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Paper des Monats
- ja (27)
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). Also, two successful research project in collaboration with CAM2, Sweden are presented.
Gold-based nanoparticles below 2 nm in size are promising as luminescent probes for in vivo bioimaging, owing to their brightness and rapid renal clearance. However, their use as contrast agents in the near-infrared II (NIR-II, 1000–1700 nm) range remains challenging due to their low photoluminescence (PL) quantum yield. To address this, PL enhancement can be achieved by either rigidifying the ligand-shell structure or increasing the size of the ligand shell. In this study, we synthesized ultra-small gold nanoparticles stabilized by co-ligands, namely monothiol and short dithiol molecules. By precisely controlling the amount of reducing agent used during particle preparation, we successfully modulated the physicochemical properties of the co-ligand shell, including its size, composition, and structure. Consequently, we achieved a remarkable 60-fold increase in the absorption cross-section at 990 nm while maintaining the small size of the 1.5-nm metal core. The analytical and optical characterization of our thiol-capped gold nanoparticles indicates that the ligand shell size is governed by the quantity of the reducing agent, which, in turn, impacts the balance between radiative and non-radiative processes, thereby influencing the PL quantum yield.
Tailor-made nanoparticles are of increasing interest in e.g. catalysis, as sensor materials, analytical assays, or can have superior photophysical properties. A major issue concerning the preparation of high-quality and functional nanoparticles is a good control of particle size, shape, polydispersity, and composition.
Small Angle X-ray Scattering (SAXS) is a non-destructive method for the analysis of nanostructures in a wide variety of materials. This method allows determining averaged structural parameters on a length scale from just above atomic sizes up to several 100 nanometers such as sizes, size distributions, volume fractions, and inner surface sizes. Moreover, anomalous Small Angle X-ray Scattering (ASAXS) exploits the anomalous dispersion of the scattering amplitudes near the X-ray absorption edges of the elements contained in the sample. These element sensitive contrast variations can be used to analyse average composition fluctuations on the nm scale. Two kinds of nanoparticles are chosen here to elaborate the advantages of ASAXS in the analysis of complex materials.
A facile and efficient methodology is developed for the thermal synthesis of size-tunable, stable, and uniform bimetallic NiCu core–shell nanoparticles (NPs) for various application in catalysis. Their diameter can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio is adjustable in a wide range from 1:1 to 30:1. The NPs are structurally characterized by a method combination of transmission electron microscopy, anomalous small-angle X-ray scattering (ASAXS), X-ray absorption fine structure, and X-ray photoelectron spectroscopy. Here, we focus on the ASAXS method and its ability to analyses nanostructure parts and their compositions at once. As a result, a NiCu alloyed core surrounded by a Ni enriched shell and an outer NiO shell was found.
Semiconductor nanocrystals (quantum dots, QDs) are well known for their superior photophysical properties and enabled advancements in several key technologies of the 21st century and numerous technological applications like in photovoltaics, LED displays, photocatalysis, and biosensing. To achieve high photoluminescence quantum yields (PLQY) and enhanced photostability the QD core needs to be passivated by a second semiconductor, which possess a larger band gap to confine the charges within the QD core. An important parameter is thereby the lattice mismatch between the core and shell. To avoid strong lattice strain, which would alter the photophysical properties, an intermediary shell can be used as a lattice adapter between the core and the outer shell leading to core/shell/shell systems. These systems have shown to possess high PLQYs combined with a strong long-term stability and can be found in modern QLED displays. ASAXS was used here to better understand the core/shell/shell structure of InP/ZnSe/ZnS QDs to enable a correlation between their structural and photophysical properties.
