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Paper des Monats
- ja (68)
Solid wastewater-based fertilizers were screened for per- and polyfluoroalkyl substances (PFAS) by the extractable organic fluorine (EOF) sum parameter method. The EOF values for ten sewage sludges from Germany and Switzerland range from 154 to 7209 mg kg−1. For thermal treated sewage sludge and struvite the EOF were lower with values up to 121 mg kg−1. Moreover, the application of PFAS targeted
and suspect screening analysis of selected sewage sludge samples showed that only a small part of the EOF sum parameter values can be explained by the usually screened legacy PFAS. The hitherto unknown part of EOF sum parameter contains also fluorinated pesticides, pharmaceutical and aromatic compounds. Because these partly fluorinated compounds can degrade to (ultra-)short PFAS in wastewater treatment plants they should be considered as significant sources of organic fluorine in the environment. The combined results of sum parameter analysis and suspect screening reveal the need to update current regulations, such as the German fertilizer ordinance, to focus not solely on a few selected PFAS such as perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) but
consider an additional sum parameter approach as a more holistic alternative. Moreover, diffusion gradient in thin-films (DGT) passive samplers were utilized as an alternative simplified extraction method for PFAS in solid wastewater-based fertilizers and subsequently quantified via combustion ion chromatography. However, the DGT method was less sensitive and only comparable to the EOF values
of the fertilizers in samples with >150 mg kg−1, because of different diffusion properties for various PFAS, but also kinetic exchange limitations.
Abstract: Increasing demand for sustainable, resilient, and low-carbon construction materials has highlighted the potential of Compacted Mineral Mixtures (CMMs), which are formulated from various soil types (sand, silt, clay) and recycled mineral waste. This paper presents a comprehensive inter- and transdisciplinary research concept that aims to industrialise and scale up the adoption of CMM-based construction materials and methods, thereby accelerating the construction industry’s systemic transition towards carbon neutrality. By drawing upon the latest advances in soil mechanics, rheology, and automation, we propose the development of a robust material properties database to inform the design and application of CMM-based materials, taking into account their complex, time-dependent behaviour. Advanced soil mechanical tests would be utilised to ensure optimal performance under various loading and ageing conditions. This research has also recognised the importance of context-specific strategies for CMM adoption. We have explored the implications and limitations of implementing the proposed framework in developing countries, particularly where resources may be constrained. We aim to shed light on socio-economic and regulatory aspects that could influence the adoption of these sustainable construction methods. The proposed concept explores how the automated production of CMM-based wall elements can become a fast, competitive, emission-free, and recyclable alternative to traditional masonry and concrete construction techniques.
We advocate for the integration of open-source digital platform technologies to enhance data accessibility, processing, and knowledge acquisition; to boost confidence in CMM-based technologies; and to catalyse their widespread adoption. We believe that the transformative potential of this research necessitates a blend of basic and applied investigation using a comprehensive, holistic, and transfer-oriented methodology. Thus, this paper serves to highlight the viability and multiple benefits of CMMs in construction, emphasising their pivotal role in advancing sustainable development and resilience in the built environment.
Laser-induced breakdown spectroscopy (LIBS) is becoming a more mature technology every year with new variants such as laser ablation molecular isotopic spectrometry, reheating by various discharge techniques, and multiple pulse excitation schemes, in which sometimes lasers of different pulse lengths are used. However, lasers with inherent parameters like pulse length and repetition rate are still almost exclusively employed. Recent years have witnessed the advent of novel high-repetition-rate laser concepts for machining processes, like welding, milling, and engraving. Here, a comprehensive study of single-pulse LIBS spectra of a single aluminum target is presented to showcase the applicability of flexible high duty-cycle master oscillator power amplifier (MOPA) lasers. Although traditional flashlamp-pumped Fabry–Pérot lasers only permit a variation in the pulse energy and are operated at very low duty-cycles, MOPA lasers add repetition rate and pulse length as variable parameters. A thorough analysis of the temporal plasma behavior revealed the emission dynamic to closely match the excitation laser pulse pattern. An aluminum sample’s spectral response was shown to be significantly impacted by variations in both rate and length. Although the spectral emission strength of the elemental lines of Al, Sr, and Ca all peaked at slightly different parameter settings, the strongest impact was found on the relative abundance of molecular AlO bands. Unlike in previous laser ablation molecular isotopic spectrometry (LAMIS) publications, the latter could be readily detected with a good intensity and well-resolved spectral features without any temporal gating of the detector. This finding, together with the fact that MOPA lasers are both inexpensive and dependable, makes for a promising combination for future studies including the detection of diatomic band structures.
