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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.
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).
The rails of modern railways face an enormous wear and tear from ever increasing train speeds and loads. This necessitates diligent non-destructive testing for defects of the entire railway system.
Non-destructive testing of rail tracks is carried out by rail inspection trains equipped with ultrasonic and eddy current test devices. However, the evaluation of the gathered data is mainly done manually with a strong focus on ultrasonic data, and defects are checked on-site using hand-held testing equipment. Maintenance measures are derived based on these on-site findings.
The aim of the AIFRI project (Artificial Intelligence For Rail Inspection) is to
- increase the degree of automation of the inspection process, from the evaluation of the data to the planning of maintenance measures,
- increase the accuracy of defect detection,
- automatically classify detected indications into risk classes.
These aims will be achieved by training a neural network for defect detection and classification. Since the current testing data is unbalanced, insufficiently labeled and largely unverified we will supplement fused, simulated eddy current and ultrasonic testing data in form of a configurable digital twin.
Non-destructive testing of rail tracks is carried out by using rail inspection cars equipped with ultrasonic and eddy current measurement. The evaluation of test data is mainly done manually, supported by a software tool which pre-selects relevant indications shown to the evaluators. The resulting indications have to be checked on-site using hand-held testing equipment. Maintenance interventions are then derived on the basis of these on-site findings.
Overall aim of the AIFRI (Artificial Intelligence For Rail Inspection) project - funded by the German Federal Ministry of Digital and Transport (BMDV) as part of the mFUND programme under funding code 19FS2014 – is to increase the degree of automation of the inspection process from the evaluation of the data to the planning of maintenance interventions. The accuracy of defect detection shall be increased by applying AI methods in order to enable an automated classification of detected indications into risk classes. For this purpose, data from both eddy current inspections and ultrasonic inspections will be used in combination.
Within the framework of this data-driven project, relevant defect patterns and artefacts present in the rail are analysed and implemented into a configurable digital twin. With the help of this digital twin virtual defects can be generated and used to train AI algorithms for detection and classification. With the help of reliability assessment trained AI algorithms will be evaluated with regard to the resulting quality in defect detection and characterisation.
A particular aspect of the development of AI methods is the data fusion of different NDT data sources: Thereby, synergies are used that arise from linking eddy current and ultrasonic inspection data in a combined model.
In the course of the project a demonstrator consisting of the developed IT-tool and an asset management system will be implemented and tested in the field using real-world data.
Structural health monitoring techniques associate strongly with damage detection and characterization. Ultrasonic guided waves (UGW), for such scope, arise as one of the most promising methods for many reasons i.e. UGW are able to travel long distances and they have high sensitivity to damage. In this context, the necessity to model realistic wave-defect interaction occurs to be critical.
Realistic damage scenarios can be modeled through the usage of image-based quadtree meshes. Images, such as the outcome from X-ray scans, C-scans, etc., can be converted into meshes for further integration in a computational domain. Quadtree meshes are created by converting the intensity of the pixels to quadrilateral cells. Homogeneous regions inside one image result in one quad, whereas fine features such as discontinuities can be described with smaller quads.
This contribution proposes an efficient methodology to model wave defect interaction, using as a framework the scaled boundary finite element method (SBFEM) and quadtree meshes. Problems as non-conforming regions in the mesh due to the space tree decomposition can be easily avoided using SBFEM’s polygonal elements. Moreover, the semi-analytical nature of the SBFEM allows the modeling of arbitrarily long prismatic/undamaged regions of the waveguides without an increase in the computational burden.
Natural and synthetic estrogens are key endocrine-disrupting chemicals. Despite occurring at ultra-trace levels (below ng L-1), it is believed that they are contributing to an increase in feminized fish and other endocrine disruptive effects, and hence, their inclusion in the Watch list was not unexpected. One of the main sources ofestrogens to surface waters is wastewater effluent. Once in surface waters, they can partition into different compartments, i.e., water and suspended particulate matter. For this reason, there is an urgent need for a methodology to monitor estrogen levels below the environmental quality standards (EQS) set by the Water Framework Directive requirements.
In this study, a precise and accurate gas chromatography-mass spectrometry method (GC-MS/MS) for the analysis of estrone (E1), 17β-estradiol (17β-E2), 17α-estradiol (17α- E2), 17-alpha-ethinylestradiol (EE2), and estriol (E3) in whole water samples with ng L-1 limit of quantification (LOQ) was developed and validated in accordance with CEN/TS 16800:2020 guidelines.
Monitoring programs should generate high-quality data on the concentrations of substances and other pollutants in the aquatic environment to enable reliable risk assessment. Furthermore, the need for comparability over space and time is critical for analysis of trends and evaluation of restoration of natural environment. Additionally, research work and exercises at the European level have highlighted that reliable measurements of estrogenic substances at the PNEC level are still challenging to achieve.
The project EDC-WFD Metrology for monitoring endocrine disrupting compounds under the EU Water Framework Directive aims to develop traceable analytical methods for determining endocrine disrupting compounds and their effects, with a specific focus on three estrogens of the first watch list (17-beta-estradiol (17βE2), 17-alpha-ethinylestradiol (EE2), and estrone (E1)). Estrogens 17-alpha-estradiol (17E2) and estriol (E3) will be included to demonstrate the reliability of the developed methods and to support the requirements of Directive 2013/39/EC, Directive 2009/90/EC and Commission Implementation Decision (EU) 2018/840, hence improving the comparability and compatibility of measurement results within Europe. During the EDC-WFD project four selected effect-based methods (EBM) will be deeply investigated in order to improve their rationale use and their support in water quality assessment. In particular, the EBM sensitivity, specificity and accuracy on reference materials with single or mixture solutions of the five substances at a concentration of EQS values will be explored.
This contribution will present the objectives and methods applied within the EDC-WFD project.
Chromium(III) complexes can show phosphorescence from the spin-flip excited doublet states 2E/2T1 in the near-infrared with high photoluminescence quantum yields and extremely long lifetimes in the absence of dioxygen. The prototype molecular ruby, [Cr(ddpd)2]3+ (ddpd = N,N’-dimethyl-N,N’-dipyridine-2-ylpyridine-2,6-diamine), has a photoluminescence quantum yield and a luminescence lifetime of 13.7% and 1.1 ms in deaerated acetonitrile, respectively. However, its luminescence is strongly quenched by 3O2 via an efficient Dexter-type energy transfer process. To enable luminescence applications of molecular rubies in solution under aerobic conditions, we explored the potential of sterically demanding ddpd ligands to shield the chromium(III) center from O2 using steady state and time-resolved photoluminescence spectroscopy. The structures of the novel complexes with sterically demanding ligands were investigated by single crystal X-ray diffraction and quantum chemically by density functional theory calculations. The O2 sensitivity of the photoluminescence was derived from absolutely measured photoluminescence quantum yields and excited state lifetimes under inert and aerobic conditions and by Stern–Volmer analyses of these data. Optimal sterically shielded chromium(III) complexes revealed photoluminescence quantum yields of up to 5.1% and excited state lifetimes of 518 μs in air-saturated acetonitrile, underlining the large potential of this ligand design approach to broaden the applicability of highly emissive chromium(III) complexes.
