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We present transmission electron microscope (TEM) tomography investigations of ruthenium-based fuel cell catalyst materials as employed in direct methanol fuel cells (DMFC). The digital three-dimensional representation of the samples not only enables detailed studies on number, size, and shape but also on the local orientation of the ruthenium particles to their support and their freely accessible surface area. The shape analysis shows the ruthenium particles deviate significantly from spherical symmetry which increases their surface to volume ratio. The morphological studies help to understand the structure formation mechanisms during the fabrication as well as the high effectiveness of these catalysts in the oxygen reduction reaction at the cathode side of fuel cells.
Statistical analysis of tomographic reconstruction algorithms by morphological image characteristics
(2010)
We suggest a procedure for quantitative quality control of tomographic reconstruction algorithms. Our task-oriented evaluation focuses on the correct reproduction of phase boundary length and has thus a clear implication for morphological image analysis of tomographic data. Indirectly the method monitors accurate reproduction of a variety of locally defined critical image features within tomograms such as interface positions and microstructures, debonding, cracks and pores. Tomographic errors of such local nature are neglected if only global integral characteristics such as mean squared deviation are considered for the evaluation of an algorithm. The significance of differences in reconstruction quality between algorithms is assessed using a sample of independent random scenes to be reconstructed. These are generated by a Boolean model and thus exhibit a substantial stochastic variability with respect to image morphology. It is demonstrated that phase boundaries in standard reconstructions by filtered backprojection exhibit substantial errors. In the setting of our simulations, these could be significantly reduced by the use of the innovative reconstruction algorithm DIRECTT.
Computed tomography reconstructions of projected data usually assume an ideal point-like
focal spot. However, in practice, the actual finite focus size leads to blurred projections,
unavoidably. The elements (voxels) of the reconstruction array are smeared differently as a
function of their individual position relative to source and detector. Neglecting the focal
smearing generates considerably blurred reconstructions. Previous attempts were based on
directly deconvolving blurred projections from a constant kernel, which yields better results
but still exhibits artefacts. Iterative algorithms can be adopted to take into account focal
smearing as a function of position. However, this requires detailed prior knowledge of
quantitative smear functions. The DIRECTT (Direct Iterative Reconstruction of Computed
Tomography Trajectories) algorithm is a promising candidate to meet these requirements. It
has been demonstrated elsewhere that DIRECTT copes with limited data sets such as
limited view and region-of- interest data by tracing single sinusoidal-like trajectories in
Radon space, which are selected from the set of all possible trajectories by appropriate
criteria. Currently, position-dependent smearing is used in the projection part of iterations.
At the example of model reconstructions we demonstrate the gain of spatial resolution by
iterative variable desmearing according to the DIRECTT algorithm in comparison to the
standard filtered back-projection.
Magnetic domains have been the subject of much scientific investigation since their theoretical existence was first postulated by P.-E. Weiss over a century ago. Up to now, the three-dimensional (3D) domain structure of bulk magnets has never been observed owing to the lack of appropriate experimental methods. Domain analysis in bulk matter thus remains one of the most challenging tasks in research on magnetic materials. All current domain observation methods are limited to studying surface domains or thin magnetic films. As the properties of magnetic materials are strongly affected by their domain structure, the development of a technique capable of investigating the shape, size and distribution of individual domains in three dimensions is of great importance. Here, we show that the novel technique of Talbot-Lau neutron tomography with inverted geometry enables direct imaging of the 3D network of magnetic domains within the bulk of FeSi crystals.