A major advantage in the reassessment of existing structures is the possibility of including measured data that describe the actual properties and the current condition of the structure to be reassessed. Currently, the incorporation of such measured information is mostly unregulated. However, the use of measurement results is vitally important, since a measured data-based improvement of the computation models level of approximation can lead at least to more meaningful results, possibly to extended remaining life times of the structure and in the best case to a saving of resources. Conversely, not appreciating well measurable and relevant information can be equated with a waste of resources. In this paper, a concept for the comparable use of non-destructively measured data as basic variables in probabilistic reliability assessments is outlined and examined using a typical prestressed concrete road bridge as a case-study. An essential requirement is the calculation of measurement uncertainties in order to evaluate the quality of the measurement results comparably. In conclusion, the example of ultrasonic and radar measurement data is used to demonstrate the effects that the incorporation of the measured information has on the reliability of the structure.
In this study, the wavefield radiated from a building to its surroundings is identified and extracted from M4.6 earthquake recordings collected by sensors installed in a building and on the nearby athletic field in Matera (Italy) using a new approach for soil-structure interaction assessment. The proposed approach for earthquake data analysis combines in an innovative way two methods already used in seismology and engineering seismology: deconvolution and polarization analysis. The approach enables the identification, reconstruction, and characterization of the wavefield radiated from a vibrating building into its surroundings, and the estimation of the amount of energy associated with it. The approach consists of four steps: estimation of the resonant frequencies of the building, deconvolution of the earthquake recordings from a building and its surroundings, identification of the seismic phases, reconstruction of the signal transmitted from the building to its surroundings, and estimation of its energy, and polarization analysis. Analysis of recordings of the M4.6 event highlighted that the motion related to the wavefield radiated from the building to the ground was mostly linearly polarized in the radial and transverse planes, while a clear ellipticity was observed only in the horizontal plane. The wavefield radiated from the building might be dominated by unconventionally polarized surface waves, i.e., quasi-Rayleigh waves or a combination of quasi-Rayleigh and quasi-Love waves. The results indicated that the energy transmitted from the analyzed vibrating building to its surroundings was significant and decreased the ground motion shaking due to the out-of-phase motion.
An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning of material properties. Such chemical bonding information can be computed using the LOBSTER software package, which post-processes modern density functional theory data by projecting the plane wave-based wave functions onto an atomic orbital basis. With the help of a fully automatic workflow, the VASP and LOBSTER software packages are used to generate the data. We then perform bonding analyses on 1520 compounds (insulators and semiconductors) and provide the results as a database. The projected densities of states and bonding indicators are benchmarked on standard density-functional theory computations and available heuristics, respectively. Lastly, we illustrate the predictive power of bonding descriptors by constructing a machine learning model for phononic properties, which shows an increase in prediction accuracies by 27% (mean absolute errors) compared to a benchmark model differing only by not relying on any quantum-chemical bonding features.
Weather-dependent passive thermography and thermal simulation of in-service wind turbine blades
(2023)
. To cope with the increase in the manufacturing and operation of wind turbines, wind farm operators need inspection tools that are able to provide reliable information while keeping the downtime low. Current inspection techniques require to stop the wind turbine. This work presents the current progress in the project EvalTherm, in which passive thermography is evaluated as a possible non-destructive inspection tool for operational wind turbine blades (WTBs). A methodology to obtain thermal images of rotating WTBs has been established in this project. However, the quality of the results is heavily dependent on various aspects such as weather conditions, information on the inspected WTB, damage history, etc. In this work, a section of a used WTB is simulated using finite-element modelling (FEM) as well as experimentally tested for evaluating the accuracy of the model. Such a model will provide insight into the potential thermal response of a certain structure (with specific material properties) in given weather (boundary) conditions. The model is able to provide satisfactory predictions of the thermal response of the structure, as well as indicate what thermal contrast(s) result from artificial defects introduced in the structure.
