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Paper des Monats
- ja (68)
Liquid-metal embrittlement (LME) of galvanized (Zn-coated) advanced high-strength steels is a long-known problem in materials science. Here we reveal the initial microstructural processes underneath the Zn-coating that lead to LME-microcrack initiation in the steel substrate. We track the microstructural evolution during the first tens of milliseconds and find pronounced signatures of Fe-Zn intermetallic precipitation in both ferrite grain boundaries and at internal ferrite-oxide phase boundaries. In concert with novel CALPHAD-integrated density-based thermodynamic modelling, we demonstrate that Zn-rich intermetallic phase-nucleation can occur at markedly low processing temperatures due to a segregation transition. We show that a small Znenrichment caused by Zn bulk-diffusion during the initial temperature rise in a joining process is sufficient to induce the segregation transition and subsequent nucleation of Fe-Zn intermetallic grain-boundary phases, which the experiments link to crack initiation sites. These findings direct focus onto LME-controlling microstructural and thermodynamic phenomena at temperatures below the ductility trough and the austenite formation temperature.
On the use of Carbograph 5TD as an adsorbent for sampling VVOCs: validation of an analytical method
(2023)
A standardised method for the analysis of very volatile organic compounds (VVOCs) in indoor air is still missing. This study evaluates the use of Carbograph 5TD as an adsorbent for 60 compounds (47 VVOCs + 13 VOCs) by comparing their recoveries with different spiking modes. The influence of the spiking of the tubes in dry nitrogen, humidified air or along the whole flushing duration mimicking real sampling was investigated. 49 substances (36 VVOCs from C1 to C6) had recoveries over 70% on the adsorbent in humidified air and were validated. The linearity of the calibration curves was verified for every spiking mode and the limits of detection (LOD) and quantification (LOQ) were determined. The LOQs were lower than the existing indoor air guideline values. The robustness of the method was considered by studying the influence of the sampling volume, the sampling flow rate, the humidity level and the storage of the tubes. In general, the most volatile or polar substances were the less robust ones. The combined measurement uncertainty was calculated and lies below 35% for a vast majority of the substances. An example of an emission chamber test using polyurethane foam is shown: Carbograph 5TD performs much better than Tenax® TA for VVOCs and emissions from n-butane were quantified with combined measurement uncertainty.
Corrosion monitoring of reinforced concrete structures:The DGZfP specification B12 Collaboration
(2023)
Corrosion monitoring of reinforced or prestressed concrete structures has becomeincreasingly important in recent years. Areas of application include componentsthat are no longer accessible after completion or where potential fieldmeasurements cannot be carried out due to existing coatings. Corrosion monitoringcan also be used to monitor the progress of corrosion in corroding systems, e.g. to prove the success of repair measures according to repair principle 8 in accordancewith EN 1504‐9 or repair method 8.3 in accordance with the DIBt repair guideline.It also could be used to prove the functionality of cathodic corrosion protectionsystems in accordance with ISO 12696. Despite the increasing importance ofcorrosion monitoring, no guidelines orrecommendations existed until 2018. Thisgap was closed by the English version of specification B12,“Corrosion Monitoringof Reinforced and Prestressed Concrete Structures,”of the German Society for Non‐Destructive Testing, which was published in 2021. This article introducesspecification B12 by explaining the basicmeasurement principles and illustratingthe potential of corrosion monitoring in new and existing buildings.
In recent years, in addition to the commonly known wire-based processes of Directed Energy Deposition using lasers, a process variant using the electron beam has also developed to industrial market maturity. The process variant offers particular potential for processing highly conductive, reflective or oxidation-prone materials. However, for industrial usage, there is a lack of comprehensive data on performance, limitations and possible applications. The present study bridges the gap using the example of the high-strength aluminum bronze CuAl8Ni6. Multi-stage test welds are used to determine the limitations of the process and to draw conclusions about the suitability of the parameters for additive manufacturing. For this purpose, optimal ranges for energy input, possible welding speeds and the scalability of the process were investigated. Finally, additive test specimens in the form of cylinders and walls are produced, and the hardness profile, microstructure and mechanical properties are investigated. It is found that the material CuAl8Ni6 can be well processed using wire electron beam additive manufacturing. The microstructure is similar to a cast structure, the hardness profile over the height of the specimens is constant, and the tensile strength
and elongation at fracture values achieved the specification of the raw material.
