-magnetite mineral series Mg2CFe3C 2 O4K ðMn; Fe; MgÞ2CðFe; MnÞ3CO4 KFe2CFe3C O Þ, but this speci4 2 men does not contain sufficient Mg or Mn to have a significant effect on the Fe3C/SFe. There is a measurable variation in Fe3C/SFe within the ilmenite grains, with fluctuations between 0.0 and 0.2 over submicron distances. Data presented in Fig. 7 suggest a zoned pattern of Fe3C substitution in ilmenite close to the magnetite boundary. Substitution of Fe3C is allowed within the ilmenite lattice. At high temperatures, there is a continuous solid solution series between ilmenite and the Fe3C end-member, hematite, which is achieved by coupled substitution of Fe3C for Ti4C and Fe3C for Fe2C (Andersen et al., 1991). Intermediate Fe3C/SFe values were found for five points along the interface region between the two minerals in the line scan (Fig. 7). A transition zone can also be seen along the mineral boundary in Fig. 8. This zone may represent a region of high Fe3C content in ilmenite or it may reflect the lower limit of the spatial resolution of these spectrum images. However, since no attempt was made to ensure that the mineral interface intersects the sample plane at 908, it is also possible that the intermediate values reflect a mixed ratio from overlap of the minerals along an inclined boundary plane. When the 10 nm probe approaches very close to the grain boundary, the

electron beam passing through the sample may interact with material on both sides of the interface to produce a weighted average signal for the two minerals. 3.3. Method development and analytical precision The method applied in this study was developed from the modified integral intensity method, described by van Aken and Liebscher (2002). Our processing method has the advantage that Fe3C/SFe determinations can be performed from spectra that do not have an accurately calibrated energy scale and can be extended to samples with unknown Fe valence. The method allows us to work with line and map spectrum images where all the Fe L3 edges have been realigned at a fixed energy position that is not necessarily a reflection of the true energy position of the edge. The drawback of working with uncalibrated spectra is that we cannot make use of the valence dependent chemical shift in the absolute energy positions of the Fe L3 and L2 white lines as was done by van Aken and Liebscher (2002). Aligning the L3 edges at a fixed energy value allows for more precise background removal from spectrum images, but removes any chemical shift information that may have been present in the original data. Instead we rely on the variation in L3/L2 peak intensity ratios for our Fe3C/SFe measurements. Using fixed positions for the integration windows, there is a slight influence of the valence dependent changes in L3–L2 peak separation

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Fig. 7. Measurements of Fe3C/SFe for an 80 point line spectrum image across an ilmenite/magnetite interface in working area 3. Error bars indicate the variations in valence ratios based on one standard deviation of the measured L3/L2 ratios for magnetite. The dark solid line plots a five-point moving average through the Fe3C/SFe data. The inset is a bright field TEM image of the area where the line spectrum image data were collected.

distance on the measured L3/L2 ratios, as illustrated in Fig. 3, but this effect is seldom measurable when working at 0.2 eV/ channel energy dispersion. As a result, the L3/L2 calibration range used in our method is smaller than that of van Aken and Liebscher’s (2002) method, which integrates off-peak for the more intense L3 peak in Fe2C minerals and for the less intense L2 peak in Fe3C minerals. Nevertheless, we obtain acceptable precision in Fe3C/SFe measurements. Using our processing method, the standard deviation of Fe3C/SFe calculated from

the L3/L2 ratios of the mineral standards is G0.05 for magnetite and hematite (Table 1) compared with absolute errors of G0.03 to G0.04 reported for pyroxenes, oxide and hydroxide minerals by van Aken and Liebscher (2002). The precision is lower for fayalite (G0.09), because of the flattening of the calibration curve as Fe3C/SFe approaches zero (Fig. 3). Precision for point analyses was estimated from repeat measurements on mineral standards of constant Fe3C/SFe. In

Fig. 8. Fe3C/SFe map over a 0.15!0.15 mm2 area, covering an interface between magnetite and ilmenite. The inset shows an annular dark field STEM image of where the spectrum image data was collected in working area 1. EELS spectra were collected at approximately 10 nm intervals across the grid area.

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Table 4 Signal-to-background ratios for EELS core loss spectra as a function of live counting time Fe (wt%)

Magnetite (70)

Ilmenite (31)

Live time 2 s Live time 4 s Live time 20 s

6.3G0.2 5.8G0.2 6.8G1.4

2.2G0.0 2.3G0.0 2.5G0.3

Ratios are calculated from the height of the L3 peak maximum over the height of the inverse power law background at the L3 position in the raw EELS spectra. The ratios are given as mean valuesGone standard deviation for seven point analyses at 20 s and five spectra each at both 2 and 4 s from the line spectrum images.