pH and oxygen are amongst the most important and frequently measured analytes in the life and material sciences, indicating, e.g., diseases and corrosion processes. This includes the optical monitoring of pH in living cells for studying cellular internalization pathways, such as phagocytosis, endocytosis, and receptor ligand internalization with the aid of molecular and nanoscale fluorescent sensors. Nanoparticle (NP)-based sensors, that are labeled or stained with a multitude of sensor dyes, have several advantages as compare to conventional molecular probes like enhanced brightness, i.e., amplified signals, ease of designing ratiometric systems by combining analyte sensitive and inert reference dyes, and increased photostability. Moreover, this can enable the use of hydrophobic dyes in aqueous environments. Versatile templates and carriers for the fabrication of nanosensors by the staining and/or labelling with different fluorophores and sensor molecules or surface functionalized NP like silica (SiO2-NP) and polystyrene (PS-NP) particles provide. Here we present the design of a versatile platform of color emissive nanosensors and stimuli-responsive microparticles for the measurement of pH, oxygen, and other targets utilizing both types of matrices and sets of spectrally distinguishable sensor and reference dyes and their characterization and demonstrate the applicability of representative sensor particle for cellular studies.
Bioanalytical, diagnostic, and security applications require the fast and sensitive determination of a steadily increasing number of analytes or events in parallel in a broad variety of detection formats and increased sensitivities. This – flanked by recent technical advancements and the availability of simple to use, commercial time-resolved photoluminescence measuring devices at reasonable costs - calls for the exploitation of the species- and environment-specific photoluminescence parameter luminescence lifetime. In this context, time-resolved photoluminescence measurements of different classes of molecular and nanocrystalline emitter and luminescent particles in different time windows are presented and examples for applications such as lifetime multiplexing and barcoding in conjunction with fluorescence lifetime imaging microscopy (FLIM) and flow cytometry are given.
Due to their unique physico-chemical properties, nanoparticles are well established in research and industrial applications. A reliable characterization of their size, shape, and size distribution is not only mandatory to fully understand and exploit their potential and develop reproducible syntheses, but also to manage environmental and health risks related to their exposure and for regulatory requirements. To validate and standardize methods for the accurate and reliable particle size determination nanoscale reference materials (nanoRMs) are necessary. However, there is only a very small number of nanoRMs for particle size offered by key distributors such as the National Institute of Standards and Technology (NIST) and the Joint Research Centre (JRC) and, moreover, few provide certified values. In addition, these materials are currently restricted to polymers, silica, titanium dioxide, gold and silver, which have a spherical shape except for titania nanorods. To expand this list with other relevant nanomaterials of different shapes and elemental composition, that can be used for more than one sizing technique, we are currently building up a platform of novel nanoRMs relying on iron oxide nanoparticles of different shape, size and surface chemistry. Iron oxide was chosen as a core material because of its relevance for the material and life sciences.
What is meant by ‘Micro Non-Destructive Testing and Evaluation’? This was the central subject of debate in this Special Issue.
At present, sub-millimeter-size components or even assemblies are pervading the industrial and scientific world. Classic examples are electronic devices and watches (as well as parts thereof), but recent examples encompass additively manufactured lattice structures, stents, or other microparts. Moreover, most assemblies contain micro-components. Testing such components or their miniaturized parts would fit well within the topic of micro non-destructive testing and evaluation.
In all cases, performance and integrity testing, quality control, and dimensional tolerances need to be measured at the sub-millimeter level (ideally with a spatial resolution of about a micron); most of the time, such features and components are embedded in much larger assemblies, which also need to be taken into account. The solution to this dilemma (i.e. measuring large parts with high resolution) depends on the part and on the problem under consideration.
Another possible definition of micro non-destructive testing and evaluation can relate to the characterization of micro-features (e.g., the microstructure) in much larger specimens, such as damage in concrete cores or porosity in additively manufactured components. A further aspect is the use of microscopic probes to evaluate macroscopic properties. This is the case, for instance but not at all exclusively, in the use of diffraction techniques to determine macroscopic stress.
The splits between testing and characterization at the micro-level (or of micro parts) from one side and handling of macroscopic assemblies on the other represent a great challenge for many fields of materials characterization. On top of that, including the use of microscopic methods to test integrity would add a further level of complexity.
Imaging, mechanical testing, non-destructive testing, measurement of properties, structural health monitoring, and dimensional metrology all need to be re-defined if we want to cope with the multi-faceted topic of micro non-destructive testing and evaluation.
The challenge has already been accepted by the scientific and engineering communities for a while but is still far from being universally tackled. This Special Issue yields an interesting answer to the questions posed above. It presents the progress made and the different aspects of the challenge as well as at indicates the paths for the future of NDT&E.
This paper discusses the feasibility of a novel strategy based on the combination of bioprinting nano-doping technology and laser ablation-inductively coupled plasma time-of-flight mass spectrometry analysis for the preparation and characterization of gelatin- based multi-element calibration standards suitable for quantitative imaging. To achieve this, lanthanide up-conversion nanoparticles were added to a gelatin matrix to produce the bioprinted calibration standards. The features of this bioprinting approach were com- pared with manual cryosectioning standard preparation, in terms of throughput, between batch repeatability and elemental signal homogeneity at 5 μm spatial resolution. By using bioprinting, the between batch variability for three independent standards of the same concentration of 89 Y (range 0–600 mg/kg) was reduced to 5% compared to up to 27% for cryosectioning. On this basis, the relative standard deviation ( RSD ) obtained between three independent calibration slopes measured within 1 day also reduced from 16% (using cryosectioning ) to 5% (using bioprinting), supporting the use of a single standard preparation replicate for each of the concentrations to achieve good calibration performance using bioprinting. This helped reduce the analysis time by approximately 3-fold. With cryosectioning each standard was prepared and sectioned individually, whereas using bio-printing it was possible to have up to six different standards printed simultaneously, reducing the preparation time from approximately 2 h to under 20 min (by approxi- mately 6-fold). The bio-printed calibration standards were found stable for a period of 2 months when stored at ambient temperature and in the dark.
A solvothermal method was used to prepare a series of Yb3+/Tm3+/Ca2+ co-doped NaYF4 nanoparticles with different Ca2+ contents. Strong upconversion blue fluorescence could be observed under 980 nm laser excitation of the samples. The effect of different Ca2+ contents on the luminescence intensity was investigated, and it was found that the UV-vis upconversion luminescence increased and then decreased with an increasing Ca2+ concentration during the increase of the Ca2+ content from 0 mol% to 25 mol%, reaching the strongest fluorescence at 15 mol%, which was up to about 28 times stronger than that without Ca2+ doping. Furthermore, the mechanism was investigated, and it was found that the doping of Ca2+ disrupted the symmetry of the crystal field, resulting in a significant enhancement of the overall fluorescence. Applied to fluorescence intensity ratio thermometry, the absolute and relative sensitivities are as high as 0.0418 K−1 and 2.31% K−1, respectively, with a minimum temperature resolution of 0.0129 K.
