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In the interest of exploring their potential in the field of single particle analysis, a Microdroplet Generator (MDG) was coupled to an ICP-ToF-MS. Isotopic Dilution Analysis was also incorporated for the size determination of three different Platinum nanoparticles samples (50, 63 and 70 nm). The performance of the technique was validated by comparison to traditional size characterization techniques (sp-ICP-ToF-MS, TEM), while the robustness of the technique was proven by incorporating NaCl in the samples’ matrix, up to 100 mg/L.
Asymmetrical Flow Field-Flow Fractionation (AF4), as a cleaning technique, was combined on-line with the multielemental analytical capabilities of an Inductively Coupled Plasma-Time of Flight-Mass Spectrometer (ICP-ToF-MS). In that manner, the heavy ionic matrix effect of untreated cells' samples can be significantly reduced. As a proof of concept, commercial baker's yeast cells were analysed.
McSAS3 is a refactored software package for fitting large batches of (X-ray or Neutron) scattering data. It uses a Monte-Carlo acceptance-rejection algorithm to optimize model parameters - ideal for analysis of size-disperse scatterers.
The refactored code can exploit multiprocessing, traceably stores (multiple) results in the output file, and allows for re-histogramming of previous optimizations. Besides analysis of large batches, it can also be integrated in automated data processing pipelines.
The live demonstration will show how to use the software, what its limitations are, and what outcomes can look like for batches of results.
We investigated the performance of nitrogen microwave inductively coupled atmospheric-pressure plasma mass spectrometry (MICAP-MS) under matrix effects and its applicability to trace element analysis in steels. Influences of different gas flows and ion optics on the matrix tolerance are studied, indicating that nebulizer gas flow has the most significant impact. Optimization of ion optics improves matrix tolerance for light elements due to the reduction of the inelastic collisional scattering effect. With optimized operating conditions, MICAP-MS achieves an internal standard intensity recovery of over 90% at an Fe concentration of 500 mg L−1. Even at an Fe concentration of 1 g L−1, the recovery remains above 80%. Three certified reference materials – non-alloy, low-alloy and high-alloy steel – were analyzed using MICAP-MS. The determined mass concentrations of the trace and minor components show metrological compatibility to the reference values. No significant differences are observed between the results obtained with aqueous and matrix-matched calibration, demonstrating the strong matrix tolerance of MICAP-MS, and its promising applicability to steel analysis.
Cardiac troponin I (cTnI) is a crucial biomarker for diagnosing cardiac vascular diseases, including acute myocardial infarction (AMI). This study presents a proof-of-concept chemiluminescence-based immunosensor for rapid and accurate measurement of cTnI, with the potential for online monitoring. The immunosensor incorporates a flow cell design and a sensitive complementary metal-oxide-semiconductor (CMOS) camera for optical readout. A microfluidic setup was established to enable selective and quasi-online determination of cTnI within ten minutes. The sensor was tested with recombinant cTnI in phosphate buffer, demonstrating measurements in the concentration range of 2–25 µg/L, with a limit of detection (LoD) of 0.6 µg/L (23 pmol/L) achieved using the optimized system. The immunosensor exhibited high selectivity, as no cross-reactivity was observed with other recombinant proteins such as cTnT and cTnC at a concentration of 16 µg/L. Measurements with diluted blood plasma and serum yielded an LoD of 60 µg/L (2.4 nmol/L) and 70 µg/L (2.9 nmol/L), respectively. This biosensor offers a promising approach for the rapid and sensitive detection of cTnI, contributing to the diagnosis and management of acute myocardial infarction and other cardiac vascular diseases.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
Creep-resistant steels such as the 13CrMoV9-10, used in the construction of thick-walled pressure vessels, are most commonly submerged arc welded (SAW). These steels can develop stress relief cracks (SRC) if the mandatory post weld heat treatment (PWHT) is performed improperly. Current PWHT parameters, such as heating rate and holding time at a specific holding temperature, are based on both empirical experience and conventional free shrinking welding experiments to characterize the SRC-susceptibility of the weld. These cannot adequately depict the higher residual stresses caused by the structurally induced stiffness of the surrounding construction. This study discusses the development of a repeatable, precise, and time-efficient methodology to study the effects of different stress levels and heating rates on the SRC susceptibility of the coarse grain heat-affected zone (CGHAZ). For that purpose, samples were thermically treated to simulate a coarse grain heat-affected zone (CGHAZ) and subsequently exposed to representative levels of stress during the heating phase of a PWHT. The recorded stress and heating rate–dependent strains were mathematically analyzed via curve tracing/calculus to identify interdependent effects. This procedure facilitates the measurement of material characteristics such as carbide growth on grain boundaries at the µm-scale via an integrated value over the entire sample volume. The first and second derivatives show a slight, precipitate-dependent, increase in hardness of the sample, depending on the heating rate and applied stress. This new methodology generates an improved assessment of the SRC susceptibility of SAW microstructures of creep-resistant CrMoV steels.
