Figure 2: Our x-ray
transparent deformation apparatus, Mjölnir, in (a ) schematic
(Butler et al., 2017), and (b ) installed at the PSICHE
beamline. (c ) Stepped loading procedure. (d )
Reconstructed μCT image showing damage accumulation at one end of the
sample (this occurred in both samples) – dashed white line shows the
analyzed sub-volume.
X-ray imaging and image data
pre-processing
X-ray μCT data was acquired using an sCMOS (scientific
Complementary-Metal-Oxide Semiconductor) Hamamatsu ORCA Flash4.0 camera,
with a Rodagon 50 lens, giving about 2.5x magnification (effective pixel
size 2.7 µm), and a 250 µm thick LuAG:Ce scintillator. The white beam
with an average detected energy of about 66 keV was filtered with 1 mm
aluminium and 0.5 mm tungsten. During each scan, 1200 projections were
acquired over 180°, with an exposure time per projection of 15-19 ms
depending on the progressive darkening of the objective lens. A mix of
absorption and phase contrast data was acquired, with a sample to
detector distance of 125 mm.
Each µCT volume was reconstructed by filtered back projection.
Reconstructions were performed at the PSICHE beamline, using both x-ray
absorption and phase contrast modes as implemented in the PyHST2
software (Mirone et al., 2014), and yielded 3D volumes of 1700 x 1700 x
4102 equidimensional voxels, with a voxel edge length of 2.7 μm. These
volumes were then processed to extract the fracture network from the
reconstructed images. To deal efficiently with the huge size of each 3D
volume (approx. 40 GB) and speed up the subsequent processing, we
selected a sub-volume of interest – the region in the failed samples
where the majority of damage had accumulated (Figure 2d, Table 1). Using
the AvizoTM software package, this sub-volume was
extracted from each of the full 3D volumes and de-noised with an
anisotropic diffusion filter (stop value 0.4 over 4 iterations), which
was chosen to emphasize the microcrack features as it preserves strong
edges and enhances edge contrast. It was then down-sampled to 16-bit
with a 32-bit threshold range of -0.3 to 0.8, yielding individual
datasets of manageable size (approx. 3 GB).
Table 1: Dimensions of
the whole sample and analyzed sub-volume, with uncertainties to two
decimal places.