Reliability assessment of existing concrete bridges with geometrical NDT results - Case studies
(2023)
The results of and the validity in reliability assessment of existing bridges essentially depend on the information available about the considered system. Information about the actual condition as well as structural and material characteristics can be observed on-site to refine the computation models used in assessment. Non-destructive testing (NDT) methods for concrete structures are capable of reconstructing missing, questioned, or inconsistent as-built plans. This contribution summarizes recent developments within the scope of the national pre-standardization project “ZfPStatik”, which aims to prepare a guideline about NDT-supported structural analyses. The focus is on the purposeful and explicit utilization of geometrical tendon and reinforcement bar positions (measured on-site using the ultrasound echo and ground penetrating radar (GPR) techniques) in probabilistic reliability analyses — shown by means of real case studies. The well-established first order reliability method is applied to different concrete bridges, which are typical for the German road bridge stock, to demonstrate the utility of incorporating quality-evaluated NDT-results in terms of changes in structural reliability.
To accelerate the growth of Industry 4.0 technologies, the digitalization of mechanical testing laboratories as one of the main data-driven units of materials processing industries is introduced in this paper. The digital lab infrastructure consists of highly detailed and standard-compliant materials testing knowledge graphs for a wide range of mechanical testing processes, as well as some tools that enable the efficient ontology development and conversion of heterogeneous materials’ mechanical testing data to the machine-readable data of uniform and standardized structures. As a basis for designing such a digital lab, the mechanical testing ontology (MTO) was developed based on the ISO 23718 and ISO/IEC 21838-2 standards for the semantic representation of the mechanical testing experiments, quantities, artifacts, and report data. The trial digitalization of materials mechanical testing lab was successfully performed by utilizing the developed tools and knowledge graph of processes for converting the various experimental test data of heterogeneous structures, languages, and formats to standardized Resource Description Framework (RDF) data formats. The concepts of data storage and data sharing in data spaces were also introduced and SPARQL queries were utilized to evaluate how the introduced approach can result in the data retrieval and response to the competency questions. The proposed digital materials mechanical testing lab approach allows the industries to access lots of trustworthy and traceable mechanical testing data of other academic and industrial organizations, and subsequently organize various data-driven research for their faster and cheaper product development leading to a higher performance of products in engineering and ecological aspects.
The existing cement and concrete standards are not capable of making full use of the current technology capacity due to strong focus on conventional concrete and thus they are not fit for the current and future challenges of construction industry. The paper highlights shortcomings with regard to the implementation of the existing standards. It can be seen that future-oriented standards are generally required to contribute to a lower-carbon footprint of the industry. These changes are significantly more relevant in sub-Saharan Africa, due to the rapidly increasing urbanisation challenge and the enormous potentials to develop lower-carbon technologies than elsewhere in the world.
Hierarchically porous, high‐surface‐area silica materials are excellent candidates for multiple applications like catalysis and environmental remediation. Shaping these materials with additive manufacturing (AM) techniques, like robocasting, could enable their use with the benefit of on‐demand, customized shaping and maximizing performance. Herein, ordered mesoporous silica COK‐12 slurries were robocasted into monoliths, containing different ratios of uncalcined COK‐12 and sodium bentonite (0–25 wt.%). The rheology of the mixed slurries is characterized by lower flow indexes (0.69 vs. 0.32) and higher yield stresses (96 vs. 259 Pa) compared to pure COK‐12 ones. Monoliths were printed in woodpile structures and calcined at 600°C. Micro‐CT measurements showed a linear shrinkage of 25% after calcination. Mechanical characterization showed increased uniaxial strength (0.20 ± 0.07 to 1.0 ± 0.3 MPa) with increasing binder/solids ratio from 13 to 25%. The amorphous, mesoporous structure of COK‐12 was retained. The structures exhibited open porosities of 52 ± 4% and showed higher specific mesopore volumes, and increased average mesopore size (6 vs. 8 nm) compared to COK‐12. Small‐angle x‐ray scattering analysis revealed an increased lattice parameter (10.3 vs. 11.0 nm) and reduced wall thickness (3.1 nm vs. 4.1 nm) of the COK‐12 in the monoliths. These properties indicate suitability for their application as porous supports and adsorbents.