The 18O/16O ratio of cherts (δ18Ochert) increases nearly monotonically by ~15‰ from the Archean to present. Two end-member explanations have emerged: cooling seawater temperature (TSW) and increasing seawater δ18O (δ18Osw). Yet despite decades of work, there is no consensus, leading some to view the δ18Ochert record as pervasively altered.
Here, we demonstrate that cherts are a robust archive of diagenetic temperatures, despite metamorphism and exposure to meteoric fluids, and show that the timing and temperature of quartz precipitation and thus δ18Ochert are determined by the kinetics of silica diagenesis. A diagenetic model shows that δ18Ochert is influenced by heat flow through the sediment column. Heat flow has decreased over time as planetary heat is dissipated, and reasonable Archean-modern heat flow changes account for ~5‰ of the increase in δ18Ochert, obviating the need for extreme TSW or δ18Osw reconstructions. The seawater oxygen isotope budget is also influenced by solid Earth cooling, with a recent reconstruction placing Archean δ18OSW 5 to 10‰ lower than today. Together, this provides an internally consistent view of the δ18Ochert record as driven by solid Earth cooling over billion-year timescales that is compatible with Precambrian glaciations and biological.
One-pot covalent functionalization of 2D black phosphorus by anionic ring opening polymerization
(2022)
In this work, a one-pot approach for the covalent functionalization of few-layer black phosphorus (BP) by anionic ring opening polymerization of glycidol to obtain multifunctional BP-polyglycerol (BP-PG) with high amphiphilicity for near-infrared-responsive drug delivery and biocompatibility is reported. Straightforward synthesis in combination with exceptional biological and physicochemical properties designates functionalized BP-PG as a promising candidate for a broad range of biomedical applications.
The Federal Institute for Materials Research and Testing (BAM) organised an interlaboratory comparison (ILC) for the characterisation of 87Sr/86Sr isotope ratios in limestone (IAG/CGL ML-3) and Penrhyn slate (IAG OU-6) reference materials by applying the conventional method for 87Sr/86Sr isotope ratios. Samples were sent to thirteen analytical laboratories . Since both samples are powdered, rock materials, dissolution of the sample and Sr isolation via ion exchange chromatography were mandatory. This was done using acid, microwave/acid, bomb/acid digestion or borate fusion and subsequent isolation of Sr by means of commercially available ion exchange resins. In this study, we present and discuss the potential effects that differences between laboratories, and between two instrumental measurement techniques (i.e., MC-ICP-MS and MC-TIMS), may have upon the dispersion of measurement results of the 87Sr/86Sr isotope ratio in the two aforementioned reference materials. We used a statistical mixed effects model to assess the potential effects of both the laboratory and the measurement technique. Consensus values for both materials and associated standard uncertainties {(IAG/CGL ML-3 (0.708245±0.000004) mol/mol; IAG OU-6 (0.729769±0.000008) mol/mol} were estimated by fitting a linear, Gaussian mixed effects model (Pinheiro and Bates 2000) using the R function “lmer” defined in package “lme4”. The statistical results showed that there is no significant effect attributable to differences between instrumental techniques when both materials are considered together, or separately. The p-value of the test of significance of the measurement technique effect is greater than 0.54. For both materials there were statistically significant effects attributable to differences between laboratories when the measurement results for both materials were considered together and separately. This effect is less than 0.00004 in absolute value. However, for neither material did consideration or disregard for such differences induce significant changes in the estimate of the consensus value for the 87Sr/86Sr isotope ratio. Therefore, the effects attributable to differences between instrumental techniques or between laboratories can safely be disregarded when computing the best estimate for the true value of 87Sr/86Sr isotope ratio in these materials, by the community of expert laboratories represented in this study.
Nanoparticles (NPs) have become important materials for a variety of chemical technologies, including catalysis. One of the main challenges is the reduction of green house gases, such as CO2. One opportunity besides the capturing is the conversion to synthesis gas via the reverse water-gas shift reaction.
A facile and efficient method is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core-shell NPs. The diameter of the NPs can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio from 30:1 to 1:1. The NPs are structurally characterized with combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray photoelectron spectroscopy, and X-ray absorption fine structure. Using these analytical methods, a core-shell-shell structure their chemical composition is elucidated. A depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core-shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction).
Since its discovery, graphene has got growing attention in the industrial and application research due to its unique properties . However, graphene has not been yet implemented into the industrial market, in particularly due to the difficulty of properly characterizing this challenging material. As most of other nanomaterials, graphene’s properties are closely linked to its chemical and structural properties, such as number of layers, flake thickness, degree of functionalisation and C/O ratio. For the commercialization, suitable procedures for the measurement and characterization of the ultrathin flakes, of lateral dimensions in the range from µm to tens of µm, are essential.Surface chemical methods, especially XPS, have an outstanding role of providing chemical information on the composition. Thereby, one well-known problem for surface analytical methods is the influence of contamination on the composition as in the case of adventitious carbon. The differentiation between carbon originated from the contamination or from the graphene sample itself is often not obvious, which can lead to altered results in the determination of the composition. To overcome this problem, Hard Energy X-ray Photoelectron Spectroscopy (HAXPES) offers new possibilities due to its higher information depth. Therefore, XPS measurement obtained with Al Kα radiation (E = 1486. 6 eV) were compared with analyses performed with a Cr Kα (E = 5414. 8 eV) excitation on functionalized graphene samples. Differences are discussed in terms of potential carbon contamination, but also of oxygen on the composition of the samples. Measurements are performed on O-, N- and F-functionalized graphene. Different preparation procedures (powder, pellet, drop cast from liquid suspension) will be also discussed, correlation of the results with the flakes morphology as well as their validation with other independent methods are in progress.
X-ray absorption spectroscopy (XAS) provides a unique, atom-specific tool to probe the electronic structure of solids. By surmounting long-held limitations of powder-based XAS using a dynamically averaged powder in a Resonant Acoustic Mixer (RAM), we demonstrate how time-resolved in situ (TRIS) XAS provides unprecedented detail of mechanochemical synthesis. The use of a custom-designed dispersive XAS (DXAS) setup allows us to increase the time resolution over existing fluorescence measurements from ∼15 min to 2 s for a complete absorption spectrum. Hence, we here establish TRIS-XAS as a viable method for studying mechanochemical reactions and sampling reaction kinetics. The generality of our approach is demonstrated through RAM-induced (i) bottom-up Au nanoparticle mechanosynthesis and (ii) the synthesis of a prototypical metal organic framework, ZIF-8. Moreover, we demonstrate that our approach also works with the addition of a stainless steel milling ball, opening the door to using TRIS-DXAS for following conventional ball milling reactions. We expect that our TRIS-DXAS approach will become an essential part of the mechanochemical tool box.
In mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics.
In mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics.
In mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics. heuristics.
