Electron Micro Probe Analysis

Electron microprobe analysis (EMPA) is a quantitative spectrographic technique measuring characteristic X-ray emission of elements by either specific energy or

wavelength caused by sample irradiation. Electron beam bombardment causes ejection of primary lower energy level electrons creating ionization. Higher level shell electrons drop to fill voids in lower shells and emit a photon by doing so. Electron shells are specific energy states surrounding the nuclei of an atom. Shells are categorized into K, L and M shells, the order representing increasing energy (Goldstein et al., 2003). These shells are subdivided into sub shells (Goldstein et al., 2003). Energy can only be

transferred through sub shells of the three major shells forming characteristic X-rays from energy transfers at the boundary of subshells (Goldstein et al., 2003). Specific X-ray energies and wavelengths characterize each element undergoing excitation, defined by Moseley’s Law (Goldstein et al., 2003). As the atomic number of the element analyzed increases, critical ionization energy also increases, leading towards lower spatial

3.3.4.1

Energy Dispersive Spectrometry

Energy dispersive spectrometry (EDS) is a form of X-ray spectroscopy that identifies-quantifies elements and their abundance by measuring photon energy and converting it to an electrical signal (photoelectric absorption). The conversion is carried out a by a lithium silicon solid state EDS detector in a cooled atmospheric chamber. Silicon electrons in the detector are raised into the conduction band while leaving a hole in the valence band by bombarding photons (Goldstein et al., 2003). Both electric signals are captured by electrodes at either end of the detectors silicon plate and are amplified and shaped to form characteristic peaks (Goldstein et al., 2003). Spot analysis of datable phases was carried out by the author under the supervision of Ivan Barker to check mineralogical consistency from feature scans.

3.3.4.2

Wave-length Dispersive Spectrometry

Wavelength dispersive spectrometry (WDS) uses the same photon emission previously described but measures electromagnetic radiation wavelength instead of energy. WDS measures emission wavelength by the use of Bragg’s law. Curved crystals, composed of homogeneous crystalline material with known d-spacings, are bombarded by X-ray emissions from irradiated samples. Wavelengths satisfying Bragg’s law are reflected to a gas proportional counter: a thin tungsten wire in a gas tube

(Goldstein et al., 2003). The gas is ionized releasing an electron attracted to a grounded thin wire creating a voltage charge pulse (Goldstein et al., 2003). The pulses are

proportional to the original X-ray photon and intensities are counted and compared to standards. In comparison to EDS, WDS offers orders of magnitude higher resolution and can simultaneously measure several elements at the same time, provided several crystals are present. Error is derived mainly from overlapping element wavelengths and

inappropriate beam current or beam spot size.

WDS analysis was completed by the JEOL JXA-8530F field-emission

microprobe housed at the University of Western Ontario. The microprobe contains five wavelength dispersive spectrometers with ten analyzing crystals along with BSE, SE and CL detectors. Spot analysis and elemental mapping of minerals were calibrated

accordingly to relative mineral standards and refractive crystals to avoid wavelength overlap and low count rates. Element mapping of monazite and xenotime grains were completed on samples 709, 716 and 6416. Essential metamorphic and alteration minerals were subjected to point analyses too.

3.3.4.3

EDS Phase Mapping

Elemental phase mapping uses simultaneous EDS and BSE imaging to create montaged element maps of sample areas. A grid of image zones is created for a sample area. The SEM acquires an energy spectrum at each pixel in a single image zone with the peak intensities being relative to elemental proportions. Simultaneously captured BSE and EDS images, sized 256 X 192 pixels, are compiled and digitally sewn together in a grid with a 10 pixel overlap creating a BSE image montage. Each grid rectangle in the BSE montage represents a 1.4 X 1.0 mm portion of the sample. Processing EDS data through Inca software enabled relative proportions of elements to be displayed geometrically. Selected carbon coated polished thin sections representing distinct lithologies were subjected to EDS phase mapping.

3.3.4.4

BSE-EDS Feature Mapping

Feature mapping is another SEM automation technique utilizing both BSE imaging and EDS to identify features of interest within a sample. Furthermore, details such as morphological measurements and position are recorded for each feature of interest. The technique involves creating a digital grid map of the sample surface. Each grid square acts as a window that the SEM rasters during BSE detection and identifies brighter materials containing higher atomic number elements. The BSE brightness is defined within a grey scale range and scaled to the operator’s need. Areas of higher brightness are selected by the routine and analyzed using quantified EDS. The EDS results are compared to a recipe file containing threshold values of acceptable element concentration for categorization. After features contained within the window are analyzed by scanning EDS, the SEM moves the stage slightly to the next window and repeats the process. Window sizes were set to 256 X 192 pixels, approximately 1.4 x 1.0 mm with a 10 pixel overlap. Threshold values for datable phases are listed in Tables 3.3

and 3.4. Recipe A was the initial values used for samples 6225, 6245, and 6220A. After identifying xenotime and baddeleyite during zircon imaging recipe B was implemented. Feature mapping can take hours to a few days per sample depending on window size, the number of feature categories or the amount of features present. Polished thin section samples underwent feature mapping to identify and locate datable phases (zircon, monazite, xenotime, allanite and baddeleyite). Data processing through ESRI Arc GIS allowed plotting of features on high resolution scanned sample images using the stage coordinates in relation to the sample.

Recipe A Class

Baddeleyite Zircon Monazite Zirconalite

Si Min -0.1 8 Elem en ts i n We ig h t % Max 8 30 O Min 16 20 5 Max 60 60.12 100 Zr Min 15 15 15 Max 82 60 35 Ti Min -0.1 10 Max 9 25 Ce Min 5 Max 100 P Min 5 Max 100 Ca Min 3.5 Max 11

Table 3-4 Table listing class recipe A for EDS feature mapping. Elements are listed with maximum and minimum threshold values.

Recipe B Class

Baddeleyite Zircon Monazite Allanite Xenotime

Si Min -0.1 8 -0.5 10 Max 8 30 7 35 O Min 18 20 15 15 10 Elem en ts i n We ig h t % Max 60 60.12 55 70 35 Zr Min 15 15 Max 80 60 Ti Min -0.1 Max 7 Ce Min 5 1 Max 100 50 P Min 5 -0.1 Max 35 2 Fe Min 2 Max 30 Y Min 10 Max 35 Ir Min 30 Max 60

Table 3-5 Table listing class recipe B for EDS feature mapping. Elements are listed with maximum and minimum threshold values.