There is no consensus on which hydration stoppage method is optimal to preserve the microstructure and mineral composition of samples, especially considering the specific aspects of different testing methods, such as TGA, MIP, or XRD. This paper presents a quantitative comparison between the most popular hydration stoppage strategies and parameters such as the sample piece size, the soaking time in a solvent, and the type, as examined on cement paste hydrated for 7 days. It was found that the carbonation appears either for samples smaller than 2.36 mm and bigger than 4.75 mm or samples soaked in a solvent for longer than 1 h. Fast solvent replacement leads to ettringite diminution and total pore volume increase. Among others, solvent replacement with subsequent gentle heating under a vacuum was found to be the most efficient, whereas it was experimentally demonstrated that isopropyl alcohol stops hydration faster than ethanol and acetone.
Due to the extremely high specific surface area of nanoparticles and corresponding potential for adsorption, the results of surface analysis can be highly dependent on the history of the particles, particularly regarding sample preparation and storage. The sample preparation method has, therefore, the potential to have a significant influence on the results. This report describes an interlaboratory comparison (ILC) with the aim of assessing which sample preparation methods for ToF-SIMS analysis of nanoparticles provided the most intra- and interlaboratory consistency and the least amount of sample contamination. The BAM reference material BAM-P110 (TiO2 nanoparticles with a mean Feret diameter of 19 nm) was used as a sample representing typical nanoparticles. A total of 11 participants returned ToF-SIMS data,in positive and (optionally) negative polarity, using sample preparation methods of “stick-and-go” as well as optionally “drop-dry” and “spin-coat.” The results showed that the largest sources of variation within the entire data set were caused by adventitious hydrocarbon contamination or insufficient sample coverage, with the spin-coating protocol applied in this ILC showing a tendency toward insufficient sample coverage; the sample preparation method or the participant had a lesser influence on results.
An amorphous Lewis-acidic zirconium chlorofluoride as HF shuttle: C–F bond activation and formation
(2023)
An exceptional HF transfer reaction by C–F bond activation of fluoropentane and a subsequent hydrofluorination of alkynes at room temperature is reported. An amorphous Lewis-acidic Zr chlorofluoride serves as heterogeneous catalyst, which is characterised by an eightfold coordination environment at Zr including chlorine atoms. The studies are seminal in establishing sustainable fluorine chemistry.
The performance of second generation ICP-TOFMS, equipped with a micro-channel plate (MCP) enabling multi-isotope detection, in terms of isotope ratio precision and instrumental isotopic fractionation (IIF) for (multi-)isotope ratio analysis was thoroughly assessed for B, Sr and Pb. Experimental isotope ratio precision of 0.14 % for 11B/10B intensity ratio, 0.15 % for 87Sr/86Sr intensity ratio and 0.07% for 208Pb/206Pb intensity ratio were obtained at high signal levels ($500 mg L−1) which is comparable to first generation ICP-TOFMS. The long-term stability of isotope ratios, measured over several hours and expressed as repeatability, is between 0.05 % and 1.8 % for B, Sr and Pb. The observed IIF per mass unit is negative for B (i.e., −11 % for 11B/10B) which is in accordance with measurements using sector field (MC) ICP-MS. But the observed IIF per mass unit is positive for Sr (i.e., 2 % for 87Sr/86Sr) and Pb (i.e., 4.5 % for 208Pb/206Pb) which is not in accordance with measurements using sector field (MC) ICP-MS. Furthermore, different IIFs per mass unit were observed for different isotope pairs of the same isotopic system (i.e., Sr, Pb) and adjacent isotopic systems (i.e., Pb vs. Tl). This and the observations from three-isotope plots for Sr and Pb show that ion formation, ion extraction, ion transmission, ion separation and ion detection in second generation ICP-TOFMS is subject to IIF that does not follow the known mass dependent fractionation laws and is possibly caused by mass independent fractionation and/or multiple (contradictory) fractionation processes with varying contributions. The non-mass dependent IIF behavior observed for second generation ICP TOFMS has profound consequences for the IIF correction of isotope raw data, including application of multi-isotope dilution mass spectrometry (IDMS) using ICP-TOFMS. Hence, only IIF correction models that correct also for mass independent fractionation are applicable to calculate reliable isotope ratios using second generation ICP-TOFMS. In the present study, reliable d11B values, and absolute B, Sr and Pb isotope ratios could be determined using the SSB approach in single-element solutions as well as in a mixture of B, Sr and Pb, where the isotopes were measured simultaneously.