determining precision for measurements within spectrum images, which involved shorter acquisition times, we assumed a constant Fe3C/SFe ratio for magnetite and used the standard deviation of the magnetite L3/L2 ratios as a measure of the analytical precision. Precision for magnetite during spectrum image acquisition was comparable to the point measurements (G0.04 to G0.05). Estimated errors are slightly larger for ilmenite (G0.06 to G0.07), which has lower Fe content than magnetite, so along with the decrease in method sensitivity near the low end of the Fe3C/SFe scale, lower signal intensity may have contributed to a slight decrease in precision. Longer collection times were expected to produce better signal-to-background ratios in the EELS core loss spectra so that single point measurements of 20 s should have had greater precision than spectrum image measurements of 2–4 s per point. However, calculated signal-to-background ratios for raw EELS data, indicate that there is little difference between a 2 or 4 s acquisition time during spectrum imaging and a 10-fold increase in collection time for the point measurements (Table 4). The Fe content of the sample has a far greater effect on signal-to-background for the Fe L3 and L2 white lines than collection times and probably represents the limiting factor for Fe valence mapping in samples containing less than 10% Fe. Sample thickness also affects the background counts, so that signal-to-background ratios can be improved to some extent by working in thinner areas. Moving from a region with a relative thickness of 0.9l to one of 0.6l improved ilmenite signal-to-background from 2.2 to 2.8 and magnetite from 5.3 to 8.6 for the 20 s point acquisitions. The data collection parameters in this study were chosen after extensive experimentation with a variety of Fe-bearing minerals to optimize the signal-to-background ratio for the core loss region of the spectra. Beam current and probe size have a substantial effect on the intensity of the L3 and L2 white lines and we found that moving from 5 to 10 nm probe and 105 to 110 mA beam current, and changing the energy dispersion from 0.1 to 0.2 eV/channel greatly improved the precision of the Fe3C/SFe measurements. However, optimizing the data collection for the Fe L3 and L2 white lines in this way creates conditions where the intensity of the zero loss peak tends to saturate the detector while collecting low energy-loss spectra. The saturation necessitates removal of detector dark current references before acquiring core loss data and leads to poor precision if Fourier-ratio plural-scattering corrections are

applied using the low loss spectra (Egerton, 1996). We ensured that all spectra were collected in areas of thickness less than 1.0l, to minimize plural scattering and used only the core loss data, without deconvolution, for our Fe3C/SFe measurements. Deconvolution may be critical for resolving the fine structure of the Fe L3 and L2 white lines, which is the basis of the Fe3C/ SFe EELS method developed by Garvie and Buseck (1998), but is less important for our technique, which hinges on integrating over a narrow area near the peak maxima. By omitting the plural scattering correction, we were able to overcome common problems of trying to compensate for spatial drift between the sequential core-loss and low-loss acquisitions that are required to deconvolve spectra. Spatial drift can lead to poor deconvolution results, particularly if the sample thickness changes over the scanned area. Without deconvolution, the spatial drift is only a concern during collection of the core loss spectrum image. 4. Conclusions We have presented a method that can be used to measure Fe valence in mineral samples and to produce line spectrum images and maps of Fe valence changes over submicron areas. The method is based on EELS measurements of the relative intensities of the Fe L3 and L2 white lines in core energy-loss spectra, which are sensitive to Fe valence state. Measurements are made in STEM mode, which gives high spatial resolution and allows very accurate positioning of the electron beam in the area of interest. Our method is derived from previously published techniques for point measurements so that the analyses can be extended to spectrum imaging. We have made several modifications to the earlier techniques including: an EELS edge alignment procedure that allows the inverse power law background to be precisely fitted to spectrum image data; using core energy-loss data for thin samples without plural scattering deconvolution; and determining L3/L2 peak intensity ratios from EEL spectra that are not calibrated with respect to the energy scale. Iron valence in oxides can be measured rapidly using this relatively simple method with automated processing within GMS. Spectrum images can be acquired using collection times of 2 s per spectrum, which gives adequate signal-to-background resolution. Prior to inverse power law background subtraction, a software routine is used to compensate for energy drift across the spectrum image, by aligning selected EELS edges in the individual spectra. A batch processing routine can then be applied to remove background under the individual L3 and L2 peaks using a double arctangent function; calculate L3/L2 intensity ratios and determine Fe3C/SFe for all spectra in the spectrum image. Our method has been demonstrated by Fe3C/SFe point measurements on iron oxide and iron titanium oxide minerals, and by line and map spectrum images on a sample of intergrown ilmenite and magnetite. Both the distinct change in Fe valence across the magnetite/ilmenite interface and zonation of Fe3C/SFe ratios, resulting from varying degrees of

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substitution of Fe3C within the ilmenite grains, can be observed in the spectrum image data. Acknowledgements Development of a STEM/EELS method for measuring Fe 3C/SFe in minerals was funded by Ontario Power Generation (OPG). We would like to thank Monique Hobbs and Mark Jensen at OPG for their support on this project. The STEM used in this study is housed at the Microscopy and Microanalysis Facility at UNB, which is supported by grants from the Canadian Foundation for Innovation and the Atlantic Innovation Fund. SEM/EDS analyses were also conducted at this facility with the assistance of Dr. Douglas Hall. References Andersen, D.J., Bishop, F.C., Lindsley, D.H., 1991. Internally consistent solution models for Fe–Mg–Mn–Ti oxides: Fe–Mg–Ti oxides and olivine. Am. Mineral. 76, 417–444. Bezos, A., Humler, E., 2005. The Fe3C/SFe ratios of MORB glasses and their implications for mantle melting. Geochim. Cosmochim. Acta 69, 711–725. Blomfield, C.J., 2005. Spatially resolved X-ray photoelectron spectroscopy. J. Electron Spectrosc. Relat. Phenom. 143, 243–251. Cressey, G., Henderson, C.M.B., van der Laan, G., 1993. Use of L-edge X-ray absorption spectroscopy to characterize multiple valence states of 3d transition metals; a new probe for mineralogical and geochemical research. Phys. Chem. Miner. 20, 111–119. Dyar, M.D., Lowe, E.W., Guidotti, V., Delaney, J.S., 2002. Fe3C and Fe2C partitioning among silicates in metapelites: a synchrotron micro-XANES study. Am. Mineral. 87, 514–522. Egerton, R.F., 1996. Electron Energy Loss Spectroscopy in the Electron Microscope, 2nd ed. Plenum Press, New York. Garvie, L.A.J., Buseck, P.R., 1998. Ratios of ferrous to ferric iron from nanometre-sized areas in minerals. Nature 396, 667–670.

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