The complex nature of liquid water saturation of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs) greatly affects the device performance. To investigate this problem, we present a method to quantify the presence of liquid water in a PEFC CL using small-angle X-ray scattering (SAXS). This method leverages the differences in electron densities between the solid catalyst matrix and the liquid water filled pores of the CL under both dry and wet conditions. This approach is validated using ex situ wetting experiments, which aid the study of the transient saturation of a CL in a flow cell configuration in situ. The azimuthally integrated scattering data are fitted using 3D morphology models of the CL under dry conditions. Different wetting scenarios are realized in silico, and the corresponding SAXS data are numerically simulated by a direct 3D Fourier transformation. The simulated SAXS profiles of the different wetting scenarios are used to interpret the measured SAXS data which allows the derivation of the most probable wetting mechanism within a flow cell electrode.
While the synthesis of Metal-Organic Framework (MOF) particles can be as easy as adding two solutions together, reproducibly obtaining the same particles, time and time again, is a lot harder. As laboratory-independent reproducibility is a cornerstone of the scientific method, we must put effort into finding and controlling all necessary parameters to achieve this.
An open-source Python/EPICS-controlled robotic platform (see picture) was adapted to systematically explore this for a 20 ml MOF synthesis of the Zeolitic Imidazole Framework-8 (ZIF-8) chemistry in methanol. Parameters that were explored included: 1) addition sequence, 2) addition speeds, 3) reaction times, 4) source chemicals, 5) stirring speeds, 6) stirring bar choice, 7) starting concentrations, and 8) workup methodologies. It was found that, by controlling these parameters, highly reproducible syntheses are obtained. Secondly, the variation of these parameters alone led to a dramatic difference in volume-weighted particle size means, which exceeds an order of magnitude as investigated by our in-house X-ray scattering instrument [1].
The syntheses are thoroughly documented in an automated fashion, and the synthesis libraries as well as analyses libraries will become available in batches soon. With this library, it will be possible to extract previously unknown correlations, and other laboratories can produce specific particles by following the exact procedures of the particles of their choice.
Robot-assisted laser thermography for surface breaking crack detection on complex shaped components
(2023)
Laser thermography using a focused (spot or line) beam has proved to be effective for detection of surface breaking cracks on planar samples. In this work, we use the same principle, but applied to complex shaped components, like a rail cross-section, a gear, and a gas turbine blade. We use a six-axis robot to move the sample in-front of our thermographic setup. Several scanning-path and thermographic parameters are explored: scanning speed, density of points in each scanning slice, laser power, camera framerate. Additionally, we explore semi-automatic evaluation algorithms for crack detection, as well as 2D-to-3D registration of the found indications.
The use of benchtop-NMR instruments is constantly increasing during the recent years. Advantages of being affordable, portable and easy-to-operate without the need for trained staff make them especially interesting for industrial applications in quality control. However, applications of NMR spectroscopy as an online PAT tool are still very rare but offer a huge potential for process optimization and control. A key task to exploit this potential is hardware field integration of the lab-instruments in a rough environment of a chemical plant. Additionally, developments in automation and data evaluation are mandatory to ensure a robust unattended operation with low maintenance requirements. Here, we show an approach of a fully automated analyzer enclosure considering explosion safety, field communication, as well as environmental conditions in the field.
Temperature sensitivity is still a limitation of benchtop-NMR instruments in flow applications. Recent developments of manufacturers allow for limited operation at static temperature levels, however, a dynamic system for continuous operation is still not available. Using a prototype system offering a larger bore, active temperature shielding studies with thermostated air were performed evaluating the performance.
Automated data evaluation of NMR spectra using a modular indirect hard modeling (IHM) approach showed good results and flexibility. A second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously, offering new ways to simultaneously evaluating large numbers of different models.
