In the present paper, as part of an interdisciplinary research project (Priority Programme SPP2045), we propose a possible way to design an open access archive for particle-discrete tomographic datasets: the PARROT database (https://parrot.tu-freiberg.de). This archive is the result of a pilot study in the field of particle technology and three use cases are presented for illustrative purposes. Instead of providing a detailed instruction manual, we focus on the methodologies of such an archive. The presented use cases stem from our working group and are intended to demonstrate the advantage of using such an archive with concise and consistent data for potential and ongoing studies. Data and metadata merely serve as examples and need to be adapted for disciplines not concerned here. Since all datasets within the PARROT database and its source code are freely accessible, this study represents a starting point for similar projects.

A two-step framework to analyze local microstructure variations of paper sheets based on 3D image data is presented. First, a multi-stage workflow efficiently acquires a large set of highly resolved tomographic image data, which enables—in combination with statistical image analysis—the quantification of local variations and pairwise correlations of morphological microstructure characteristics on length scales ranging from micrometers to centimeters. Secondly, the microstructure is analyzed in terms of the local behavior of porosity, thickness, and further descriptors related to transportation paths. The power of the presented framework is demonstrated, showing that it allows one (i) to quantitatively reveal the difference in terms of local structural variations between a model paper before and after unidirectional compression via hard-nip calendering and that (ii) the field of view which is required to reliably compute the probability distributions of the considered local microstructure characteristics is at least 20 mm$^{2}$. The results elucidate structural differences related to local densification. In particular, it is shown how calendering transforms local variations in sheet thickness into marked local mass density variations. The obtained results are in line with experimental measurements of macroscopic properties (basis weight, Bekk smoothness parameters, thickness, and Gurley retention times).

Identifying the fate of birds’ nests and the causes of breeding failure is often crucial for the development of conservation strategies for threatened species. However, collecting these data by repeatedly visiting nests might itself contribute to nest failure or bias. To solve this dilemma, automatic cameras have increasingly been used as a time-efficient means for nest monitoring. Here, we consider whether the use of cameras itself may influence hatching success of nests of the Black-tailed Godwit Limosa limosa at two long-term study sites in northern Germany. Annually between 2013 and 2019, cameras were used to monitor godwit nests. In 2014 and 2019, nests were randomly equipped with cameras or not, and nest survival checked independently of the cameras. Nest-survival models indicated that survival probabilities varied between years, sites and with time of the season, but were unaffected by the presence of cameras. Even though predation is the main cause of hatching failure in our study system, we conclude that predators did not learn to associate cameras with food either when the cameras were initially installed or after they had been used for several years. Cameras were thus an effective and non-deleterious tool to collect data for conservation in this case. As other bird species may react differently to cameras at their nests, and as other sets of predators may differ in their ability to associate cameras with food, the effect of cameras on breeding success should be carefully monitored when they are used in a new study system.

The three-dimensional characterization of distributed particle properties in the micro- and nanometer range is essential to describe and understand highly specific separation processes in terms of selectivity and yield. Both performance measures play a decisive role in the development and improvement of modern functional materials. In this study, we mixed spherical glass particles (0.4–5.8 μm diameter) with glass fibers (diameter 10 μm, length 18–660 μm) to investigate a borderline case of maximum difference in the aspect ratio and a significant difference in the characteristic length to characterize the system over several size scales. We immobilized the particles within a wax matrix and created sample volumes suitable for computed tomographic (CT) measurements at two different magnification scales (X-ray micro- and nano-CT). Fiber diameter and length could be described well on the basis of the low-resolution micro-CT measurements on the entire sample volume. In contrast, the spherical particle system could only be described with sufficient accuracy by combining micro-CT with high-resolution nano-CT measurements on subvolumes of reduced sample size. We modeled the joint (bivariate) distribution of fiber length and diameter with a parametric copula as a basic example, which is equally suitable for more complex distributions of irregularly shaped particles. This enables us to capture the multidimensional correlation structure of particle systems with statistically representative quantities.

Far-field three-dimensional X-ray diffraction microscopy allows for quick measurement of the centers of mass and volumes of a large number of grains in a polycrystalline material, along with their crystal lattice orientations and internal stresses. However, the grain boundaries—and, therefore, individual grain shapes—are not observed directly. The present paper aims to overcome this shortcoming by reconstructing grain shapes based only on the incomplete morphological data described above. To this end, cross-entropy (CE) optimization is employed to find a Laguerre tessellation that minimizes the discrepancy between its centers of mass and cell sizes and those of the measured grain data. The proposed algorithm is highly parallel and is thus capable of handling many grains (>8,000). The validity and stability of the CE approach are verified on simulated and experimental datasets.