Mechanical flexibility in molecular crystals is a fascinating behavior with potential for developing advanced technologies. However, the phenomenon of mechanical bending is poorly understood. We explore for the first time the atomistic origin of elastic bending in a single component organic crystal using a combination of μ-focus synchrotron X-ray diffraction and ab initio simulation.
Structural build-up describes the stability and early-age strength development of fresh mortar used in 3D printing. lt is influenced by several factors, i.e. the composition of the print able material, the printing regime, and the ambient conditions. The existing modelling approaches for structural build-up usually define the model parameters for a specific material composition with out considering the influence of the ambient conditions. The goal of this contribution is to explicitly include the temperature dependency in the modelling approach. Temperature changes have signifi cant impact on the structural build-up process: an increase of the temperature leads to a faster dissol ution of cement phases and accelerates hydration. The proposed extended model includes temperature dependency using the Arrhenius theory. The new model parameters are successfully calibrated based on Viskomat measurement data using Bayesian inference. Furthermore, a higher impact of the temperature in the re-flocculation as in the structuration stage is observed.
The present work is part of the AIFRI project (Artificial Intelligence For Rail Inspection), where we and our project partners train a neural network for defect detection and classification. Our goal at BAM is to generate artificial ultrasound and eddy current training data for the A.I. This paper has an exploratory nature, where we focus on the simulation of eddy current signals for head check cracks, one of the most important rail surface defects. The goal of this paper is twofold. On the one hand, we present our general simulation setup. This includes geometric models for head check cracks with features like branching and direction change, a model for the HC10 rail testing probe, and the configuration of the Faraday simulation software.
On the other hand, we use the Faraday software to simulate eddy current testing signals with a strong focus on the influence of the damage depth on the signal, while differentiating between different crack geometries. Here, we observe an early saturation effect of the test signal at a damage depth of 2 mm (at a crack angle of 25◦ to the surface). That is about 2 mm earlier than we would expect from measurements at a crack angle of 90◦. This behavior will be investigated further in a future paper. Finally, we interpolate the simulated signals in a two-step curve fitting process. With these interpolations we may generate eddy current test signals for any damage depth within the simulated range.
Bulk metallic glasses (BMG) are amorphous metal alloys known for their unique physical and mechanical properties. In the present study, the formation of femtosecond (fs) laser-induced periodic surface structures (LIPSS) on the Zr-based BMGs Zr46Cu46Al8, Zr61Cu25Al12Ti2, Zr52.5Cu17.9Al10Ni14.6Ti5 (Vit105) and Zr57Cu15.4Al10Ni12.6Nb5 (Vit106) was investigated as a function of their different chemical composition. For this purpose, LIPSS were generated on the sample surfaces in an air environment by fs-laser irradiation (λ = 1025 nm, τ = 300 fs, frep = 100 kHz). The surface topography was characterized by scanning electron microscopy and atomic force microscopy. Moreover, the impact of LIPSS formation on the structure and chemical surface composition was analyzed before and after fs-laser irradiation by X-ray diffraction and X-ray photoelectron spectroscopy as well as by transmission electron microscopy in combination with energy dispersive X-ray spectroscopy. Despite the different chemical composition of the investigated BMGs, the fs-laser irradiation resulted in almost similar properties of the generated LIPSS patterns. In the case of Zr61Cu25Al12Ti2, Vit105 and Vit106, the surface analysis revealed the preservation of the amorphous state of the materials during fs-laser irradiation. The study demonstrated the presence of a native oxide layer on all pristine BMGs. In addition, fs-laser irradiation results in the formation of laser-induced oxide layers of larger thickness consisting of an amorphous ZrAlCu-oxide. The precise laser-structuring of BMG surfaces on the nanoscale provides a versatile alternative to thermoplastic forming of BMG surfaces and is of particular interest for the engineering of functional material surfaces.