Immobilized metal affinity chromatography (IMAC) is a widely used technique for purifying polyhistidine-tagged recombinant proteins. However, it often has practical limitations that require complex optimizations and additional steps for purification. In this study, we introduce functionalized corundum particles as a novel, efficient, and economical method for purifying recombinant proteins in a column-free format. The corundum surface is modified with amino silane APTES, followed by EDTA dianhydride, and then loaded with nickel ions. We used the Kaiser test to monitor the modification process and ICP-MS to quantify the metal-binding capacity. To evaluate the system, we used His-tagged protein A/G (PAG) mixed with bovine serum albumin (BSA). The corundum particles exhibited a binding capacity of approximately 3 mg of protein per gram of corundum or 2.4 mg per 1 mL of corundum suspension. We also examined cytoplasm obtained from different E. coli strains as an example of a complex matrix. Varying the imidazole concentration in the loading and washing buffers showed that higher concentrations during loading improved purity. Even with sample volumes as large as one liter, we successfully isolated recombinant proteins down to a concentration of 1 µg/mL. We found higher purity levels with corundum when comparing the corundum material to standard Ni–NTA agarose beads. We successfully purified His6-MBP-mSA2, a fusion protein comprising monomeric streptavidin and maltose-binding protein, from E. coli cytoplasm, demonstrating the method's applicability. We also purified SARS-CoV-2-S-RBD-His8 expressed in human Expi293F cells, confirming its suitability for mammalian cell culture supernatants. The material cost of the nickel-loaded corundum material (without regeneration) is estimated to be less than 30 cents per gram of functionalized support or 10 cents per milligram of isolated protein. Another advantage of this system is the exceptional physical and chemical stability of corundum particles. Overall, we have demonstrated that this novel material offers an efficient, robust, and cost-effective purification platform for His-tagged proteins, even in challenging, complex matrices and large sample volumes with low product concentrations. This method has potential applications in both small laboratories and large-scale industrial settings.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
This paper reports a systematic study into the effect of nitrogen on iron-catalyzed graphitization of biomass. Chitin, chitosan, N-acetylglucosamine, gelatin and glycine were selected to represent nitrogen-rich saccharides and amino-acid/polypeptide biomass precursors. The materials were pyrolyzed with an iron catalyst to produce carbons with a wide range of chemical and structural features such as mesoporosity and nitrogen-doping. Many authors have reported the synthesis of nitrogen-doped carbons by pyrolysis and these have diverse applications. However, this is the first systematic study of how nitrogen affects pyrolysis of biomass and importantly the catalytic graphitization step. Our data demonstrates that nitrogen inhibits graphitization but that some nitrogen survives the catalytic graphitization process to become incorporated into various chemical environments in the carbon product.
The dataset contains raw data gathered with the ultrasonic pulse-echo method on concrete specimens. The surfaces of the measuring objects were automatically scanned point by point. Pulse-echo measurements were performed at each of these measuring points. The test specimens represent two typical testing tasks in construction industry: the detection of objects and the determination of dimensions to describe the geometry of components. By automating the measurement process, the different test scenarios are examined with a high repeatability, precision and measuring point density. Longitu- dinal and transversal waves were used and the geometrical aperture of the testing system was varied. The low-frequency probes operate in a range of up to approximately 150 kHz. In addition to the specification of the geometrical dimensions of the individual probes, the directivity pattern and the sound field characteristics are provided. The raw data are stored in a universally readable format. The length of each time signal (A-scan) is two milliseconds and the sampling rate is two mega-samples per second. The provided data can be used for comparative studies in signal analysis, imag- ing and interpretation as well as for evaluation pur- poses in different, practically relevant testing scenarios.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
This data set contains three different data types obtained from concrete specimens. For each specimen, the rebound numbers, ultrasonic data (ultrasonic velocity, time of flight), and destructive concrete strength are given. Two kind of specimen geometries were tested: cubes and drilled cores. The files are labeled according to the specimen geometry as "cube" or "core" and the type of measurement data as "compressive_strength", "rn_R" and "rn_Q" for rebound numbers as well as "us" for ultrasonic data. The ultrasonic data were generated by six independent laboratories, the rebound numbers by five independent laboratories and the destructive tests by one laboratory. The designation of each specimen establishes the relationship between the different data types.