In this paper, prediction models are proposed which allow the mineralogical characterization of particle systems observed by X-ray micro tomography (XMT). The models are calibrated using 2D image data obtained by a combination of scanning electron microscopy and energy dispersive X-ray spectroscopy in a planar cross-section of the XMT data. To reliably distinguish between different minerals the models are based on multidimensional distributions of certain particle characteristics describing, for example, their size, shape, and texture. These multidimensional distributions are modeled using parametric Archimedean copulas which are able to describe the correlation structure of complex multidimensional distributions with only a few parameters. Furthermore, dimension reduction of the multidimensional vectors of particle characteristics is utilized to make non-parametric approaches such as the computation of distributions via kernel density estimation viable. With the help of such distributions the proposed prediction models are able to distinguish between different types of particles among the entire XMT image.

In this paper, three-dimensional (3D) image data of ore particle systems is investigated. By combining X-ray microtomography with scanning electron microscope (SEM)-based image analysis, additional information about the mineralogical composition from certain planar sections can be gained. For the analysis of tomographic images of particle systems the extraction of single particles is essential. This is performed with a marker-based watershed algorithm and a post-processing step utilizing a neural network to reduce oversegmentation. The results are validated by comparing the 3D particle-wise segmentation empirically with 2D SEM images, which have been obtained with a different imaging process and segmentation algorithm. Finally, a stereological application is shown, in which planar SEM images are embedded into the tomographic 3D image. This allows the estimation of local X-ray attenuation coefficients, which are material-specific quantities, in the entire tomographic image.

The two high-pressure water-retaining dams at the Ibbenbüren coalmine in Münsterland (Germany) have to perform reliably under the induced tension caused by further exploitation of the current mining area. The load-bearing and the sealing functions of the new barriers were separated and new sealing materials were developed. An innovative multilayer sealing system of bentonite and sandwiched equipotential layers (SANDWICH) supporting homogeneous swelling and sealing, independent of formation water (Nüesch et al., 2002), was applied in this project. A testing program of strain-controlled swelling pressure tests on compacted bentonite specimens and on a bentonite/sand mixture was conducted to ensure an adequate potential for swelling-pressure development.

The measurements under constant volume for dry densities between 1.45 g/cm3 and 1.67 g/cm3 showed an evolving swelling pressure between 1.04 and 1.8 MPa for 100% bentonite samples. Straincontrolled oedometer tests for zero strain and step-wise applied strain up to 2% revealed that a sufficient magnitude of swelling pressure existed at maximum applied strain.

Composite magnetoelectrics implemented as thin film heterostructures are discussed in view of their applicability as highly sensitive magnetic field sensors. Here, either PZT or AlN served as piezoelectric component. The magnetostrictive phase consisted of layer systems based on FeCo or (Fe90Co10)78Si12B10. All functional layers were deposited with thicknesses of a few micrometers on Si cantilever structures with typical lateral dimensions of 25 mm by 2.2 mm. Magnetoelectric coefficients as large as 6900 V/cm Oe and a limit of detection as low as 1 pT/(Hz)1/2 were measured. Currently, the best result demonstrates a detection limit of 500 fT/(Hz)1/2 at 958 Hz frequency using a set of two sensors for external noise suppression. A frequency conversion technique is proposed to broaden the applicability of resonant magnetoelectric sensors to a wider frequency range. Finally, the achieved sensor performance is evaluated with regard to typical magnetic field amplitudes in medical applications.

Dialectometric intensity estimation as introduced in Rumpf etal. (2009) and Pickl and Rumpf (2011, 2012) is a method for the unsupervised generation of maps visualizing geolinguistic data on the level of linguistic variables. It also extracts spatial information for subsequent statistical analysis. However, as intensity estimation involves geographically conditioned smoothing, this method can lead to undesirable results. Geolinguistically relevant structures such as rivers, political borders or enclaves, for instance, are not taken into account and thus their manifestations in the distributions of linguistic variants are blurred. A possible solution to this problem, as suggested and put to the test in this paper, is to use linguistic distances rather than geographical (Euclidean) distances in the estimation. This methodological adjustment leads to maps which render geolinguistic distributions more faithfully, especially in areas that are deemed critical for the interpretation of the resulting maps and for subsequent statistical analyses of the results.

The presence of elongation, streak and blurring artifacts in tomograms recorded under a missing wedge of rotation angles presents a major challenge for the quantitative analysis of tomographic image data. We show that the missing wedge artifacts of standard reconstruction algorithms may be reduced by the innovative reconstruction technique DIRECTT. For the comparison of missing wedge artifacts we apply techniques from spatial statistics, which have been specifically designed to investigate the shape of phase boundaries in tomograms.

We have recently presented a novel method for a complete thermoelectric characterization [J. de Boor, V. Schmidt. Adv. Mater. 22:4303, (2010)]. This method is based on the well-known electrical van der Pauw method and allows measurement of the electrical and thermal conductivity, the Seebeck coefficient and the thermoelectric figure of merit. After a short review of this method we will discuss the systematic measurement errors of the method. It turns out that radiative heat loss can affect the thermal conductivity measurement significantly. We will give a simple estimation for the relative error due to radiation losses and discuss error minimizing strategies.