The impact of high additions of vegetable oil (12 vol%) on the mechanical and microstructural properties of metakaolin-slag-based alkali-activated materials (AAMs) was studied. The addition of oil resulted in a slight decrease in initial polymerization kinetics but did not affect the final degree of reaction. AAM-oil-composite-mortars exhibited approximately ∼30% lower compressive strength primarily due to the entrainment of air voids. Newly formed soap phases significantly reduced the volume of small capillary and gel pores (pore radii <15 nm), leading to a decrease in specific inner surface area by a factor of up to 15. The porosity modification induced by the oil addition greatly enhanced the resistance of AAMs against sulfuric acid attack, shifting the dominant processes from diffusion and cracks to framework-dissolution controlled by the inherent phase stabilities. Following the immersion in sulfuric acid (pHstat = 2) for 8 weeks, the depth of corroded layer decreased by 70% and no cracks due to expansive phases were observed. These promising findings suggest that the incorporation of vegetable oil in AAMs has the potential to address durability concerns associated with diffusion-based corrosion processes, thereby expanding the range of future applications.
AISI 2205 duplex stainless steel is used in a variety of industries, including the chemical and petrochemical industries. This is due to its high tensile strength combined with good ductility and corrosion resistance. However, in laser beam welding, these properties are negatively afected by the high cooling rates typical of the welding process. The resulting higher ferrrite content in the weld metal than in the base material leads to a reduction in the ductility and corrosion resistance of the welded joint. To overcome this problem, in this study, thick plates were coated by direct energy deposition (DED) prior to laser beam welding, whereas a duplex powder mixture containing a higher nickel concentration was used as a coating material. To improve the weld quality for the proposed two-step process, a method of additional material deposition instead of conventional tack weld was investigated. The resulting welded joints showed a well-balanced austenite to ferrite ratio and their properties and microstructure were verifed by metallographic analysis, electron backscatter difraction and Charpy impact testing. Using the standard ASTM G48 test method, it was found that the corrosion resistance of the welds was improved by a factor of four in average compared to the conventionally welded joints. The resulting properties, such as good ductility and corrosion resistance, of the welds with pre-coated edges showed good agreement with those of the base metal and confrmed the proposed two-step process as a promising alternative to the conventional approaches for welding thick duplex stainless steel plates.
With femtosecond-laser direct writing (fs-LDW) maturing in all aspects as a manufacturing technology, a toolset for quality assurance must be developed. In this work we introduce a first of its kind test artifact. Test artifacts are standardized 3D models with specific geometric features to evaluate the performance of writing parameters. Test artifacts are already common in other 3D additive manufacturing technologies e.g. selective laser melting. The test artifact introduced in this work was developed in particular to accommodate the high geometrical resolution of fs-LDW structures and the limited possibilities to examine the resulting structure. Geometric accuracy, surface adhesion as well as confocal Raman spectroscopy results were considered when evaluating the design of the test artifact. We will explain the individual features and design considerations of our fs-LDW test artifact. The difference between two slicers, Cura and 3DPoli, and the implications on measured feature sizes and the general shape is quantified. The measured geometries are used to derive a general design guide for a specific combination of photoresists, laser power and scanning speed and to analyze the geometric accuracy of a structure produced using these guidelines. The shown test artifact is publicly available as STL file on GitHub (https://github.com/BAMresearch/2PP-TestArtifact) and in the supplement.
The crystallization proceeds by the advance of the crystal faces into the disordered phase at the expense of the material excess, the supersaturation. Using a conservation constraint for the transformation ratio α∈[0,1] as complementing the rescaled supersaturation to 1 and a kinetic law for the normal growth velocity as function of the supersaturation raised to power g, the growth order, we derive an equation for the rate of transformation dα/dt. We integrate it for the six combinations of the three spatial dimensions D = 1, 2, 3 and the two canonical values of g = 1, 2 towards obtaining expressions for αDg. The same equation, with g = 1 and D = n (n is the so called Avrami exponent) is obtained when taking only the linear in α term from the Taylor’s expansion around α = 0 of the model equation of Johnson-Mehl-Avrami-Kolmogorov (JMAK). We verify our model by fitting datasets of α21 and α31 (from α = 0 to αupper = 0.999) with JMAK to obtain from the fit n = 1.725, 2.43, resp. We show
further how the values of n depend on the value of αupper to which the fit is performed starting always from 0. Towards building a validation protocol, we start with validating α21 with published results.
Materials that support natural biodiversity on their surfaces can compensate for human activities that have a negative impact on nature and thus contribute to a carbon-neutral and nature-positive world. Specifically designing bioreceptive materials which favor the growth of biofilms on their surface is an approach complementing conventional, macroscopic green façades. But what exactly characterizes a bioreceptive substrate and how do biofilm and substrate interact? How and why does a spontaneous colonization and the formation of biofilms take place? What are biofilms and how can they be established in a laboratory setting? How can this existing knowledge be transferred to the artificial stone concrete so that this material can be tuned to increase (or decrease) its bioreceptivity?
