Application Notes
Published: 27 Sep 2023 · Last updated: 27 Sep 2023
Tags: EBSD
The microstructures that are formed during in geological fault zones during earthquakes are very challenging to characterise effectively. Depending on the pressure, temperature and strain rate, the resulting microstructures can be typified by very fine grained, dynamically recrystallised regions ("mylonites") or by brecciated material, potentially with veins of quenched melt rock caused by frictional heating ("pseudotachylites"). There have been numerous studies using electron backscatter diffraction (EBSD) to characterise mylonite microstructures, but pseudotachylites are significantly more challenging – mineral fragments are often highly deformed, extremely fine grained (e.g. <5 µm grain diameter) and surrounded by an amorphous, glassy matrix.
Recent research using high spatial resolution analyses has shown that, contrary to earlier understanding, pseudotachylites are predominantly comprised of crystalline or semi-crystalline material and, as such, can be measured using EBSD. However, the EBSD patterns are typically very poor quality due to the high dislocation content and the very fine crystallite size: this makes successful data collection difficult, although analyses can benefit from the high spatial resolution of the complementary transmission Kikuchi diffraction (TKD) technique. In this application note a pseudotachylite sample is analysed using both EBSD and TKD, with pattern matching methods employed to enhance both the indexing rate and the final data quality.
A fault rock sample containing pseudotachylite veins was collected from Fjordland, New Zealand from which a thin section was prepared and polished for EBSD analysis. Both low and high resolution EBSD maps were collected, finishing with a high-resolution map, covering 250 x 280 µm across a pseudotachylite vein using a 200 nm step size. The EBSD patterns were collected using a 12 keV accelerating voltage to improve the spatial resolution and were indexed using conventional Hough-based indexing (matching against 12 mineral phases). An electron transparent section was subsequently prepared from within the finest-grained area of the vein using a focused ion beam scanning electron microscope (FIB-SEM) and this was then analysed using TKD at 30 keV accelerating voltage using a 40 nm step size and indexing 5 phases. In both datasets the diffraction patterns were stored for further reanalysis using AZtecCrystal MapSweeper.
In the conventional EBSD map, the original data were reprocessed using the Refinement and Repair sweep modes in MapSweeper, in order to improve the angular precision, correct for misindexing and to increase the indexing hit rate. In the TKD map, the initial indexing (aside from some garnet grains) was very poor (~15%) and so the indexed data were discarded and the whole dataset reprocessed using Dynamic Template Matching (DTM) in MapSweeper. The resulting data were then analysed using AZtecCrystal.
The conventional EBSD analysis resulted in relatively good quality data, although in the finest grained areas of the pseudotachylite vein the indexing rate was low. Overall, 67.7% of points could be indexed using the Hough transform approach. Reprocessing using the Refinement and Repair sweeps in MapSweeper significantly increased this hit rate, up to 83%, enabling a more detailed examination of the vein grain structures and mineral assemblage, as shown in the EBSD phase map. In addition, the better angular precision following MapSweeper refinement is clearly visible in the kernel average misorientation (KAM) maps. This angular precision improvement has important consequences when interpreting deformation structures: in the large clinozoisite grain in this area, the measured weighted Burgers vector orientations from the conventional data suggests a preferred <010> Burgers vector. However, in the improved data following pattern matching, analysis of the same grain indicates a preferred <001> Burgers vector. This difference is due to the removal of orientation imprecisions by the pattern matching process, and their corresponding impact (in the form of systematic artefacts) on disorientation and Burgers vector information.
Figure 1. Results from the highresolution EBSD analysis of the pseudotachylite vein. Top – conventional Hough-based indexing, bottom: MapSweeper processed. Left images – phase maps (major phases include plagioclase feldspar (dark blue), clinozoisite (light blue), hornblende (fuchsia pink) and kyanite (yellow); right images – KAM maps, with a 0-5° scale. The inset images show the calculated Burgers vector orientations from the large clinozoisite grain at the area’s right edge. Scale bars mark 100µm.
The TKD analysis was particularly challenging, with highly deformed and sub-µm sized grains producing very poor quality diffraction patterns. Most could not be reliably indexed using Hough-based indexing but were able to be indexed using the DTM approach in MapSweeper. An example pattern from a plagioclase feldspar grain, with corresponding DTM solution, is shown above.
Figure 2. Example TKD pattern from highly deformed plagioclase feldspar, showing robust indexing results using dynamic template matching.
Only the garnet grains could be indexed using the conventional approach; however, after the Indexing sweep in MapSweeper, the full phase distribution and grain structure in this area could be resolved. The results confirm recent studies, showing that most of the pseudotachylite vein is actually comprised of crystalline grains, albeit with high dislocation densities and grain sizes that cannot be resolved using light microscopy. Further examination reveals significant distortion within grains, and a close relationship between the orientation of larger (> 1 µm) grains and surrounding nanoscale grains, as exemplified by the hornblende pole figure.
Figure 3. Phase maps from the TKD analysis of the finest grained area of the pseudotachylite vein. Left – result after conventional Hough-based indexing. Note the very low indexing rate, and only the garnet phase (lime green) has indexed reliably. Right – result after DTM indexing using MapSweeper. Indexing was robust for all phases (including plagioclase feldspar – dark blue, hornblende – red, phlogopite – dark green). The inset shows the contoured {010} pole figure for hornblende – the orientations of the largest (1.2 µm diameter) grain are shown in bold red, highlighting the significant intragranular distortion, while the adjacent nanoscale grains share similar crystallographic orientations (high density values in the pole figure). Scale bars mark 10 µm.
The EBSD and TKD results presented here are from an exceptionally challenging type of geological sample – a pseudotachylite vein. Despite the presence of up to 12 separate mineral phases, as well as a very fine grain size and high defect densities, the EBSD and TKD results were significantly enhanced by the application of MapSweeper data processing. For the EBSD dataset, the use of the Refinement and Repair sweep improved the data quality, enabling a better analysis of the phase distribution and detailed examination of deformation mechanisms within individual grains. In the TKD data, conventional indexing was unable to provide any reliable data, whereas DTM indexing in MapSweeper not only resolved the phases effectively but revealed extensive crystallographic orientation variations on the nanometre scale. These results suggest that the pseudotachylite vein structure may not be caused by frictional heating but involves crystal-plastic processes and possibly a degree of mechanical amorphisation. This type of study can only be achieved with the performance and versatility of AZtecCrystal MapSweeper.
Oxford Instruments Nanoanalysis thank Professor Sandra Piazolo (The University of Leeds) for providing the samples and sharing the original data. Dr. Charlie Kong (University of New South Wales) is thanked for preparing the FIB lift-out sample.
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