Monte Carlo Simulator
Figure 3: Simulated BSE image of three-component Ni-Fe-Cr system at 15 keV using libMCXray.
the differences in atomic number between each phase. Te matrix is composed of pure Ni, the heaviest of the three ele- ments, whose signal level is the highest. In comparison, the Cr phase, contained in the majority of the needle-like structures, is seen as the phase containing the lowest level of signal, consist- ing of points attached to the Fe phase and the large rectangular structure in the bottom right corner of the image.
Figure 5: Three-dimensional depiction of the EDS dataset simulated using libMCXray. The image represents spatial dimensions of 512 × 512 pixels and 2048 energy bins.
Another system was simulated consisting of the expected
phases of an Al-Si alloy to show the versatility of the method in simulating alloys closer to reality. Figure 4 shows a simu- lated BSE image of the same geometric structure, however here the phases consisted of pure Al as the matrix, phase 1, Al2 as phase 2, and Mg2
Cu Si as phase 3. Simulations were performed
under the same conditions as the Ni-Fe-Cr system. Because Cu has a much higher atomic number than the
other constituent elements, and hence a higher probability of scattering, the signal level of the Al2 est in the image. In comparison, the Mg2
Cu phase is the high- Si phase contains
the lowest signal level due to its lower probability of scatter- ing. This demonstrates that even multi-component phases may properly and easily be simulated using libMCXray, and the attributes of the Dragonfly software aid in proper image analysis. EDS spectrum analysis and mapping. EDS maps were
Figure 4: Simulated BSE image of Al-Si alloy containing three phases: pure Al, Al2
Cu, and Mg2 42 Si.
simulated for the above system using the same MultiROI and positions. Here, 2048 channels were used across the energy scale. Figure 5 shows the entire 3D dataset acquired using libMCXray, two spatial dimensions and the third in energy. Te EDS simulation was performed on the Amazon AWS high- performance computing (HPC) network and took 1 hour on 500 computers each containing 8 cores. On an extremely per- formant workstation, such a simulation would take approxi- mately 200 hours. Computing times are rendered much more reasonable by the use of cluster computing.
www.microscopy-today.com • 2020 September
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