This review paper aims at summarizing the existing state of knowledge on bioreceptive concrete and pointing out inconsistencies and contradictions which can only be removed by more interdisciplinary research in the field.
Understanding the mechanical behavior of silicon nanowires is essential for the implementation of advanced nanoscale devices. Although bending tests are predominantly used for this purpose, their findings should be properly interpreted through modeling. Various modeling approaches tend to ignore parts of the effective parameter set involved in the rather complex bending response. This oversimplification is the main reason behind the spread of the modulus of elasticity and strength data in the literature. Addressing this challenge, a surface-based nanomechanical model is introduced in this study. The proposed model considers two important factors that have so far remained neglected despite their significance: (i) intrinsic stresses composed of the initial residual stress and surface-induced residual stress and (ii) anisotropic implementation of surface stress and elasticity. The modeling study is consolidated with molecular dynamics-based study of the native oxide surface through reactive force fields and a series of nanoscale characterization work through in situ threepoint bending test and Raman spectroscopy. The treatment of the test data through a series of models with increasing complexity demonstrates a spread of 85 GPa for the modulus of elasticity and points to the origins of ambiguity regarding silicon nanowire properties, which are some of the most commonly employed nanoscale building blocks. A similar conclusion is reached for strength with variations of up to 3 GPa estimated by the aforementioned nanomechanical models. Precise consideration of the nanowire surface state is thus critical to comprehending the mechanical behavior of silicon nanowires accurately. Overall, this study highlights the need for a multiscale theoretical framework to fully understand the size-dependent mechanical behavior of silicon nanowires, with fortifying effects on the design and reliability assessment of future nanoelectromechanical systems.
An automated and straightforward detection and data treatment strategy for the determination of the protein relative concentration in individual human cells by single cell–inductively coupled plasma–time-of-flight mass spectrometry (sc-ICP-ToF-MS) is proposed. Metal nanocluster (NC)-labeled specific antibodies for the target proteins were employed, and ruthenium red (RR) staining, which binds to the cells surface, was used to determine the number of cell events as well as to evaluate the relative volume of the cells. As a proof of concept, the expression of hepcidin, metallothionein-2, and ferroportin employing specific antibodies labeled with IrNCs, PtNCs, and AuNCs, respectively, was investigated by sc-ICP-ToF-MS in human ARPE-19 cells. Taking into account that ARPE-19 cells are spherical in suspension and RR binds to the surface of the cells, the Ru intensity was related to the cell volume (i.e., the cell volume is directly proportional to (Ru intensity)3/2), making it possible to determine not only the mass of the target proteins in each individual cell but also the relative concentration. The proposed approach is of particular interest in comparing cell cultures subjected to different supplementations. ARPE-19 cell cultures under two stress conditions were compared: a hyperglycemic model and an oxidative stress model. The comparison of the control with treated cells shows not only the mass of analyzed species but also the relative changes in the cell volume and concentration of target proteins, clearly allowing the identification of subpopulations under the respective treatment.
Quenching and partitioning (Q&P) steels are characterized by an excellent combination of strength and ductility, opening up great potentials for advanced lightweight components. The Q&P treatment results in microstructures with a martensitic matrix being responsible for increased strength whereas interstitially enriched metastable retained austenite (RA) contributes to excellent ductility. Herein, a comprehensive experimental characterization of microstructure evolution and austenite stability is carried out on a 42CrSi steel being subjected to different Q&P treatments. The microstructure of both conditions is characterized by scanning electron microscopy as well as X‐ray diffraction (XRD) phase analysis. Besides macroscopic standard tensile tests, RA evolution under tensile loading is investigated by in situ XRD using synchrotron and laboratory methods. As a result of different quenching temperatures, the two conditions considered are characterized by different RA contents and morphologies, resulting in different strain hardening behaviors as well as strength and ductility values under tensile loading. In situ synchrotron measurements show differences in the transformation kinetics being rationalized by the different morphologies of the RA. Eventually, the evolution of the phase specific stresses can be explained by the well‐known Masing model.