Detaillierte Kenntnisse der elastischen Materialeigenschaften sind in vielen ingenieurtechnischen Bereichen von grundlegender Bedeutung. Insbesondere für die Anwendung von Predictive Maintenance und Structural- Health-Monitoring Methoden mit Ultraschall ist die genaue Kenntnis der elastischen Materialkonstanten eine Grundvoraussetzung. Die von den Herstellern zur Verfügung gestellten Angaben zu den elastischen Materialkonstanten, insbesondere für Polymere und faserverstärkte Kunststoffe, sind jedoch oft unzureichend, da diese vom Produktionsprozess abhängig sind und sich zusätzlich aufgrund von Materialabbauprozessen oder Ermüdung ändern können. In der Praxis liegen polymere Werkstoffe, faserverstärkte Kunststoffe und Metalle oft als dünne, plattenförmige Strukturen vor, in welchen sich geführte Ultraschallwellen (UGWs) ausbreiten können. In der aktuellen Forschung sind bereits verschiedene Neuronale Modelle zur Bestimmung der elastischen Konstanten und der Materialcharakterisierung mittels UGWs bekannt. Ein einfaches neuronales Netz, mit aus Dispersionsbildern extrahierten Werten für Frequenz und Wellenzahl ausbeutungsfähiger Moden als Eingabe, zur Vorhersage der elastischen Konstanten wird in verwendet. Ein rekurrentes Neuronales Netz mit einem Zeit-Frequenz Vektor als Eingabe wird in angewandt, während in ein 1D- Convolutional-Neuronal-Networks (CNN) unter Verwendung der zeitlichen Auslenkung der Grundmoden und in ein 2D-CNN unter Verwendung einer polaren Gruppengeschwindigkeitsdarstellung zur Bestimmung der elastischen Konstanten verwendet wird. In diesem Vortrag wird ein Ansatz zur Bestimmung der isotropen elastischen Konstanten von dünnen Platten auf der Grundlage von UGWs unter Verwendung von Dispersionsbildern und 2D-CNNs vorgestellt. Dispersionsabbildungen aus numerischen Simulationen werden mithilfe verschiedener Methoden vorverarbeitet, um realistische Messdaten zu simulieren. Mit den modifizierten Daten wird das Modell trainiert und die Architektur optimiert. Anschließend wird die Genauigkeit des erzeugten Modells mit realen Messdaten validiert. Es wird gezeigt, dass 2D-CNNs in der Lage sind, die isotropen elastischen Konstanten anhand multimodaler Merkmale aus Dispersionsbildern vorherzusagen, ohne dass eine anfängliche Schätzung der Parameter oder manuelle Merkmalsextraktion erforderlich ist.
This paper presents an automatic damage imaging technique by employing a signal processing approach based on applying hierarchically clustered filters across different domains. The technique involves time-frequency-wavenumber filter banks which are applied sequentially to ultrasonic guided wave (UGW) data. The study is conducted for a single lap joint composite specimen with a special focus on small voids which were formed due to manual adhesive component mixing. UGW data are acquired with a 3D Scanning Laser Doppler Vibrometer (LDV) over the scan area of the bonded plate. UGWs are excited at the central frequency of 100 kHz by a single piezoelectric transducer mounted on the surface of the single plate. Within each domain of time, frequency, and wavenumber, four filters are designed which results in 64 distinct filtered wavefields. From each filtered wavefield, an image is obtained by using root-mean-square (RMS) calculation of the signals. The obtained results are then combined to create a final, improved-resolution image of the scan area. The final image is compared to the image obtained through RMS calculation of full wavefield with interpolation through Delaunay triangulation and the image obtained by X-ray radiography. The results show that the smallest void that could be detected has a diameter of 2.14 mm.
Fungal pigments such as melanin and carotenoids are distinctive markers of animal and plant pathogenic fungi as well as their environmental relatives. These complex pigments play important roles in pathogenicity and stress tolerance while also being useful as biomarkers. Accordingly, it is important to be able to identify in situ the pigments in black fungi, a group of clinical and environmental importance. In this study, wild-type and genetically modified strains of Knufia petricola A95 and wild fungal cells attached to ancient rock were investigated for their spectroscopic and microscopic Raman features and morphological appearance. Knockout mutants of melanin synthesis genes pks1 (polyketide synthase), sdh1 (scytalone dehydratase), and both pks1 and the carotenoid synthesis gene phd1 (phytoene desaturase) were studied We applied two different Raman microscopes using two lasers, with 633 nm and 488 nm wavelengths. We analyzed and compared Raman spectra between the measured reference substances and the mutant and wild-type strains. In the wild strain WT:A95, the peaks close to melanin peals were found at 1353 cm−1 and 1611 cm−1. There are no characteristic melanin peaks at 1580–1600 cm−1 and around 1350 cm−1 at the spectrum of the Δpks1/Δphd1 mutant and the Δsdh1 mutant. The Δpks1 mutant spectrum has the peaks at the beta-carotene v2 C-C in-plane stretch at 1155 cm−1 and v3 C-CH3 deformation at 1005 cm−1. The peaks of carotenoids and melanin were found in all mutants and the wild strain, except the Δpks1/Δphd1 mutant. Raman spectra allow for discrimination between the various pigments. Hence, interactions between natural fungal melanin, as well as other protective pigments, and complex environmental matrices can be characterized on a range of spatial and temporal scales.
