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Etalon features in transmittance spectra of films arise due to the coherent superposition of waves caused by reflections multiple times at the inner film boundaries. The fringe maxima occur at i𝜆 = 2nd cos 𝜑 with i - being an integer, 𝜆 - the wavelength, d - the film thickness, 𝜑 - the angle of incidence in respect to the film normal and n - the refractive index of the film. It is obvious that such features can hinder the interpretation of absorption bands when fringe amplitude and period are in the same range as the expected bands.
This poster discusses the suitability of two optical methods for the THz spectral range applied to Fourier Transform Spectroscopy.
Etalon effects in THz transmittance spectra, either taken in time- domain or frequency-domain, often hamper or even hinder the interpretation of film properties. In this paper we discuss the transferability and applicability of spectroscopic methods typically employed in the near and mid infrared spectral range to eliminate the fringes in the transmittance spectra in the THz spectral range.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2020)
Block-sparse regularization is already well-known in active thermal imaging and is used for multiple measurement based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging.
We show how the combination of the spatial autocorrelation function and permeability calculations, applied to 3D X-ray computed tomography data, can yield quantitative information on the anisotropy of both meso-structure and fluid flow in Diesel Particulate Filter (DPF) materials, such as Cordierite and SiC. It was found that both the degree of anisotropy, and the orientation of the permeability and meso-structure are similar, but not identical. We confirm that the morphological anisotropy of cordierite materials is weak, and clearly influenced by the extrusion process that determines the main direction of anisotropy. Properties of the autocorrelation function are discussed and it is shown why estimating the characteristic length of real meso-structures (grain or ?pore? size) is not possible. Finally, we show that the autocorrelation function applied on grey-level images can give a good estimate of the degree of anisotropy even with limited resolution.
The ability to track electrode degradation, both spatially and temporally, is fundamental to understand performance loss during operation of lithium batteries. X-ray computed tomography can be used to follow structural and morphological changes in electrodes; however, the direct detection of electrochemical processes related to metallic lithium is difficult due to the low sensitivity to the element. In this work, 4-dimensional neutron computed tomography, which shows high contrast for lithium, is used to directly quantify the lithium diffusion process in spirally wound Li/SOCl2 primary cells. The neutron dataset enables the quantification of the lithium transport from the anode and the accumulation inside the SOCl2 cathode to be locally resolved. Complementarity between the collected neutron and X-ray computed tomographies is shown and by applying both methods in concert we have observed lithium diffusion blocking by the LiCl protection layer and identified all cell components which are difficult to distinguish using one of the methods alone.
In this presentation we discuss the online monitoring of metallic AM parts produced by the Laser Powder Bed Fusion (LPBF) process by using optical, thermographic and electromagnetic methods. In a first approach we present the detection of defects generated during the process and discuss how to improve these methods for the optimization of design and production of metallic AM parts.
The evaluation of measurement uncertainty is essential for testing and calibration laboratories. This paper provides a general process description for the determination of the measurement uncertainty of quantitative data and its application to the conformity assessment with examples, and how to deal with the uncertainty of qualitative (Boolean) results, e. g. when "Alarm" or "No alarm" occours in an instrument display.