In mass spectrometry based proteomics, protein homology leads to
many shared peptides within and between species. This complicates
taxonomic inference. inference. We introduce PepGM, a graphical model for taxonomic profiling of viral proteomes and metaproteomic datasets.
Using the graphical model, our approach computes statistically sound
scores for taxa based on peptide scores from a previous database
search, eliminating the need for commonly used heuristics. heuristics.
Probability based taxonomic profiling of viral and microbiome samples using PepGM and Unipept
(2022)
In mass spectrometry based proteomics, protein homology leads to many shared peptides within and between species. This complicates
taxonomic inference in samples of unknown taxonomic origin. PepGM uses a graphical model for taxonomic profiling of viral proteomes and
metaproteomic datasets providing taxonomic confidence scores. To build the graphical model, a list of potentially present taxa needs to be
inferred. To this end, we integrate Unipept, which enables the fast querying of potentially present taxa. Together, they allow for taxonomic
inference with statistically sound confidence scores.
In general, wind turbines transform the kinetic energy of the wind into electric power. Thereby, the wind turbine blades are facing unsteady loads which are transferred to the hub to generate a rotation of the turbine’s axis. This brief introduction focuses on the aerodynamics of the blades and the corresponding loads. Starting with the basic flow field and loads of an airfoil, terms like stagnation point, boundary layer, Reynolds number, transition, and separation are introduced. For different geometries, lift and drag coefficient curves are discussed. Then, full wings will be considered, including their three-dimensional flow field due to wing tip vortices and crossflows. As a main source of increased loads, unsteady effects are explained in more detail such as gusts, tower passing, earth boundary layer crossing, free stream turbulences, yaw misalignment, etc. At the end, extra loads due to an oscillating free stream are introduced.
With the online coupling (or hyphenation) of chemically-resolved spectroscopy detection with classical size-exclusion chromatography (SEC) it is possible to correlate polymer molecular size with chemical structure in a single in-situ or on-flow measurement. Medium-resolution 1H-NMR (60 MHz) spectroscopy (i.e., “desktop NMR”) and Fouriertransform Infrared Spectroscopy (FTIR) have both been developed as coupled methods (SEC-MR-NMR, SEC-FTIR) for the detection of polymer analytes by monitoring e.g. alkene or carbonyl functionality.1,2 Here, we have investigated the potential for the detection of polymer end groups, using a slightly higher field-strength spectrometer (80 MHz 1H Larmor frequency) and taking advantage of a columnless injection method that provides bulk spectra for reference. End-functionalized polymers were synthesized by reaction of PEG with toluene isocyanate, yielding ,-functionalized polymers with exactly 2 IR- and NMR-detectable functional groups per chain, as proven by MALD-TOF mass spectrometry. We have investigated the sensitivity (limit of detection) and spectral resolution for these functional groups in chloroform, THF, and water. Results have demonstrated a good feasibility for the simultaneous online detection of PEG backbone (M~4000 g/mol) and these end groups at the level of ca. 2 mol%.
We interpret solving the multi-vehicle routing problem as a team Markov game with partially observable costs. For a given set of customers to serve, the playing agents (vehicles) have the common goal to determine the team-optimal agent routes with minimal total cost. Each agent thereby observes only its own cost. Our multi-agent reinforcement learning approach, the so-called multi-agent Neural Rewriter, builds on the single-agent Neural Rewriter to solve the problem by iteratively rewriting solutions. Parallel agent action execution and partial observability require new rewriting rules for the game. We propose the introduction of a so-called pool in the system which serves as a collection point for unvisited nodes. It enables agents to act simultaneously and exchange nodes in a conflict-free manner. We realize limited disclosure of agent-specific costs by only sharing them during learning. During inference, each agents acts decentrally, solely based on its own cost. First empirical results on small problem sizes demonstrate that we reach a performance close to the employed OR-Tools benchmark which operates in the perfect cost information setting.
Hybrid optical measurement technique for detection of defects in epitaxially grown 4H-SiC layers
(2022)
Recent developments in power electronics require the use of new wide bandgap compound semiconductors. Silicon carbide (SiC) is one of the most promising materials for power electronics due to its outstanding properties and commercial availability. Some types of defects in the SiC substrates or homoepitaxial SiC layers can affect the performance of electronic devices in a serious manner or make its operation even impossible. Optical methods such as imaging ellipsometry (IE) and white light interference microscopy (WLIM) were applied for fast and non-contact investigation of defects in the epitaxially grown 12 µm 4H-SiC layers on 4H- SiC substrates.
Ellipsometry enables the investigation of material properties over a broad spectral range. As a fast and non-destructive method, it is widely used in industry for quality assurance. Despite the wide application of ellipsometry and its high industrial relevance there are some material-specific standards and there have been no generally accepted standards dealing with model validation and measurement uncertainties. The first German standard DIN50989-1: 2018 Ellipsometry – Part1: Principles (currently international standard ISO 23131: 2021) marks the beginning of a 6-part standard series for ellipsometry, which was developed under consideration of GUM.
Luminescent semiconductor quantum dots (QDs) are frequently used in the life and material sciences as reporter for bioimaging studies and as active components in devices such as displays, light-emitting diodes, solar cells, and sensors. Increasing concerns regarding the use of toxic elements like cadmium and lead, and hazardous organic solvents during QD synthesis have meanwhile triggered the search for heavy-metal free QDs using green chemistry syntheses methods. Interesting candidates are ternary AgInS2 (AIS) QDs that exhibit broad photoluminescence (PL) bands, large effective Stokes shifts, high PL quantum yields (PL QYs), and long PL lifetimes, which are particularly beneficial for applications such as bioimaging, white light-emitting diodes, and solar concentrators. In addition, these nanomaterials can be prepared in high quality with a microwave-assisted (MW) synthesis in aqueous solution. The homogeneous heat diffusion and instant temperature rise of the MW synthesis enables a better control of QD nucleation and growth and thus increases the batch-to-batch reproducibility. In this study, we systematically explored the MW synthesis of AIS/ZnS QDs by varying parameters such as the order of reagent addition, precursor concentration, and type of stabilizing thiol ligand, and assessed their influence on the optical properties of the resulting AIS/ZnS QDs. Under optimized synthesis conditions, water-soluble AIS/ZnS QDs with a PL QY of 65% and excellent colloidal and long-term stability could be reproducible prepared.
