Wehrmacht - Verbrechen - Widerstand: Vier Beiträge zum nationalsozialistischen Weltanschauungskrieg

Vorbemerkung: „Die nachstehenden Beiträge gehen auf eine Vortragsreihe zurück, die im Sommer 2002 vom Hannah-Arendt-Institut zusammen mit der Stadt Leipzig und der Volkshochschule Leipzig im Rahmen des Begleitprogramms zur Ausstellung „Verbrechen der Wehrmacht. Dimensionen des Vernichtungskrieges 1941–1944“ organisiert wurde...

Bioactivity and corrosion behavior of magnesium barrier membranes

In the current research, magnesium and its alloys have been intensively studied as resorbable implant materials. Magnesium materials combine their good mechanical properties with bioactivity, which make them interesting for guided bone regeneration and for the application as barrier membranes. In this study, the in vitro degradation behavior of thin magnesium films was investigated in cell medium and simulated body fluid. Three methods were applied to evaluate corrosion rates: measurements of (i) the gaseous volume evolved during immersion, (ii) volume change after immersion, and (iii) polarization curves. In this comparison, measurements of H2 development in Dulbecco's modified Eagle's medium showed to be the most appropriate method, exhibiting a corrosion rate of 0.5 mm·year−1. Observed oxide and carbon contamination have a high impact on controlled degradation, suggesting that surface treatment of thin foils is necessary. The bioactivity test showed positive results; more detailed tests in this area are of interest

X‐ray microscopy and automatic detection of defects in through silicon vias in three‐dimensional integrated circuits

Through silicon vias (TSVs) are a key enabling technology for interconnection and realization of complex three-dimensional integrated circuit (3D-IC) components. In order to perform failure analysis without the need of destructive sample preparation, x-ray microscopy (XRM) is a rising method of analyzing the internal structure of samples. However, there is still a lack of evaluated scan recipes or best practices regarding XRM parameter settings for the study of TSVs in the current state of literature. There is also an increased interest in automated machine learning and deep learning approaches for qualitative and quantitative inspection processes in recent years. Especially deep learning based object detection is a well-known methodology for fast detection and classification capable of working with large volumetric XRM datasets. Therefore, a combined XRM and deep learning object detection workflow for automatic micrometer accurate defect location on liner-TSVs was developed throughout this work. Two measurement setups including detailed information about the used parameters for either full IC device scan or detailed TSV scan were introduced. Both are able to depict delamination defects and finer structures in TSVs with either a low or high resolution. The combination of a 0.4 objective with a beam voltage of 40 kV proved to be a good combination for achieving optimal imaging contrast for the full-device scan. However, detailed TSV scans have demonstrated that the use of a 20 objective along with a beam voltage of 140 kV significantly improves image quality. A database with 30,000 objects was created for automated data analysis, so that a well-established object recognition method for automated defect analysis could be integrated into the process analysis. This RetinaNet-based object detection method achieves a very strong average precision of 0.94. It supports the detection of erroneous TSVs in both top view and side view, so that defects can be detected at different depths. Consequently, the proposed workflow can be used for failure analysis, quality control or process optimization in R&D environments

Interplay of the forces governing steroid hormone micropollutant adsorption in vertically-aligned carbon nanotube membrane nanopores

Vertically-aligned carbon nanotube (VaCNT) membranes allow water to conduct rapidly at low pressures and open up the possibility for water purification and desalination, although the ultralow viscous stress in hydrophobic and low-tortuosity nanopores prevents surface interactions with contaminants. In this experimental investigation, steroid hormone micropollutant adsorption by VaCNT membranes is quantified and explained via the interplay of the hydrodynamic drag and friction forces acting on the hormone, and the adhesive and repulsive forces between the hormone and the inner carbon nanotube wall. It is concluded that a drag force above 2.2 × 10$^{−3}$ pN overcomes the friction force resulting in insignificant adsorption, whereas lowering the drag force from 2.2 × 10$^{−3}$ to 4.3 × 10$^{−4}$ pN increases the adsorbed mass of hormones from zero to 0.4 ng cm$^{−2}$. At a low drag force of 1.6 × 10$^{−3}$ pN, the adsorbed mass of four hormones is correlated with the hormone−wall adhesive (van der Waals) force. These findings explain micropollutant adsorption in nanopores via the forces acting on the micropollutant along and perpendicular to the flow, which can be exploited for selectivity