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
The corner echo is a well-known effect in ultrasonic testing, which allows detection of surface breaking cracks with predominantly perpendicular orientation to the surface as, for example, corrosion cracks in metal pipes or shafts. This echo is formed by two planes, the surface of the crack and the surface which the crack breaks. It can also be classified as a half-skip method, since a reflection of the pulse occurs on the backwall before the reflection at the defect takes place. In combination with the diffraction from the crack tip, the corner echo also allows crack sizing. As shown in this paper, the corner reflection can be used in civil engineering for nondestructive inspection of concrete. Commercially available low frequency ultrasonic arrays with dry point contact sources generate SH transversal waves with sufficient divergence of the sound field in order to detect corner reflections. Ultrasonic line-scans and area-scans were acquired with a linear array on flat concrete specimens, and the data were reconstructed by the Synthetic aperture focusing technique. If the angles and the area of reconstruction are chosen accordingly, the corner echo reflection can be distinguished from other ultrasonic information. The corner echo can thus be used as a method for deciding whether a crack is a partial-depth crack or a full-depth crack and thus for obtaining a statement about crack depth. This paper presents corresponding experimental results obtained on concrete specimens with artificial test defects and cracks induced under controlled conditions.
Two test series were examined using nondestructive measuring methods by six independent laboratories before determining their compressive strength. The nondestructive test methods used were the rebound hammer and ultrasonic pulse velocity measurement. Two types of geometries were investigated: drilled cores and cubes. The measurement procedure for each of these datasets is conditioned to the geometry and is therefore different.
The first series consists of 20 drilled cores (approximately diameter/height = 10 cm/20 cm) from the 55-year-old Lahntal Viaduct near Limburg, Germany. After preparation in the first laboratory, the lateral surface of the drilled cores was tested with the rebound hammer using a given pattern. Every laboratory tested every drilled core at different locations.
Ultrasonic measurements in transmission were performed repeatedly at predefined points on the flat surfaces of the specimen.
The second series consisted of 25 newly manufactured concrete cubes of a mix with a target concrete strength class of C30/37. The edge length was 15 cm. Each laboratory received five specimens of this test series. Thus, contrary to the first series, each specimen was tested by only one laboratory. Two side faces of each cube were tested with the rebound hammer. In addition, ultrasonic measurements were performed by one laboratory. The time of flight was measured between the tested side faces of the rebound hammer at different positions.
For both series, rebound hammers were used to determine the R-value as well as the Q-value. The rebound hammer models within the laboratories were always the same, while they differed between the laboratories. The ultrasonic measurements took place with different measurement systems and couplants. Finally, both specimen series were tested destructively for compressive strength.
The dataset contains the raw data summarized in tabular form. In addition, relevant calculated data are included in some cases. For the ultrasonic measurements, the time of flight has already been converted into the ultrasonic velocity. Besides, in addition to the raw data of the compressive strength test (force, weight, and geometry values), the calculated compressive strengths and densities are also provided.
The glass transition behavior of thin films of poly(bisphenol A carbonate) (PBAC) was studied employing ellipsometry. The glass transition temperature increases with the reduction of the film thickness. This result is attributed to the formation of an adsorbed layer with a reduced mobility compared to bulk PBAC. Therefore, for the first time, the growth kinetics of the adsorbed layer of PBAC was investigated, prepared by leaching samples from a 200 nm thin film which were annealed for several times at three different temperatures. The thickness of each prepared adsorbed layer was measured by multiple scans using atomic force microscopy (AFM). Additionally, an unannealed sample was measured. Comparison of the measurements of the unannealed and the annealed samples provides proof of a pre-growth regime for all annealing temperatures which was not observed for other polymers. For the lowest annealing temperature after the pre-growth stage only a growth regime with a linear time dependence is observed. For higher annealing temperatures the growth kinetics changes from a linear to a logarithmic growth regime at a critical time. At the longest annealing times the films showed signs of dewetting where segments of the adsorbed film were removed from the substrate (dewetting by desorption). The dependence of the surface roughness of the PBAC surface on annealing time also confirmed that the films annealed at highest temperatures for the longest times desorbed from the substrate.
The microstructure of an apatite-wollastonite (code name AP40) glass-ceramic is analyzed in this study by combining 2D microscopy, phase analysis, X-ray absorption and synchrotron X-ray refraction computed tomography (XCT and SXRCT, respectively). It is shown that this combination provides a useful toolbox to characterize the global microstructure in a wide scale range, from sub-micrometer to millimeter. The material displays a complex microstructure comprising a glassy matrix with embedded fluorapatite and wollastonite small crystals. In this matrix, large (up to 200 μm) spike-shaped structures are distributed. Such microstructural features are oriented around a central sphere, thereby forming a structure resembling a sea urchin. A unique feature of SXRCT, in contrast to XCT, is that internal interfaces are visualized; this allows one to show the 3D distribution of these urchins with exceptionally good contrast. Furthermore, it is revealed that the spike-shaped structures are not single crystals, but rather composed of sub-micrometric crystals, which are identified as fluorapatite and diopside phases by SEM-EDX analysis.
