Three Dimensional Microanalysis by Energy Dispersive Spectrometry : Improved Data Processing

This thesis is focused on a combined microscopy technique: energy dispersive spectrometry (EDS) is extended to a three dimensional (3D) microanalysis using a so-called "dual-beam microscope": a scanning electron microscope (SEM) equipped with a focused ion beam (FIB). In the sequential acquisition, the surface freshly milled by the FIB is characterised by SEM imaging and EDS mapping. A 3D elemental picture of the specimen is obtained this way. This technique suffers from the same limitations than the 2D EDS mapping, the major one being linked to the volume of X-ray emission that is large due to the required high accelerating voltage. Other limitations of 3D EDS microanalysis are more specific to FIB/SEM technique, such as the low acquisition time per spectrum due to the large number of spectra required in an acquisition. The goal of this thesis was to develop post-processing solutions to overcome the limitations of 3D EDS microanalysis. Three solutions have been developed. As the acquired data are composed of a high number of noisy spectra, multivariate statistic methods are appropriate. Such a technique is adapted to 3D EDS data and provides smoother spectra improving the quantification afterwards. When analysing a feature that is smaller than the volume of X-ray emission, the quantified composition is inaccurate as part of the X-rays are emitted from the feature’s surrounding. To take into account the influence of the neighbouring voxels, an enhanced quantification technique is developed. It is based on a recursive approach adapting an existing complex quantification. Another complementary approach is developed to resolve features too fine for EDS mapping: the segmentation technique is improved by using the higher spatial resolution of SEM images. A sample formed by laser welding of nickel-titanium (NiTi) and stainless-steel wires is characterised by 3D EDS microanalysis. The acquired data are used to demonstrate the gains and the limitations of the three developed processing techniques. With them, the noise-reduced spectra reveal further details of the fine microstructure. Their quantified composition is closer to the one predicted by the phase diagram. Furthermore, the segmented phases used for the 3D visualisation have a resolution close to the one of the SEM images. This visualisation allows a deeper comprehension of the formation of the phases and their morphologies during the implied solidification. This demonstrates the great potential of this technique to characterise samples with complex microstructure and complex composition.