Binary photoluminescent semiconductor nanocrystals (quantum dots, QDs) are one of the best studied fluorescent nanomaterials, and their unique optoelectronic properties paved the road to many applications in (bio)nanophotonics, optoelectronics, and photovoltaics. However, concerns related to their toxic constituents like cadmium or lead and the emerging interest in greener chemistry synthesis approaches hamper their future applicability. Interesting alternatives for some applications like biosensing or bioimaging are heavy-metal-free ternary QDs like AgInS2 (AIS), CuInS2 (CIS), and quaternary QDs such as AIS-ZnS (ZAIS). In this context, we explored the effect of ligand denticity on the organic-to-aqueous phase transfer of oleylamine-stabilized ZAIS QDs with the hydrophilic ligands mercaptopropionic acid (MPA), dihydrolipoic acid (DHLA), and 3-mercapto-2,2-bis(mercaptomethyl)propanoic acid (3MPA), bearing mono-, bi-, and trialkyl thiol groups. Spectroscopic studies of the resulting water-dispersible ZAIS QDs revealed a considerable influence of ligand denticity and ligand-to-QD ratio on the spectral position and width (FWHM; full width at half-maximum) of the photoluminescence (PL) bands, the PL quantum yields (PL QY), and the PL decay kinetics. Thiol capping and phase transfer resulted in a loss in PL by at least a factor of 2. The ligand-induced PL quenching observed particularly for ligands bearing two or three thiol groups was attributed to the facilitated formation of surface-bound disulfides. The best colloidal stability under high dilution conditions was observed for 3MPA.
Introduction:
With the introduction of accurate deep learning predictors, spectral matching applications might experience a renaissance in tandem mass spectrometry (MS/MS) driven proteomics. Deep learning models, e.g., Prosit, predict complete MS/MS spectra from peptide sequences and give the unprecedented ability to accurately predict mass spectra that may arise from any given proteome. However, the amount of spectral data is enormous when querying large search spaces, e.g., metaproteomes composed of many different species.
Current spectral library search software, such as SpectraST, is not equipped to meet run time and memory constraints imposed by such large MS/MS databases, covering several millions of peptide spectrum predictions.
Methods:
Inspired by the fragment index data structure that had been introduced with MSFragger, we implement an efficient peak matching algorithm for computing spectral similarity between query and library spectra. Mistle (Metaproteomic index and spectral library search engine) uses index partitioning and SIMD (Single instruction, multiple data) intrinsics, which greatly improves speed and memory efficiency for searching large spectral libraries. Mistle is written in C++20 and highly parallelized.
Results:
We demonstrate the efficiency of Mistle on two predicted spectral libraries for the lab-assembled microbial communities 9MM and SIHUMIx. Compared to the spectral library search engine SpectraST, Mistle shows a >10-fold runtime improvement and is also faster than msSLASH, which uses locality-sensitive hashing. Although Mistle is slower than MSFragger, Mistle‘s memory footprint is an order of magnitude smaller. Furthermore, we find evidence that the spectral matching approach to predicted libraries identifies peptides with higher precision. Mistle detects peptides not found by database search via MSFragger and in turn uncovers unnoticed false discoveries among their matches.
Conclusion:
In this study, we show that predicted spectral libraries can enhance peptide identification for metaproteomics. Mistle provides the means to efficiently search large-scale spectral libraries, highlighted for the microbiota 9MM and SIHUMIx.
Driven by recent technological advances and the need for improved viral diagnostic applications, mass spectrometry-based proteomics comes into play for detecting viral pathogens accurately and efficiently. However, the lack of specific algorithms and software tools presents a major bottleneck for analyzing data from host-virus samples. For example, accurate species- and strain-level classification of a priori unidentified organisms remains a very challenging task in the setting of large search databases. Another prominent issue is that many existing solutions suffer from the protein inference issue, aggravated because many homologous proteins are present across multiple species. One of the contributing factors is that existing bioinformatic algorithms have been developed mainly for single-species proteomics applications for model organisms or human samples. In addition, a statistically sound framework was lacking to accurately assign peptide identifications to viral taxa. In this presentation, an overview is given on current bioinformatics developments that aim to overcome the above-mentioned issues using algorithmic and statistical methods. The presented methods and software tools aim to provide tailored solutions for both discovery-driven and targeted proteomics for viral diagnostics and taxonomic sample profiling. Furthermore, an outlook is provided on how the bioinformatic developments might serve as a generic toolbox, which can be transferred to other research questions, such as metaproteomics for profiling microbiomes and identifying bacterial pathogens.
Calibration-free methods in laser-induced breakdown spectroscopy, CF LIBS, serve as an alternative to calibration-based LIBS techniques. Their major advantage is the ability for fast chemical analysis in situations where matrix-matched standards are not readily available (as, e.g., in the analysis of biological materials and remote analysis) or amount of samples are limited. Their main applications are in the industry, geology, biology, archeology, and even space exploration. This chapter overviews the principle of operation and performance of CF LIBS techniques.
Protein adsorption at the air–water interface is a serious problem in cryogenic electron microscopy (cryoEM) as it restricts particle orientations in the vitrified ice-film and promotes protein denaturation. To address this issue, the preparation of a graphene-based modified support film for coverage of conventional holey carbon transmission electron microscopy (TEM) grids is presented. The chemical modification of graphene sheets enables the universal covalent anchoring of unmodified proteins via inherent surface-exposed lysine or cysteine residues in a one-step reaction. Langmuir–Blodgett (LB) trough approach is applied for deposition of functionalized graphene sheets onto commercially available holey carbon TEM grids. The application of the modified TEM grids in single particle analysis (SPA) shows high protein binding to the surface of the graphene-based support film. Suitability for high resolution structure determination is confirmed by SPA of apoferritin. Prevention of protein denaturation at the air–water interface and improvement of particle orientations is shown using human 20S proteasome, demonstrating the potential of the support film for structural biology.
In order to detect small and hidden material defects or micro-cracks, weak and localized magnetic stray fields need to be detected and characterized on the magnetic surface. Current flux leakage sensor elements are rigid and rely on air gaps to detect stray fields several hundred micrometers above the surface. Furthermore, the increasing complexity of critical components, enabled by novel fabrication technologies, primarily additive manufacturing, poses a significant challenge to the available flux leakage testing technologies.
The emergence of flexible magneto-electronics paves the way to a compliant form of magnetic sensors that, on one hand, are able to adapt to highly curved surfaces, allowing these measurements to be conducted on irregularly formed components, which are inaccessible for nowadays electromagnetic NDT equipment and, on the other hand, could enhance the detection limit for small magnetic stray fields, by allowing the magneto-sensitive elements to approximate the object’s surface until only a few µm, mediated by thin and flexible packaging.
In ultrasonic testing, the time of flight (ToF) of a signal can be used to infer material and structural properties of a test item. In dispersive media, extracting the bulk wave velocity from a received signal is challenging as the waveform changes along its path of propagation. When using signal features such as the first peak or the envelope maximum, the calculated velocity changes with the propagation distance. This does not occur when picking the signal onset. Borrowing from seismology, researchers used the Akaike information criterion (AIC) picker to automatically obtain onset times. In addition to being dependent on arbitrarily set parameters, the AIC picker assumes no prior knowledge of the spectral properties of the signal. This is unnecessary in ultrasonic through-transmission testing, where the signal spectrum is known to differ significantly from noise. In this contribution, a novel parameter-free onset picker is proposed, that is based on a spectral entropy criterion (SEC) to model the signal using the AIC framework. Synthetic and experimental data are used to compare the performance of SEC and AIC pickers, showing an improved accuracy for densely sampled data.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in North Macedonia. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
Climate change and related energy policies, exacerbated by unforeseen geopolitical developments, pose new challenges for gas analytics, such as the use of hydrogen, hydrogen-containing alternative gaseous fuels (NH3, etc.), the use of alternative methane-based energy gases (LNG, LPG, etc.) or decarbonisation via CCSU. In all topics, the quality, i.e. the actual chemical composition of the gases, naturally plays a decisive role. BAM is meeting this strategic importance with the further development of hydrogen analytics and is continuing to develop the methods used in order to support the German economy and research landscape with traceability, reference materials and analytical procedures as quickly as possible.