In this study, we compare analytical methods for PFAS determination–target analysis, non-target screening (NTS), direct total oxidizable precursor assay (dTOPA) and extractable organically bound fluorine (EOF). Therefore, suspended particulate matter (SPM) samples from German rivers at different locations in time series from2005 to 2020 were analyzed to investigate temporal and spatially resolved trends. In this study 3 PFAS mass balances approaches were utilized: (i) PFAA target vs. PFAS dTOPA, (ii) PFAS target vs. EOF and (iii) PFAS target vs. PFAS dTOPA vs. organofluorines NTS vs. EOF. Mass balance approach (i) revealed high proportions of precursor substances in SPM samples. For the time resolved analysis an increase from 94% (2005) to 97% in 2019 was observable. Also for the spatial resolved analysis precursor proportions were high with >84% at all sampling sites. Mass balance approach (ii) showed that the unidentified EOF (uEOF) fraction increased over time from82% (2005) to 99% (2019). Furthermore, along the river courses the uEOF increased. In the combined mass balance approach (iii) using 4 different analytical approaches EOF fractions were further unraveled. The EOF pattern was fully explainable at the sampling sites at Saar and Elbe rivers. For the time resolved analysis, an increased proportion of the EOF was now explainable. However, still 27% of the EOF for the time resolved analysis and 25% of the EOF for the spatial resolved analysis remained unknown. Therefore, in a complementary approach, both the EOF and dTOPA reveal unknown gaps in the PFAS mass balance and are valuable contributions to PFAS risk assessment. Further research is needed to identify organofluorines summarized in the EOF parameter.
Introduction to microplastics, definition, relevance, analytical approaches & challenges. TED-GC/MS working principle, features & performance. Optimisation in TED-GC/MS methodology, new validation data. Replacement of Internal Standard, outlook towards upcoming publication and application within EU´s revised drinking water directive.
Critical defects, also known as device killers, in wide bandgap semiconductors significantly affect the performance of power electronic devices. We used the methods imaging ellipsometry (IE) and white light interference microscopy (WLIM) in a hybrid optical metrology study for fast and non-destructive detection, classification, and characterisation of defects in 4H–SiC homoepitaxial layers on 4H–SiC substrates. Ellipsometry measurement results are confirmed by WLIM. They can be successfully applied for wafer characterisation already during production of SiC epilayers and for subsequent industrial quality control.
Small-angle X-ray scattering (SAXS) can be used for structural de- termination of biological macromolecules and polymers in their na- tive states. To improve the reliability of such experiments, the re- duction of radiation damage occurring from exposure to X-rays is needed.One method, is the use of scavenger molecules that protect macromolecules against radicals produced by radiation exposure.In this study we investigate the feasibility to apply the compatible solute, osmolyte and radiation protector Ectoine (THP(B)) as a scavenger throughout SAXS measurements of single-stranded DNA-binding protein Gene-V Protein (G5P/GVP). Therefore we monitor the radiation induced changes of G5P during bio-SAXS. The resulting microscopic energy-damage relation was determined by particle scattering simu- lations with TOPAS/Geant4. The results are interpreted in terms of radical scavenging as well as post-irradiation effects, related to preferential-exclusion from the protein surface. Thus, Ectoine provides an non-disturbing way to improve structure-determination of proteins via bio-SAXS in future studies.
Introduction
Per- and polyfluorinated alkyl substances (PFASs) are a group of over 4730 individual compounds. Several PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their various chemical and physical properties as well as the high number of compounds. Target-based approaches (e.g., LC-MS/MS) are limited to the availability of analytical grade standards and are not suitable for the analysis of new/unknown PFASs and transformation products. Therefore, PFAS sum parameter methods become increasingly important to indicate realistic PFAS pollution levels.
Methods
For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. In our study we used high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) which is a sensitive and highly selective tool for fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification of c(F) 2.7 µg/L.
Results
Here, we present an improved method for the determination of PFASs using HR-CS-GFMAS via GaF detection. The optimized method includes a modifier pretreatment step using a mixture of Mg, Pd and Zr and a correction measurement using perfluorooctanoic acid. The combination of both resulted in increased accuracy and precision as well as overall lower detection limits. Furthermore, during optimization the influence of species-specific responses during HR-CS-GFMAS analysis was reduced resulting in a more accurate determination of PFAS sum parameters. To test the applicability of the improved method, we analysed soil samples from a former fire-fighting training area combining the improved method for detection with our previously optimized extraction method for extractable organically bound fluorine (EOF) determination in soils.