Epoxy R-Glass Fiber-Reinforced Polymer (GFRP) composite plates were hydrothermally aged at 60 ◦C for 23, 75, and 133 days. The water content reached 0.97 wt%, 1.45 wt% and 1.63 wt%, respectively. The studied GFRP matrix was inert to hydrolysis or chain scission, allowing for investigation of irreversible changes in the fiber-matrix interphase due to hydrothermal aging upon re-drying. During each period, a subset of the specimens was removed from the water bath and dried in a chamber. The weight loss upon drying was explained with epoxy leaching (impurities), sizing-rich interphase hydrolysis, glass fiber surface hydrolysis, accumulated degradation products escaping, and water changing state from bound to free. The influence of hydrothermal aging on the fiber-matrix interfacial properties was investigated. Lower interfacial strength of hydrothermally aged (wet)
samples was attributed to plasticization of the epoxy, plasticization and degradation of the sizing-rich interphase (including formation of hydrolytic flaws), and hydrolytic degradation of the glass fiber surface. The kinetics of epoxy-compatible epoxysilane W2020 sizing-rich interphase hydrolysis provided an estimate of ca. 1.49%, 4.80%, and 8.49% of the total composite interphase degraded after 23, 75, and 133 days, respectively. At these conditions, the interface lost 39%, 48%, and 51% of its strength. Upon re-drying the specimens, a significant part of the interfacial strength was regained. Furthermore, an upward trend was observed, being 13%, 10% and 3% strength, respectively; thus, indicating a possibility of partial recovery of properties.
Surface-functionalized polymer beads encoded with molecular luminophores and nanocrystalline emitters such as semiconductor nanocrystals, often referred to as quantum dots (QDs), or magnetic nanoparticles are broadly used in the life sciences as reporters and carrier beads. Many of these applications require a profound knowledge of the chemical nature and total number of their surface functional groups (FGs), that control bead charge, colloidal stability, hydrophobicity, and the interaction with the environment and biological systems. For bioanalytical applications, also the
number of groups accessible for the subsequent functionalization with, e.g., biomolecules or targeting ligands is relevant. In this study, we explore the influence of QD encoding on the amount of carboxylic acid (COOH) surface FGs of 2 μm polystyrene microparticles (PSMPs). This is done for frequently employed oleic acid and oleylamine stabilized, luminescent core/shell CdSe QDs and two commonly used encoding procedures. This included QD addition during bead formation by a thermally induced polymerization reaction and a post synthetic swelling procedure. The accessible number of COOH groups on the surface of QD-encoded and pristine beads was quantified by two colorimetric assays, utilizing differently sized reporters and electrostatic and covalent interactions. The results were compared to the total number of FGs obtained by a conductometric titration and Fourier transform infrared spectroscopy (FTIR). In addition, a comparison of the impact of QD and dye encoding on the bead surface chemistry was performed. Our results demonstrate the influence of QD encoding and the QD-encoding strategy on the number of surface FG that is ascribed to an interaction of the QDs with the carboxylic acid groups on the bead surface. These findings are of considerable relevance for applications of nanoparticle-encoded beads and safe-by-design concepts for nanomaterials.
Density-based phase-field (DPF) methods have emerged as a technique for simulating grain boundary thermodynamics and kinetics. Compared to the classical phase-field, DPF gives a more physical description of the grain boundary structure and chemistry, bridging CALPHAD databases and atomistic simulations, with broad applications to grain boundary and segregation engineering. Notwithstanding their notable progress, further advancements are still warranted in DPF methods. Chief among these are the requirements to resolve its performance constraints associated with solving fourth-order partial differential equations (PDEs) and to enable the DPF methods for simulating moving grain boundaries. Presented in this work is a means by which the aforementioned problems are addressed by expressing the density field of a DPF simulation in terms of a traditional order parameter field. A generic DPF free energy functional is derived and used to carry out a series of equilibrium and dynamic simulations of grain boundaries in order to generate trends such as grain boundary width vs. gradient energy coefficient, grain boundary velocity vs. applied driving force, and spherical grain radius vs. time. These trends are compared with analytical solutions and the behavior of physical grain boundaries in order to ascertain the validity of the coupled DPF model. All tested quantities were found to agree with established theories of grain boundary behavior. In addition, the resulting simulations allow for DPF simulations to be carried out by existing phase-field solvers.
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.