BAM (Federal Institute for Materials Research and Testing) is developing an electronic measurement system to be placed inside a waste drum, which will be filled with concrete. The goal of this measurement system is to monitor the process of hardening and the evolution of the concrete itself over time to indirectly identify potential defects such as corrosion or cracking. The measured parameters are humidity, temperature, and pressure. In this regard, particular attention was given to the design of the electronic board’s enclosure, to allow the sensors to measure the state of the concrete without being in direct contact with it. In the scope of the European Commission’s project of PREDIS, the supply of power to the battery-less sensors and the data acquired by such sensors are transmitted through the metallic waste drum by an innovative wireless technology developed by VTT (Technical Research Centre of Finland) in order to ensure long-term operation while keeping the integrity of the sealed container.
BAM is developing an electronic measurement system to be placed inside a waste drum, which will be filled with concrete. The goal of this measurement system is to monitor the process of hardening and the evolution of the concrete itself over time to indirectly identify potential defects such as corrosion or cracking. The measured parameters are humidity, temperature, and pressure. In this regard, particular attention was given to the design of the electronic board’s enclosure, to allow the sensors to measure the state of the concrete without being in direct contact with it. In the scope of the EU project PREDIS, the data acquired by such sensors are transmitted from inside to outside the metallic waste drum through wireless technology.
The sensing system is made of a chain of small sensing units, called SensorNodes. Each SensorNode includes two off-the-shelf sensors, one for relative humidity and temperature and one for pressure and temperature. A SensorNode is designed to have a unique identifier, in order to be connected to other units while being uniquely discoverable by a standard communication protocol. In this way, a distributed matrix of measurement points is created.
One of the most challenging tasks in designing a measurement system to run in a harsh environment (such as hardening concrete) is to let the sensors sense the external environment without damaging the sensor itself.
To keep the external environment away from the electronic board while still letting the sensors measure the concrete behavior, holes have been drilled through the lid and covered from the inside with a layer of a porous membrane. The membrane's pores allow water and gas particles to pass through and let the enclosed air equilibrate with the external environment.
With the help of the developed sensors, monitoring concrete in cemented waste drums will be possible. The derived data will also serve as the basis for ongoing modeling approaches for digital twins within the Predis project. Overall, the sensors provide a means of enabling safe nuclear waste management through advanced monitoring
Research on per- and polyfluoroalkyl substances (PFAS) frequently incorporates organofluorine measurements, particularly because they could support a class-based approach to regulation. However, standardized methods for organofluorine analysis in a broad suite of matrices are currently unavailable, including a method for extractable organofluorine (EOF) measured using combustion ion chromatography (CIC). Here, we report the results of an international interlaboratory comparison. Seven laboratories representing academia, government, and the private sector measured paired EOF and PFAS concentrations in groundwater and eel (Anguilla rostrata) from a site contaminated by aqueous film-forming foam. Among all laboratories, targeted PFAS could not explain all EOF in groundwater but accounted for most EOF in eel. EOF results from all laboratories for at least one replicate extract fell within one standard deviation of the interlaboratory mean for groundwater and five out of seven laboratories for eel. PFAS spike mixture recoveries for EOF measurements in groundwater and eel were close to the criterion (±30%) for standardized targeted PFAS methods. Instrumental operation of the CIC such as replicate sample injections was a major source of measurement uncertainty. Blank contamination and incomplete inorganic fluorine removal may introduce additional uncertainties. To elucidate the presence of unknown organofluorine using paired EOF and PFAS measurements, we recommend that analysts carefully consider confounding methodological uncertainties such as differences in precision between measurements, data processing steps such as blank subtraction and replicate analyses, and the relative recoveries of PFAS and other fluorine compounds.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of twodimensional ROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed
algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution
and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free twodimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.