Innovative aspects
• Highly sensitive and selective method for fluorine/PFASs analysis based on HR-CS-GFMAS
• Increased accuracy for the determination of EOF
• Reduction of PFAS species-specific responses by optimized modifier conditions
X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. Our results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.
Ergot alkaloids are a group of mycotoxins occurring in products derived from various grasses (e.g., rye) and have been regulated in the EU recently. The new maximum levels refer to the sum of the six most common ergot alkaloids in their two stereoisomeric forms in different food matrices. Typically, these twelve compounds are individually quantified via HPLC-MS/MS or -FLD and subsequently summed up to evaluate food safety in a time-consuming process. Since all these structures share the same ergoline backbone, we developed a novel sum parameter method (SPM) targeting all ergot alkaloids simultaneously via lysergic acid hydrazide. After extraction and clean-up, in analogy to the current European standard method EN 17425 (ESM) for ergot alkaloid quantitation, the samples were derivatized by an optimized hydrazinolysis protocol, which allowed quantitative conversion after 20 min at 100 °C. The new SPM was evaluated against another established HPLC-FLD-based method (LFGB) and the HPLC-MS/MS-based ESM using six naturally contaminated rye and wheat matrix reference materials. While the SPM provided comparable values to the ESM, LFGB showed deviating results. Determined recovery rates, limits of detection and quantification of all three employed methods confirm that the new SPM is a promising alternative to the classical approaches for ergot alkaloid screening in food.
This contribution attempts to shed light on the application of POD analyses and measurement uncertainty calculations in nondestructive testing of concrete structures to provide useful and quality-assured information for reliability assessments of our built environment - with an emphasis on ground penetrating radar. It is shown that signal processing techniques affect POD analysis results to varying degrees, that measurement uncertainties are useful to validate PODs, and that the utilization of both POD analysis and measurement uncertainty calculations can pave the way to NDT-based reliability assessment, which will be exemplarily demonstrated in conclusion – generally aiming to derive those maintenance strategies and actions that are in line with actual demands.
The reference method for obtaining absolute isotope ratios still is the isotope mixture approach. Due the huge efforts required the full isotope mixture approach is applied only by a few institutes worldwide. To enable an IRWG key comparison with a sufficiently large number of participants a proposal for absolute cu isotope ratios is presented where participants will be provided with the enriched isotopes, the isotope mixtures and the samples. In parallel a pilot study will be organized where alternative approaches for obtaining absolute Cu isotope ratios can be applied.
IRWG strategy update
(2023)
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
Klebeverbindungen sind aus vielen Anwendungen wie dem Leichtbau nicht mehr wegzudenken. Durch die Verklebung gleicher oder ungleicher Materialien entstehen viele Vorteile gegenüber konservativen Fügeverfahren. Jedoch stellen schwache Haftfestigkeiten eine sehr unbeliebte Fehlerart dar, die schlecht zu detektieren sind und zu einem frühzeitigen Versagen der Verklebung bei vergleichsweise geringen Belastungen führen können. Aufgrund hoher Sicherheits- und Qualitätsansprüche wird die Haftfestigkeit dieser Verbindungen jedoch noch immer zerstörend geprüft. Zufriedenstellende zerstörungsfreie Verfahren, um Haftfestigkeiten zu prüfen, sind nicht vorhanden und Thema gegenwärtiger Forschung. Ein Ansatz, der in diesem Projekt verfolgt wird, liegt in der Verwendung geführter Ultraschallwellen.
Hierzu wird anhand von Simulationen mittels der Scaled Boundary Finite Element Methode gezeigt, dass die gezielte Auswertung bestimmter Bereiche des Dispersionsdiagrams, den sogenannten vermiedenen Kreuzungen (engl. mode repulsion regions), eine Charakterisierung der Haftfestigkeiten zulassen könnten. Dies liegt darin begründet, dass die mittleren mechanischen Belastungen der Kleberschicht in diesen Bereichen ein lokales Maximum aufweisen und daher eine erhöhte Sensitivität auf Materialänderungen haben. Es wird gezeigt, wie sensitiv diese Bereiche auf Materialänderungen in der Klebergrenzschicht sind und welche potenziellen Fehlergrößen existieren.