A new simplified and effective method has been formalised to estimate the Constant Amplitude Fatigue Limit (CAFL) of stress-relieved steel welded joints subjected to uniaxial push–pull loading and failing from the weld toe. Starting from the sharp V-notch assumption of the NSIF approach and the cyclic R-curve of the material in the heat affected zone, the proposed method identifies the CAFL as threshold level of the local stress field at the V-notched weld toe in the uncracked configuration. Such threshold stress field assures the crack arrest at the V-notched weld toe, according to the cyclic R-curve analysis. The method has been validated against experimental results and proved effective for a straightforward assessment of the CAFL of welded joints, as the stable crack propagation analysis of classical fracture mechanics approaches can be avoided.
A novel biomaterial comprising alginate dialdehyde-gelatine (ADA-GEL) hydrogel augmented by lysozyme loaded mesoporous cerium doped silica-calcia nanoparticles (Lys-Ce-MSNs) is 3D printed to create bioactive scaffolds. Lys-Ce-MSNs raise the mechanical stiffness of the hydrogel composite scaffold and induce surface apatite mineralization, when the scaffold is immersed in simulated body fluid (SBF). Moreover, the scaffolds can co-deliver bone healing (Ca and Si) and antioxidant ions (Ce), and Lys to achieve antibacterial (and potentially anticancer) properties. The nanocomposite hydrogel scaffolds can hold and deliver Lys steadily. Based on the in vitro results, the hydrogel nanocomposite containing Lys assured improved pre-osteoblast cell (MC3T3-E1) proliferation, adhesion, and differentiation, thanks to the biocompatibility of ADA-GEL, bioactivity of Ce-MSNs, and the stabilizing effect of Lys on the scaffold structure. On the other hand, the proliferation level of MG63 osteosarcoma cells decreased, likely due to the effect of Lys. Last but not least, cooperatively, alongside gentamicin (GEN), Lys brought about a proper antibacterial efficiency to the hydrogel nanocomposite scaffold against gram-positive and gram-negative bacteria. Taken together, ADA-GEL/Lys-Ce-MSN nanocomposite holds great promise for 3D printing of multifunctional hydrogel bone tissue engineering (BTE) scaffolds, able to induce bone regeneration, address infection, and potentially inhibit tumor formation and growth.
The increasing amount and complexity of clinical data require an appropriate way of storing and analyzing those data. Traditional approaches use a tabular structure (relational databases) for storing data and thereby complicate storing and retrieving interlinked data from the clinical domain. Graph databases provide a great solution for this by storing data in a graph as nodes (vertices) that are connected by edges (links). The underlying graph structure can be used for the subsequent data analysis (graph learning). Graph learning consists of two parts: graph representation learning and graph analytics. Graph representation learning aims to reduce high-dimensional input graphs to low-dimensional representations. Then, graph analytics uses the obtained representations for analytical tasks like visualization, classification, link prediction and clustering which can be used to solve domain-specific problems. In this survey, we review current state-of-the-art graph database management systems, graph learning algorithms and a variety of graph applications in the clinical domain. Furthermore, we provide a comprehensive use case for a clearer understanding of complex graph learning algorithms.
Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer.