Mass spectrometry plays an important role for trace analysis in hydrogen matrix. The presentation shows first experimental results from the application of PTR-TOF-MS (Proton Transfer Reaction Time-of-Flight Mass Spectrometry).
Mycotoxins (toxins formed by fungi) in food and have caused problems for mankind since the beginning of time. The group of ergot alkaloids plays a special role in human history. Several tens of thousands of deaths during the middle ages caused by to ergotism (the disease caused by continuous intake of ergot alkaloid contaminated food) underscore the importance of reliable analytical methods to ensure food safety.
More than 50 compounds belong to the group of ergot alkaloids. The 12 most found structures – the major ergot alkaloids – are typically measured, when it comes to ergot alkaloid quantification. High performance liquid chromatography (HPLC) with a fluorescence detector (FLD) is typically used to quantify the ergot alkaloid content. The main disadvantage of this method are the high costs for calibration standards (12 different calibration substances are required). But also the time and effort required for the analysis of 12 peaks and overlapping signals that occur in complex food samples such as bread. As all ergot alkaloids share the ergoline structure and just differ in the substituents attached to this backbone, measurement of all ergot alkaloids in one sum parameter presents a time and cost saving alternative. The most important step for the development of such a sum parameter method is the reaction used to transfer all ergot alkaloids to one uniform structure. In the talk two promising reactions, the acidic esterification to lysergic acid methyl ester and hydrazinolysis to lysergic acid hydrazide, are examined for possible use in a routine analysis method. In addition to yield and reaction rate, factor such as the handling of the reaction and the possibility of parallelization play a role. Next to the current status of the ongoing research project, in this talk, current approaches to ergot alkaloid quantitation will be discussed.
The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. The integration of data obtained from pulse echo immersion ultrasound testing and radiography holds immense potential to help improve the reliability of non-destructive evaluation. In this study, distinctive features obtained from single techniques, traditional ultrasonic pulse echo testing, and radiography, as well as fused images, were investigated and the suitability of these distinctive features and fusion techniques for improving the probability of defect detection was evaluated. For this purpose, aluminum single lap joints with brass inclusions were analyzed using ultrasound pulse echo and radiography techniques. The distinctive features were extracted from the data obtained, and images of features obtained by both techniques were fused together. Different combinations of features and fusion algorithms were investigated, considering the desire to automate data evaluation in the future.
Validation of novel ultrasonic phased array borehole probe by using simulation and measurement
(2022)
Low-frequency ultrasonic testing is a well-established non-destructive testing (NDT) method in civil engineering for material characterization and the localization of cracks, reinforcing bars and delamination. A novel ultrasonic borehole probe is developed for in situ quality assurance of sealing structures in radioactive waste repositories using existing research boreholes. The aim is to examine the sealing structures made of salt concrete for any possible cracks and delamination and to localize built-in components. A prototype has been developed using 12 individual horizontal dry point contact (DPC) shear wave transducers separated by equidistant transmitter/receiver arrays. The probe is equipped with a commercially available portable ultrasonic flaw detector used in the NDT civil engineering industry. To increase the sound pressure generated, the number of transducers in the novel probe is increased to 32 transducers. In addition, the timed excitation of each transducer directs a focused beam of sound to a specific angle and distance based on the previously calculated delay time. This narrows the sensitivity of test volume and improves the signal-to-noise ratio of the received signals. In this paper, the newly designed phased array borehole probe is validated by beam computation in the CIVA software and experimental investigations on a half-cylindrical test specimen to investigate the directional characteristics. In combination with geophysical reconstruction methods, it is expected that an optimised radiation pattern of the probe will improve the signal quality and thus increase the reliability of the imaging results. This is an important consideration for the construction of safe sealing structures for the safe disposal of radioactive or toxic waste.
Mycotoxins (toxic compounds formed by fungi) in food and feed have caused problems for mankind since the beginning of time. The group of ergot alkaloids plays a special role in human history. Several tens of thousands of deaths during the middle ages caused by to ergotism (the disease caused by continuous intake of ergot alkaloid contaminated food) underscore the importance of reliable analytical methods to ensure food safety.
More than 50 compounds belong to the group of ergot alkaloids. The 12 most found structures – the major ergot alkaloids – are typically measured, when it comes to ergot alkaloid quantification. High performance liquid chromatography (HPLC) with a fluorescence detector (FLD) is typically used to quantify the ergot alkaloid content. The main disadvantage of this method are the high costs for calibration standards (12 different calibration substances are required). But also, the time and effort required for the analysis of 12 peaks and overlapping signals that occur in complex food samples such as bread. As all ergot alkaloids share the ergoline structure and just differ in the substituents attached to this backbone, measurement of all ergot alkaloids in one sum parameter presents a time and cost saving alternative. The most important step for the development of such a sum parameter method is the reaction used to transfer all ergot alkaloids to one uniform structure. Two promising reactions, the acidic esterification to lysergic acid methyl ester and hydrazinolysis to lysergic acid hydrazide, were examined for possible use in a routine analysis method. In addition to yield and reaction rate, factors such as handling of the reaction and the possibility of parallel sample workup play a role.
Investigation of degradation of the aluminum current collector in lithium-ion batteries by GD-OES
(2022)
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
In industrialised countries more than 80% of the time is spent indoors. Products, such as building materials and furniture, emit volatile organic compounds (VOCs), which are therefore ubiquitous in indoor air. VOC in combination may, under certain environmental and occupational conditions, result in reported sensory irritation and health complaints. Emission concentrations can become further elevated in new or refurbished buildings where the rate of air exchange with fresh ambient air may be limited due to improved energy saving aspects. A healthy indoor environment can be achieved by controlling the sources and by eliminating or limiting the release of harmful substances into the air. One way is to use (building) materials proved to be low emitting. Meanwhile, a worldwide network of professional commercial and non-commercial laboratories performing emission tests for the evaluation of products for interior use has been established. Therefore, comparability of test results must be ensured. A laboratory’s proficiency can be proven by internal and external validation measures that both include the application of suitable emission reference materials (ERM). For the emission test chamber procedure according to EN 16516, no artificial ERM is commercially available. The EU-funded EMPIR project MetrIAQ aims to fill this gap by developing new and improved ERMs. The goal is to obtain a material with a reproducible and temporally constant compound release (less than 10% variability over 14 days). Different approaches, such as the impregnation of porous materials, are being tested. The generation as well as results of the most promising materials will be presented.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Croatia. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in the United Kingdom. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
A recent upgrade of key equipment of the BAMline widens its imaging capabilities: shorter scan acquisition times are now possible, in situ and operando studies can now be routinely performed, and different energy spectra can easily be set up. In fact, the upgraded double-multilayer monochromator brings full flexibility by yielding different energy spectra to optimize flux and energy resolution as desired.
