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By means of synchrotron X-ray computed tomography, model composites consisting of silica and styrenebutadiene rubber were studied with a very high spatial resolution. By our analysis technique we were able to determine the nano- and micro dispersion from the experimental results by our numerical analysis. These results are discussed with respect to crucial advantages of the generically 3-dimensional tomography technique as compared to 2-dimensional methods. Our quantitative analysis of the 3d images demonstrates that in the case of our model composites the filler dispersion is good, independent on the filler concentration. Our new 3-dimensional results evidence that considering only 2-d pictures may lead to ambiguities that can lead to wrong conclusions.
A surface-labeled lyophilized lymphocyte (sLL) preparation has been developed using human peripheral blood mononuclear cells prelabeled with a fluorescein isothiocyanate conjugated anti-CD4 monoclonal antibody. The sLL preparation is intended to be used as a reference material for CD4+ cell counting including the development of higher order reference measurement procedures and has been evaluated in the pilot study CCQM-P102. This study was conducted across 16 laboratories from eight countries to assess the ability of participants to quantify the CD4+ cell count of this reference material and to document cross-laboratory variability plus associated measurement uncertainties. Twelve different flow cytometer platforms were evaluated using a standard protocol that included calibration beads used to obtain quantitative measurements of CD4+ T cell counts. There was good overall cross-platform and counting method agreement with a grand mean of the laboratory calculated means of (301.7 ± 4.9) µL-1 CD4+ cells. Excluding outliers, greater than 90% of participant data agreed within ±15%. A major contribution to variation of sLL CD4+ cell counts was tube to tube variation of the calibration beads, amounting to an uncertainty of 3.6%. Variation due to preparative steps equated to an uncertainty of 2.6%. There was no reduction in variability when data files were centrally reanalyzed. Remaining variation was attributed to instrument specific differences. CD4+ cell counts obtained in CCQM-P102 are in excellent agreement and show the robustness of both the measurements and the data analysis and hence the suitability of sLL as a reference material for interlaboratory comparisons and external quality assessment.
Adhesion measurements are presented which were carried out with an atomic force microscope between polymer balls attached to a cantilever and a silicon wafer under ultra high vacuum conditions. In using a silicon surface with a defined structure a correlation between adhesion force and contact area was found. This correlation could partly be explained by the Johnson-Kendall-Roberts model, if a change of the surface energy is assumed as a result of the structuring. For a constant geometric contact area an additional structuring leads to a decrease of the adhesion force.
Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a machine learning (ML) approach for automated damage detection, based on an ML toolbox for industrial condition monitoring. The toolbox combines multiple complementary algorithms for feature extraction and selection and automatically chooses the best combination of methods for the dataset at hand. Here, this toolbox is applied to a guided wave-based SHM dataset for varying temperatures and damage locations, which is freely available on the Open Guided Waves platform. A classification rate of 96.2% is achieved, demonstrating reliable and automated damage detection. Moreover, the ability of the ML model to identify a damaged structure at untrained damage locations and temperatures is demonstrated.
The existence of microbial activity hotspots in temperate regions of Earth is driven by soil heterogeneities, especially the temporal and spatial availability of nutrients. Here we investigate whether microbial activity hotspots also exist in lithic microhabitats in one of the most arid regions of the world, the Atacama Desert in Chile. While previous studies evaluated the total DNA fraction to elucidate the microbial communities, we here for the first time use a DNA separation approach on lithic microhabitats, together with metagenomics and other analysis methods (i.e., ATP, PLFA, and metabolite analysis) to specifically gain insights on the living and potentially active microbial community. Our results show that hypolith colonized rocks are microbial hotspots in the desert environment. In contrast, our data do not support such a conclusion for gypsum crust and salt rock environments, because only limited microbial activity could be observed. The hypolith community is dominated by phototrophs, mostly Cyanobacteria and Chloroflexi, at both study sites. The gypsum crusts are dominated by methylotrophs and heterotrophic phototrophs, mostly Chloroflexi, and the salt rocks (halite nodules) by phototrophic and halotolerant endoliths, mostly Cyanobacteria and Archaea. The major environmental constraints in the organic-poor arid and hyperarid Atacama Desert are water availability and UV irradiation, allowing phototrophs and other extremophiles to play a key role in desert ecology.
The superior properties of high-entropy multi-functional materials are strongly connected with their atomic heterogeneity through many different local atomic interactions. The detailed element-specific studies on a local scale can provide insight into the primary arrangements of atoms in multicomponent systems and benefit to unravel the role of individual components in certain macroscopic properties of complex compounds. Herein, multi-edge X-ray absorption spectroscopy combined with reverse Monte Carlo simulations was used to explore a homogeneity of the local crystallographic ordering and specific structure relaxations of each constituent in the equiatomic single-phase facecentered cubic CrMnFeCoNi high-entropy alloy at room temperature. Within the considered fitting approach, all five elements of the alloy were found to be distributed at the nodes of the fcc lattice without any signatures of the additional phases at the atomic scale and exhibit very close statistically averaged interatomic distances (2.54 – 2.55 Å) with their nearest-neighbors. Enlarged structural displacements were found solely for Cr atoms. The macroscopic magnetic properties probed by conventional magnetometry demonstrate no opening of the hysteresis loops at 5 K and illustrate a complex character of the long-range magnetic order after field-assisted cooling in ± 5 T. The observed magnetic behavior is assigned to effects related to structural relaxations of Cr. Besides, the advantages and limitations of the reverse Monte Carlo approach to studies of multicomponent systems like high-entropy alloys are highlighted.
The maximum magnetisation (saturation magnetisation) obtainable for iron oxide nanoparticles can be increased by doping the nanocrystals with non-magnetic elements such as zinc. Herein, we closely study how only slightly different synthesis approaches towards such doped nanoparticles strongly influence the resulting sub-nano/atomic structure. We compare two co-precipitation approaches, where we only vary the base (NaOH versus NH3), and a thermal decomposition route. These methods are the most commonly applied ones for synthesising doped iron oxide nanoparticles. The measurable magnetisation change upon zinc doping is about the same for all systems. However, the sub-nano structure, which we studied with Mössbauer and X-ray absorption near edge spectroscopy, differs tremendously. We found evidence that a much more complex picture has to be drawn regarding what happens upon Zn doping compared to what textbooks tell us about the mechanism. Our work demonstrates that it is crucial to study the obtained structures very precisely when “playing” with the atomic order in iron oxide nanocrystals.
Für die Berechnung des Crashverhaltens von Fahrzeugstrukturen muss zusätzlich zur Dehnratenabhängigkeit des plastischen Verformungsverhaltens des Grundwerkstoffs auch das Verhalten von Fügestellen bei hoher Beanspruchungsgeschwindigkeit bestimmt werden. Ziel der VDEh-Arbeitsgruppe 'Hochgeschwindigkeitszugversuche an gefügten Stählen' war die Erstellung eines Stahl-Eisen-Prüfblattes (SEP) zur Ermittlung crashrelevanter Kennwerte für gefügte Stahl-Feinbleche unter vereinheitlichten Prüfbedingungen. Zur Erarbeitung der in dieser Richtlinie zu formulierenden Empfehlungen wurden Scherzugversuche bei hoher Geschwindigkeit an punktgeschweißten und lasergeschweißten Proben von elf Prüflaboratorien durchgeführt. Der Beitrag beschreibt die Ergebnisse dieses Ringversuchs und seine Auswirkungen auf das SEP.