The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements
The fundamental processes of nucleation and crystallization are widely observed in systems relevant to material synthesis and biomineralization; yet most often, their mechanism remains unclear. In this study, we unravel the discrete stages of nucleation and crystallization of Fe3(PO4)2·8H2O (vivianite). We experimentally monitored the formation and transformation from ions to solid products by employing correlated, time-resolved in situ and ex situ approaches. We show that vivianite crystallization occurs in distinct stages via a transient amorphous precursor phase. The metastable amorphous ferrous phosphate (AFEP) intermediate could be isolated and stabilized. We resolved the differences in bonding environments, structure, and symmetric changes of the Fe site during the transformation of AFEP to crystalline vivianite through synchrotron X-ray absorption spectroscopy at the Fe K-edge. This intermediate AFEP phase has a lower water content and less distorted local symmetry, compared to the crystalline end product vivianite. Our combined results indicate that a nonclassical, hydration-induced nucleation and transformation driven by the incorporation and rearrangement of water molecules and ions (Fe2+ and PO4 3−) within the AFEP is the dominating mechanism of vivianite formation at moderately high to low vivianite supersaturations (saturation index ≤ 10.19). We offer fundamental insights into the aqueous, amorphous-to-crystalline transformations in the Fe2+−PO4 system and highlight the different attributes of the AFEP, compared to its crystalline counterpart.
The ultrasonic echo technique is frequently used in non-destructive testing (NDT) of concrete structures for thickness measurements, geometry determinations as well as localization of built-in components. To improve ultrasonic imaging of complex structures in concrete, we transferred a geophysical imaging technique, the reverse time migration (RTM), to NDT in civil engineering. In contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, RTM is a wavefield continuation method in time and uses the full wave equation. Thus, RTM can handle complicated wave propagations in any direction without dip limitation. In this paper, we focused on the application and evaluation of a two-dimensional (2D) elastic RTM algorithm considering compressional waves, vertically polarized shear waves, and Rayleigh waves. We tested the elastic RTM routine on synthetic ultrasonic echo data generated with a 2D concrete model consisting of several steps and circular air inclusions. As these complex structures can often be found in real-world NDT use cases, their imaging is especially important. By using elastic RTM, we were able to clearly reproduce vertical reflectors and lower edges of circular air voids inside our numerical concrete model. Such structures cannot be imaged with conventional SAFT algorithms. Furthermore, the used elastic RTM approach also yielded a better reconstruction of a horizontal reflector and upper boundaries of circular air inclusions. Our encouraging results demonstrate that elastic RTM has the potential to significantly improve the imaging of complex concrete structures and, thus, is a step forward for detailed, high-quality ultrasonic NDT in civil engineering.
Multiscale modeling of linear elastic heterogeneous structures via localized model order reduction
(2023)
In this paper, a methodology for fine scale modeling of large scale linear elastic structures is proposed, which combines the variational multiscale method, domain decomposition and model order reduction. The influence of the fine scale on the coarse scale is modelled by the use of an additive split of the displacement field, addressing applications without a clear scale separation. Local reduced spaces are constructed by solving an oversampling problem with random boundary conditions. Herein, we inform the boundary conditions by a global reduced problem and compare our approach using physically meaningful correlated samples with existing approaches using uncorrelated samples. The local spaces are designed such that the local contribution of each subdomain can be coupled in a conforming way, which also preserves the sparsity pattern of standard finite element assembly procedures. Several numerical experiments show the accuracy and efficiency of the method, as well as its potential to reduce the size of the local spaces and the number of training samples compared to the uncorrelated sampling.
We analyse electromotive force measurements of concentration cells using non-equilibrium thermodynamics, and determine the transference coefficients of ion-exchange membranes in aqueous KCl solutions. By taking advantage of the analytical expression for the permselectivity, we extract transport coefficients with high accuracy. The transport number of K+ and the transference coefficient of water in the Selemion CMVN cationexchange membrane are found to be 100𝑡K+ = 99.59 ± 0.56 and 𝑡𝑤 = 3.69 ± 0.40 respectively, while for the Selemion AMVN anion-exchange membrane they are 100𝑡Cl− = 100.21 ± 0.37 and 𝑡𝑤 = −3.75 ± 0.27. These results suggest that the membranes are perfectly selective to the target ion, and that each ion carries 3-4 water molecules through the membrane, which reduces the membrane permselectivity. In these concentration cells, the electrical potential contribution of the membrane alone was more easily isolated with bare Ag/AgCl electrodes without reference solutions and liquid junction plugs. Additionally, we find a large contribution to the measured concentration cell voltage from concentration gradients across the porous plug of the reference electrode, which cannot be explained by Henderson’s equation alone. For most of the concentration range, the transport number of the porous plug is determined to be 100𝑡K+ = 49.43 ± 0.78 with negligible water transport, similar to literature values for bulk electrolyte. In dilute electrolyte solutions with concentrations below 0.1 mol kg−1, the plug shows anomalous behaviour consistent with an increase in K+ selectivity and water co-transport.