NMR is becoming increasingly popular for the investigation of building materials as it is a non-invasive technology that does not require any sample preparation nor causes damage to the material. Depending on the specific application it can offer insights into properties like porosity and spatial saturation degree as well as pore structure. Moreover it enables the determination of moisture transport properties and the (re-)distribution of internal moisture into different reservoirs or chemical phases upon damage and curing. However, as yet most investigations were carried out using devices originally either designed for geophysical applications or the analysis of rather homogeneous small scale (< 10 mL) samples. This paper describes the capabilities of an NMR tomograph, which has been specifically optimized for the investigation of larger, heterogeneous building material samples (diameters of up to 72 mm, length of up to 700 mm) with a high flexibility due to interchangeable coils allowing for a high SNR and short echo times (50 - 80 m s).
Bisphenol A (BPA) is used in Polycarbonate, Polyacrylic resins, Polysulfones, Epoxy resins, and Polyetherimides. It is also used in recycled Polyvinyl chloride [1–3]. BPA has been classified as a substance of very high concern (SVHC) under REACH [4] due to its endocrine disrupting properties. The German competent authorities want to reduce the content of BPA in the environment. Possible substitutes for BPA are Bisphenol B (BPB), Bisphenol E (BPE),
Bisphenol F (BPF), or Bisphenol S (BPS), as they are similar in structure.
BPA-based materials have a wide area of application especially outside. These outdoor applications are exposed to different external influences, including physical, biological, mechanical and chemical influences. This results in damage and aging of the material with leaching or migration into the environment. There, the substance is transformed by various transformation processes. The emerging metabolites and transformation products (TPs) can have different properties than the parent substance. Understanding the fate and behavior of the emerging pollutants is very important.
Therefore, different transformation products of selected bisphenols will be generated and analyzed:
To investigate the fate of different bisphenols in water treatment plants technical transformation products [5] will be generated by chlorination, ozonization, the Fenton reaction, and UV-radiation.
For the investigation of the fate of Bisphenols in surface water global radiation will be simulated with UVA-lamps
Simulation of phase-I-metabolism with an electrochemical cell coupled to mass spectrometry (EC-MS).
Per- and polyfluoroalkyl substances (PFAS) are a group of anionic, cationic and zwitterionic synthetic products, in which the hydrogen atoms on the carbon skeleton of at least one carbon atom have been completely replaced by fluorine atoms and which include more than 4730 compounds, depending on the definition. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. Furthermore, current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination. In this presentation the advantages of fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy for various environment samples are shown.
For how trivial or provocative it can sound, the best neutron spectrometer in the world does not produce science and technology by itself. By definition of “Materials Science”, neutron scattering data on engineering materials must be used as a tool to understand, and even tailor, materials performance. In order for this to happen, neutron data need to be
1. Acquired under the most relevant condition possible
2. Coupled to other experimental techniques
3. Capitalized by means of proper simulations and data analysis
Point 1- calls for an intense use and the development of top-notch of in-situ techniques; Point 2- means that the sole use of neutron data will not lead to any solution of a global problem; All points above hint to the fact that access to neutron sources is not routine, and therefore it is imperative to search ways to make neutron data rentable and sustainable for the material science and industrial research community.
In this presentation, and based on two examples, we will show a couple of strategies to combine neutron data with other experiments, and with theoretical models to raise the validity of experiments to the level of problem-solving. As one might imagine, these are only a few among the almost infinite combinations possible to help improving material properties, performance, and safety, i.e., ripe for everyday use.
Comparing the performance of molecular and nanoscale luminophores and luminescent microand nanoparticles and estimating achievable signal amplitudes and limits of detection requires a standardizable intensity scale. This initiated the development of the relative MESF (number of molecules of equivalent soluble fluorochromes) and ERF (equivalent reference fluorophores) scales for flow cytometry and fluorescence microscopy. Both intensity scales rely on fluorescence intensity values assigned to fluorescent calibration beads by an intensity comparison to spectrally closely matching fluorophore solutions of known concentration using a spectrofluorometer. Alternatively, the luminophore or bead brightness (B) can be determined that equals the product of the absorption cross section (σa) at the excitation wavelength (σa(λex)) and the photoluminescence quantum yield (Φpl).