Deciphering microbiological influenced corrosion processes on steel with single cell-ICP-ToF-MS
(2022)
Microbiologically influenced corrosion (MIC) is a highly unpredictable process dictated by the environment, microorganisms, and the respective electron source. Interaction pathways between cells and the metal surface remain unclear. The development of this novel single cell-inductively coupled plasma-time of flight-mass spectrometry analytical method and a MIC-specific staining procedure facilitate the investigation of steel-MIC interactions. With this it is possible to analyze the multi-elemental fingerprint of individual cells. The detection method revealed elemental selectivity for the corrosive methanogenic archaeal strain Methanobacterium-affiliated IM1. The interface between material and environmental analysis thus receives special attention, e.g., when considering MIC on solid steel. Hence, the possible uptake of individual elements from different steel samples is investigated. Results showed the cells responded at a single-cell level to the different types of supplemented elements and displayed the abilities to interact with chromium, vanadium, titanium, cobalt, and molybdenum from solid metal surfaces. The information obtained will be used in the future to elucidate underlying mechanisms and develop possible material protection concepts, thus combining modern methods of analytical sciences with materials research.
References.
Geführte Ultraschallwellen sind für die Materialcharakterisierung hervorragend geeignet, da ihr Ausbreitungsverhalten abhängig von den Materialeigenschaften des untersuchten Werkstoffs ist.
Um aus dem messtechnisch ermittelten Ausbreitungsverhalten geführter Ultraschallwellen Rückschlüsse auf die Materialparameter zu ziehen, werden in der aktuellen Forschung verschiedene inverse Methoden diskutiert. Dispersionsabbildungen im Frequenz-Wellenzahl-Bereich repräsentieren das Ausbreitungsverhalten geführter Ultraschallwellen. Maschinelles Lernen und insbesondere Convolutional-Neural-Networks (CNNs) sind eine Möglichkeit der automatisierten inversen Bestimmung der Materialparameter aus den Dispersionsabbildungen.
In diesem Beitrag wird anhand synthetischer Daten gezeigt, wie das Ausbreitungsverhalten von geführten Ultraschallwellen unter Verwendung von CNNs und Dispersionsabbildungen genutzt werden kann, um die elastischen Konstanten einer isotropen plattenförmigen Struktur zu bestimmen. Anhand dieses Beispiels wird das generelle Vorgehen zur Anwendung maschineller neuronaler Lernverfahren aufgezeigt. Hierfür werden die verwendeten Daten analysiert, das Preprocessing erläutert und eine einfache CNN-Architektur gewählt. Im Rahmen der Auswertung wird insbesondere Wert auf die Erklärbarkeit und Zuverlässigkeit des verwendeten CNNs gelegt und so Grenzen und Möglichkeiten aufgezeigt.
In non-destructive testing and structural health monitoring with ultrasonic waves, the quantification of damage in components is one of the main tasks. In many shell-like structures, such as plates, pipes, or laminate components, ultrasonic waves propagate as guided waves. Although guided waves enable the testing of large areas, their multimodal and dispersive properties make it challenging to analyze signals. So, there is a need for more advanced algorithms to handle these properties, especially when reconstructing damage position and geometry.
The reconstruction can be formulated as an inverse problem where the measured signals are fitted with a simulative forward model. Due to the small wavelength of ultrasonic waves, classic forward models based on, e.g., the Finite Element Method are computationally intensive. In contrast, the authors use the semi-analytical Scaled Boundary Finite Element Method (SBFEM) to reduce the computational effort. The SBFEM approximates arbitrary long, undamaged parts of the structure with only a few degrees of freedom.
This contribution summarizes a general inverse procedure based on algorithmic differentiation in combination with the SBFEM. Results are presented for damaged 2D cross-sectional models of waveguides. These results include an analysis of the robustness of the proposed algorithms against noise.
This paper considers an indirect measurement approach to reconstruct a defect in a two-dimensional waveguide model for a non-destructive ultrasonic inspection via derivative-based optimization. The propagation of the mechanical waves is simulated by the scaled boundary finite element method that builds on a semi-analytical approach. The simulated data are then fitted to given data associated with the reflected waves from a defect which is to be reconstructed. For this purpose, we apply an iteratively regularized Gauss-Newton method in combination with algorithmic differentiation to provide the required derivative information accurately and efficiently. We present numerical results for three kinds of defects, namely, a crack, delamination, and corrosion. The objective function and the properties of the reconstruction method are investigated. The examples show that the parameterization of the defect can be reconstructed efficiently as well as robustly in the presence of noise.
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.
LIBS is a complementary method to XRF and can detect all elements without the need for vacuum conditions. Automated systems are already commercially available capable of scanning surfaces with a resolution of up to 0.1 mm within a few minutes. In addition to possible applications in R&D, LIBS is also used for practical applications in building materials laboratories and even on-site.
In view of ageing infrastructure facilities, a reliable assessment of the condition of concrete structures is of increasing interest. For concrete structures, the ingress of potential harmful ions is affecting the serviceability and eventually structural performance. Pitting corrosion induced by penetrating chlorides is the dominant deterioration mechanism. Condition assessment based on frequently performed chloride profiling can be useful to identify the extent and evolution of chloride ingress. This could prove to be more economical than extensive repairs, especially for important infrastructure facilities.
Currently the most common procedure for determining the chloride content is wet chemical analysis with standard resolution of 10 mm. The heterogeneity is not considered. LIBS is an economical alternative for determining the chloride content at depth intervals of 1 mm or less. It provides 2D distributions of multiple elements and can locate spots with higher concentrations. The results are directly correlated to the mass of binder and can also be performed on-site with a mobile LIBS-System.
The application of a LIBS-system is presented. Calibration is required for quantitative analysis. Concrete cores were drilled, sliced and analyzed to determine the 2D-distribution of harmful elements. By comparing the chloride ingress and the carbonation, the interaction of both processes can be visualized in a measurement that takes less than 10 minutes for a 50 mm x 100 mm drill core.
A leaflet on the use of LIBS for the chloride ingress assessment has been completed.
In many scientific fields, isotopic analysis can offer valuable information, e.g., for tracing the origin of food products, environmental contaminants, forensic and archaeological samples (provenance determination), for age determination of minerals (geochronological dating) or for elucidating chemical processes. Up to date, typically bulk analysis is aimed at measuring the isotopic composition of the entire elemental content of the sample. However, the analyte element is usually present under the form of different elemental species. Thus, separating species of interest from one another and from matrix components prior to isotope ratio measurements can provide species-specific isotopic information, which could be used for tracing the origin of environmental pollutants and elucidation of (environmental) speciation. Using on-line hyphenations of separation techniques with multicollector-ICP-MS (MC-ICP-MS) can save time and effort and enables the analysis of different species during a single measurement.