The stress–strain behavior of ceramics, such as aluminum titanate, has certain features that are unusual for brittle materials—in particular, a substantial nonlinearity under uniaxial tension, and load–unload hysteresis caused by the sharp increase of the incremental stiffness at the beginning of unloading. These features are observed experimentally and are attributed to microcracking. Here we compare different degrees of stress–strain nonlinearity of aluminum titanate materials and quantitatively model them. We use advanced mechanical testing to observe the mechanical response at room and high temperature; electron microscopy, and X-ray refraction radiography to observe the microstructural changes. Experiments show that two types of microcracks can be distinguished: (i) microcracks induced by cooling from the sintering temperature (due to heterogeneity and anisotropy of thermal expansion), with typical sizes of the order of grain size, and (ii) much larger microcracks generated by the mechanical loading. The two microcrack types produce different effects on the stress–strain curves. Such microcracks and the features of the stress–strain behavior depend on the density of the cooling-induced microcracks and on the distribution of grain sizes. They are modeled analytically and numerically.
Phase-sensitive optical time-domain reflectometry (jOTDR) is a technology for distributed vibration sensing, where vibration amplitudes are determined by recovering the phase of the backscattered light. Measurement noise induces phase errors, which degrades sensing performance. The phase errors, using a differentiation and cross-multiplication (DCM) algorithm, are investigated theoretically and experimentally in a jOTDR system based on a phase retrieval configuration consisting of an imbalanced Mach–Zehnder interferometer (IMZI) and a 3 x 3 coupler. Analysis shows that phase error is highly dependent on the AC component of the obtained signal, essentially being inversely proportional to the product of the power of the light backscattered from two locations. An analytical expression was derived to estimate the phase error and was confirmed by experiment. When applied to the same measurement data, the error is found to be slightly smaller than that obtained using in-phase/quadrature (I/Q) demodulation. The error, however, increases for longer measurement times.
The application of anti-corrosion coated, high-strength steels in the automotive industry has increased in recent years. In combination with various zinc-based surface coatings, liquid metal embrittlement cracking can be observed in some of these materials. A high-quality, crack-free spot-welded joint is essential to realize the lightweight potential of the materials. In this work, the LME susceptibility of different coatings, which will be determined by the crack length and the occurrence rate, will be investigated using a welding under external load setup. The uncoated specimens did not show any LME. EG, GI and GA showed significantly less LME than ZM coatings. The latter coatings showed much larger crack lengths than the EG, GI and GA coatings. Furthermore, two mechanisms regarding the LME occurrence rate were observed: the occurrence of LME in zinc–magnesium coatings was theorized to be driven by the material properties of the coatings, whereas the occurrence of LME at EG, GI and GA samples was forced mainly by the application of the external tensile load.
In the experimental setup of this work, the materials were exposed to unusually high mechanical loads (up to 80% of their yield strength) to evoke LME cracks.
This study describes an interlaboratory comparison (ILC) among nine (9) laboratories to evaluate and validate the standard operation procedure (SOP) for single-particle (sp) ICP-TOFMS developed within the context of the Horizon 2020 project ACEnano. The ILC was based on the characterization of two different Pt nanoparticle (NP) suspensions in terms of particle mass, particle number concentration, and isotopic composition. The two Pt NP suspensions were measured using icpTOF instruments (TOFWERK AG, Switzerland).
