Classification of igneous rocks using automatic phase mapping with AZtecEnergy

Introduction

The AutoPhaseMap module in the Oxford Instruments' EDS software, AZtecEnergy, finds areas of different characteristic composition from X-ray map data, and determines the distribution, area, constituent elements and composition of each of these areas or phases. This application note examines how this technique can be used to determine the modal percentages of different minerals in an igneous rock, and from this result classify its type.

Automatic Phase Mapping and Phase Identification

An X-ray SmartMap was collected from an area of the sample at the minimum magnification, in order to maximise the area analysed because the grain size of the material is large (greater than 1 mm). Conditions of acquisition are shown in Table 1.

Table 1. Acquisition parameters for areas analysed

X-ray maps for constituent elements were identified automatically and used to produce a Layered Image of different maps to summarise the chemistry and microstructure of the sample (Fig. 1a). The AutoPhaseMap result for this area is shown in Fig. 1b. Colours are assigned to each phase to match the colours of X-ray maps in the Layered Image. In this area nine phases were identified, and the Area% of each phase is shown in Fig. 1c. For each phase, a phase distribution image, spectrum and quantitative result is generated automatically and the results for the 4 most abundant phases are shown in Fig. 2. Phases are named automatically based on the most abundant elements identified. Inspection of the data allows the identity of each phase to be simply deduced.

Fig. 1. AutoPhaseMap calculation for an igneous rock converts X-ray mapping data summarised in (a) the Layered Image into (b) an AutoPhaseMap dataset where each pixel is designated as a phase. In (c) the area fraction of each phase is shown.

Fig. 2. Phase distribution images, X-ray spectra and quantitative analysis in oxide% for the four most important phases identified in Area 1 of the sample.

Analysis of Multiple Areas

Igneous rocks are classified based on the area or modal% of major minerals present. However, due to the relatively large grain size in this sample, and therefore the relatively small numbers of grains analysed, the classification based on a single area may not be accurate. Therefore in this study SmartMaps from four different areas of the sample were collected to check for classification consistency. Each SmartMap was collected under the same conditions (Table 1), and using the same user profile to harmonise map selection and colour, equivalent phase results are given by AutoPhaseMap for each area (Fig. 3). Due to the grain size, there are some differences in the phases present in each area and some difference in phase abundance, however plagioclase (SiAlO – red), pyroxene (SiFeO – green), quartz (SiO – blue) and K-feldspar (SiKO – purple) are major constituents in all areas.

Fig. 3. AutoPhaseMap results and area fractions for three additional areas of the sample.

Igneous Rock Classification

Igneous rocks containing quartz and with greater than 10 modal% of quartz (Q), K-feldspar (A) and plagioclase (F) are classified using the percentages of these three minerals. The method follows the IUGS classification procedure (Streckeisen (1976), Le Bas and Steckeisen (1991)). Based on the pixel totals for each of these three phases the relative percentages of these three minerals have been calculated. In addition the plagioclase ratio (plagioclase/(plagioclase+K feldspar)) has been determined. The data is summarised in Table 2. Igneous rocks with quartz between 5–20% and plagioclase ratios of greater than 90% are defined as quartz gabbros or quartz diorites using this scheme. Table 2 shows that despite variations in measured phase fractions, the modal% of quartz and the plagioclase ratio are consistent with the quartz gabbro/diorite classification in all four areas. If we add the pixels together from the four areas, to classify the rock based on all the areas measured, the same classification is also found.

Table 2. Despite variations in measured mineral percentages, all four areas analysed, and the total of the four areas all give the same classification.

Chemical Classification

The results of modal % analysis classify this rock as a quartz gabbro or quartz diorite. To distinguish between these two rock types, the chemistry of the plagioclase mineral is assessed. The results of the standardless quantitative analysis of the plagioclase phases in each of the areas determined by AutoPhaseMap are given in Table 3, in Oxide% and Number of Ions. These results show consistent mineral chemistry between the different areas with the plagioclases being moderately calcic (Ca/(Na+Ca) >0.5). Therefore these plagioclases may be classified as Labradorites. The calcic nature of the plagioclase in this rock classifies it as quartz gabbro rather than quartz diorite which has sodic (Ca/(Na+Ca) <0.5) plagioclase.

Table 3. Composition of the plagioclase phase from each area determined from the X-ray spectra reconstructed from the pixels identified as this phase.

Conclusion

EDS SmartMapping and AutoPhaseMap provide an alternative method for mineral identification, chemical characterisation, modal calculation and rock classification. The example described here shows that the analysis is consistent over more than one acquisition area, which is particularly advantageous where grain sizes are relatively large and the characterisation of the rock or other material requires the collection of data from more than one area.

References

• Streckeisen, A. L., 1976, Neues Jahrbuch fur Mineralogie, Monatshefte, H.1, 1–15
• Le Bas, M. J., Steckeisen, A. L., 1991, Journal of the Geological Society of London, 148, 825–833