Thereby, an absolute scale based on fundamental and measurable spectroscopic properties can be realized which is independent of particle size, material, and luminophore staining or labeling density and considers the sensitivity of the optical properties of luminophores to their environment. Aiming for establishing such a brightness scale for light-scattering dispersions of luminescent particles with sizes exceeding a few ten nanometers, we demonstrate how the brightness of quasi-monodisperse 25 nm, 100 nm, and 1 μm sized polystyrene particles (PSP), loaded with two different dyes in varying concentrations, can be obtained with a single custom-designed integrating sphere setup that enables the absolute determination of Φpl and transmittance and diffuse reflectance measurements. The resulting Φpl, σa(λex), imaginary parts of the refractive index, and calculated B values of these samples are given in dependence of the number of incorporated dye molecule per particle. Finally, a unitless luminescence efficiency (LE) is defined allowing for the direct comparison of luminescence efficiencies of particles with different sizes.
Optimizing the Green Synthesis of ZIF-8 by Reactive Extrusion Using In Situ Raman Spectroscopy
(2023)
We report the scale-up of a batch solid synthesis of zeolitic imidazolate framework-8 (ZIF-8) for reactive extrusion. The crystalline product forms in the extruder directly under the mixture of solid 2-methylimidazole and basic zinc carbonate in the presence of a catalytic amount of liquid. The process parameters such as temperature, liquid type, feeding rate, and linker excess were optimized using the setup specifically designed for in situ Raman spectroscopy. Highly crystalline ZIF-8 with a Brunauer–Emmett–Teller (BET) surface area of 1816 m2 g–1 was quantitatively prepared at mild temperature using a catalytic amount of ethanol and a small excess of the linker. Finally, we developed a simple and comprehensive approach to evaluating the environmental friendliness and scalability of metal–organic framework (MOF) syntheses in view of their large-scale production.
Inorganic nanocrystals with linear and nonlinear luminescence in the ultraviolet, visible, near infrared and short-wave infrared like semiconductor quantum dots and spectrally shifting lanthanide-based nanophosphors have meanwhile found many applications in the life and material sciences. This includes optical reporters for bioimaging and sensing, security and authentication barcodes, solid state lighting, converter materials, and photovoltaics. The identification of optimum particle structures requires quantitative spectroscopic studies under application-relevant conditions, focusing on the key performance parameter photoluminescence quantum yield, ideally flanked by single particle studies to assess spectroscopic inhomogeneities on a particle-to-particle level for typical preparation methods. In this context, methods to quantify the photoluminescence of these different nanoscale emitters are shown and utilized as a basis for a profound mechanistic understanding of the nonradiative deactivation pathways in semiconductor and upconversion nanocrystals of different size and particle architecture in different environments. Exemplary for the application potential of such nanomaterials, in addition, the design of optical sensors from different nanomaterials and functional organic dyes is briefly summarized.
Photodynamic therapy (PDT) used for treating cancer relies on the generation of highly reactive oxygen species, for example, singlet oxygen 1O2, by light-induced excitation of a photosensitizer (PS) in the presence of molecular oxygen, inducing DNA damage in close proximity of the PS. Although many precious metal complexes have been explored as PS for PDT and received clinical approval, only recently, the potential of photoactive complexes of nonnoble metals as PS has been discovered. Using the DNA origami technology that can absolutely quantify DNA strand break cross sections, we assessed the potential of the luminescent transition metal complex [Cr(ddpd)2]3+ (ddpd=N,N’-dimethyl-N,N’-dipyridine-2-ylpyridine-2,6-diamine) to damage DNA in an air-saturated aqueous environment upon UV/Vis illumination. The quantum yield for strand breakage, that is, the ratio of DNA strand breaks to the number of absorbed photons, was determined to 1–4%, indicating efficient transformation of photons into DNA strand breaks by [Cr(ddpd)2]3+.
Gas Chromatography coupled with Electron Ionisation Mass Spectrometry (GC-EI-MS) is a well-established technique which, in combination with spectral libraries, has the potential to identify compounds in a sample. Nevertheless, most libraries are dominated by spectra with nominal mass resolution which does not allow to make full use of the data generated by modern high-resolution instruments. The production of high-resolution spectral library is time consuming and expensive, while in silico fragmentation tools that are capable of generating HR mass spectra are still too computationally intensive. We explored the alternative of using ML models to upscale existing spectral libraries. The models were trained with spectra from the RECETOX metabolome (DOI: 10.5281/zenodo.5483564), RECETOX Exposome (DOI: 10.5281/zenodo.4471216), and MassBank (10.5281/zenodo.7436394) HR-GC-MS libraries. The model was used to generate a synthetic library which was compared with a synthetic library simulated with CFM-ID (DOI: 10.1021/acs.analchem.6b01622).