Two Pt NP samples were characterized and mass equivalent spherical sizes (MESSs) of 40.4 ± 7 nm and 58.8 ± 8 nm were obtained, respectively. MESSs showed <16% relative standard deviation (RSD) among all participating labs and <4% RSD after exclusion of the two outliers. A good agreement was achieved between the different participating laboratories regarding particle mass, but the particle number concentration results were more scattered, with <53% RSD among all laboratories, which is consistent with results from previous ILC studies conducted using ICP-MS instrumentation equipped with a sequential mass spectrometer. Additionally, the capabilities of sp-ICP-TOFMS to determine masses on a particle basis are discussed with respect to the potential for particle density determination. Finally, because quasi-simultaneous multi-isotope and multielement determinations are a strength of ICP-TOFMS instrumentation, the precision and trueness of isotope ratio determinations were assessed. The average of 1000 measured particles yielded a precision of below ±1% for intensity ratios of the most abundant Pt isotopes, i.e. 194Pt and 195Pt, while the accuracy of isotope ratios with the lower abundant isotopes was limited by counting statistics.
Per- and polyfuoroalkyl substances (PFAS) are emerging organic pollutants and can occur in surface and groundwater. To identify the degree of pollution in surface water with PFAS, often targeted HPLC–ESI–MS/MS has been employed in which commonly 30–40 compounds are analyzed. However, other PFAS and organofuorines remain undetected. We sampled surface water of the river Spree and the Teltow Canal in Berlin, Germany, which are afected by the efuent discharge of wastewater treatment plants. Here, we employed high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) for measuring extractable organofuorines (EOF) and compared in a mass balance approach the total fuorine to the identifed and quantifed PFAS from the targeted analysis. The analysis highlights that the EOF are in the range expected for an urban river system (Winchell et al. in Sci Total Environ 774, 2021). However, downstream of an efuent discharge, the EOF increased by one order of magnitude, e.g., 40.3 to 574 ng F L−1, along the Teltow Canal. From our target analytes, mostly short-chained perfuorinated carboxylic acids and sulfonates occur in the water, which however makes up less than 10% of the EOF. The increase in EOF in the Teltow Canal correlates well with the increase of perfuorohexanoic acid (PFHxA), indicating that PFHxA is characteristic for the discharged EOF but not responsible for the increase. Hence, it points to PFHxA precursor discharge. The study highlights that EOF screening using HR-CS-GFMAS is necessary to identify the full scale of pollution with regard to PFAS and other organofuorines such as pharmaceutical compounds from the efuent of WWTPs.
Immunoassays, based on the recognition and capture of analytes by highly selective antibodies, are now used extensively in all areas of diagnostics, but the challenge is to further integrate them into online sensors. To improve the transition from laboratory immunoassays to immunosensors, we have developed a complete flow system, based on a microfluidic core flow cell to enable automated detection of one of the most commonly used immunoassay substrates, TMB, by chronoamperometry. The architecture and fluidic optimisation of the system showed that a specially designed 3D flow cell allows higher flow rates (500 μL min−1) than a standard enlarged microfluidic channel (50 μL min−1) resulting in a significantly shorter detection time of 30 seconds per sample and making the system more robust against interferences due to bubble formation in the chip. The electrochemical measurements showed an improved signal-to-noise ratio (SNR) and thus higher sensitivity for a model immunoassay for diclofenac (SNR = 59), compared to the analytical performance of a conventional laboratory microplate-based assay with optical detection (SNR = 19). In general, this system facilitates the conversion of any conventional immunoassay into an immunosensor with automatic and continuous detection.
This paper presents reported machine learning approaches in the field of Brillouin distributed fiber optic sensors (DFOSs). The increasing popularity of Brillouin DFOSs stems from their capability to continuously monitor temperature and strain along kilometer-long optical fibers, rendering them attractive for industrial applications, such as the structural health monitoring of large civil infrastructures and pipelines. In recent years, machine learning has been integrated into the Brillouin DFOS signal processing, resulting in fast and enhanced temperature, strain, and humidity measurements without increasing the system’s cost. Machine learning has also contributed to enhanced spatial resolution in Brillouin optical time domain analysis (BOTDA) systems and shorter measurement times in Brillouin optical frequency domain analysis (BOFDA) systems. This paper provides an overview of the applied machine learning methodologies in Brillouin DFOSs, as well as future perspectives in this area.