In this work, we developed an on-line hyphenation of CE with multicollector-ICP-MS (CE/MC-ICP-MS) for isotopic analysis of sulfur species. With this method, the isotopic composition of sulfur in sulfate originating from river water could be analyzed without sample preparation. The results were compared with data from off-line analysis of the same samples to ensure accuracy. The precision of the results of the on-line measurements was high enough to distinguish the rivers from one another by the isotopic signature of the river water sulfate. Next to environmental applications, a current field is species-specific isotopic analysis of biomolecules, as sulfur is the only covalently bound constituent of proteins which can be analyzed by MC-ICP-MS. Data analysis of transient signals in terms of isotope ratio determination is further issue - we developed a small free accessible App allowing for fast data analysis taking relevant aspects (e.g., mass bias correction, peak picking, …) into account.
The main application of LIBS in civil engineering is the detection of harmful ions in concrete, which can penetrate the component through the porous concrete structure. The advantages of LIBS over standard methods are the possibility of multi-element analysis, measurement speed, spatially resolved measurements, and minimal sample preparation. The spatially resolved measurements of LIBS allow the assessment of the heterogeneity of the concrete by measuring separately the chemical composition of the aggregates and the binder matrix. The latter is particularly relevant because the determined elemental distribution can be directly related to the binder matrix. This is not possible with standard methods, since the material is homogenized to powder during sample preparation stage and the determined concentration is thus related to the total mass. In addition to the use of LIBS for the specific analysis of individual harmful ions, LIBS can also be used to estimate the concrete composition and thus determine, for example, the type of cement used. Corresponding information are relevant for the estimation of the remaining service life and for the preparation of a maintenance concept. In recent years, LIBS has been increasingly used in civil engineering. Currently, however, it is primarily used in research institutions and only occasionally in building materials laboratories. Special commercial devices have also been developed, which greatly simplify the application due to the high degree of automation. Mobile LIBS systems allow on-site application. A central point, which limits the use of LIBS in the commercial sector, is the lack of norms and standards. Therefore, within the framework of a project funded by the German government, work has been carried out on the preparation of a leaflet on quantitative chlorine determination in concrete, which will be published this year. In interlaboratory comparisons the robustness and accuracy for the practical application was demonstrated. LIBS also has great potential in the recycling of construction waste in conjunction with hyperspectral sensors. This issue is currently being addressed in a national project. During the presentation, the state of the art of LIBS in civil engineering will be presented, next steps will be discussed, and future challenges will be outlined.
The metrological analysis uses an unbroken chain of comparative measurements to trace results back to the national or international standard. This enables comparable, absolute quantification between laboratories. In 2020/2021, a pilot study for the quantification of SARS-CoV-2 antibodies was initiated with the involvement of BAM. Despite the consistent use of ID-MS, a large discrepancy in the results of the participating laboratories was found. This was the motivation for a project to systematically investigate and optimize traceable methods of protein quantification using mass spectrometric nontarget analysis (NTA) and recombinant antibody panels.
The composition of acoustically levitated droplets was probed by a novel combination of mid-IR laser evaporation and subsequent postionization via secondary electrospray ionization. The combination of microliter samples and subnanoliter sampling provided time-resolved interrogation of droplets and allowed for a kinetic investigation of the laser-induced release of the analyte, which was found to strongly depend on the analytes. The observed substancespecific delayed release of the analytes permitted baseline-separated discrimination of the analytes, ideal for the study of complex samples.
The additionally applied postionization scheme was found to enable efficient detection of small volatile compounds as well as peptides. The detection of small molecules and peptides occurred under very different sampling geometries, pointing to two distinct underlying ionization mechanisms. Overall, our results suggest that the experimental setup presented in this study can serve as a widely applicable platform to study chemical reactions in acoustically levitated droplets as model reactors.
Living organisms constantly interact with their environment, including through the exchange of gases. Respiration and the release and uptake of volatile organic compounds (VOCs) create dynamic microenvironments in biological systems. Studying the kinetics of volatiles in biological systems requires expensive instruments, and data analysis is challenging. Therefore, we aimed to design a minimal analytical device for measuring the composition of gaseous mixtures in realtime.
We built the ‘Modular Biological Mass Spectrometer’ (MoBiMS) from 3D-printed parts and custom sensors to fit a wide array of experimental set-ups. We tested the chemical detection range and temporal resolution of the MoBiMS employing pure compounds and complex biological samples.
Compounds with a higher than 0.4 mmHg vapor pressure and a molecular weight up to 154 g/mol were reliably sensed within seconds. The generated electron impact (EI) spectra were directly comparable with standard databases like the NIST EI library. Under a direct analysis approach, the MoBiMS identified the characteristic odor of banana (Musa sp.), that is, isoamyl acetate; tracked the dynamics of CO2 release while the Alka-Seltzer® reaction occurred showed the kinetics of the transient production and consumption of carbon dioxide during photosynthesis. MoBiMS also discriminated between volatile compounds ions coming from tobacco (Nicotiana benthamiana) leaves and the surrounding air through untargeted analysis. The small footprint of the MoBiMS and its relatively low energy consumption facilitate in situ analyses, as an additional gas supply is not necessary with EI ionization. The MoBiMS is easy to assemble, and its construction and operation are very cost-efficient compared to commercial devices. The analytical performance of the MoBiMS is suitable for real-time studies of biological systems, environmental monitoring, and medical diagnostics.
Unintended Rate Enhancement in Mechanochemical Kinetics by Using Poly(methyl methacrylate) Jars
(2022)
Time-resolved in situ (TRIS) X-ray diffraction has changed how mechanochemical transformations are studied but requires the use of X-ray transparent jars often made from poly(methyl methacrylate) (PMMA). However, using PMMA jars can alter the apparent kinetics of mechanochemical polymorphism by an order of magnitude, questioning the interpretability of established TRIS methods. Our results suggest that rate enhancement in PMMA jars may not be dominated by chemical effects of the polymer, but rather a result of different equilibrium temperatures within the jar. These features must be better understood before control over mechanochemical reactions can be achieved.
Small-angle scattering is an increasingly common method for characterizing particle ensembles in a wide variety of sample types and for diverse areas of application. SASfit has been one of the most comprehensive and flexible curve-fitting programs for decades, with many specialized tools for various fields. Here, a selection of enhancements and additions to the SASfit program are presented that may be of great benefit to interested and advanced users alike: (a) further development of the technical basis of the program, such as new numerical algorithms currently in use, a continuous integration practice for automated building and packaging of the software, and upgrades on the plug-in system for easier adoption by third-party developers; (b) a selection of new form factors for anisotropic scattering patterns and updates to existing form factors to account for multiple scattering effects; (c) a new type of a very flexible distribution called metalog [Keelin (2016). Decis. Anal. 13, 243–277], and regularization techniques such as the expectation-maximization method [Dempster et al. (1977). J. R. Stat. Soc. Ser. B (Methodological), 39, 1–22; Richardson (1972) J. Opt. Soc. Am. 62, 55; Lucy (1974). Astron. J. 79, 745; Lucy (1994). Astron. Astrophys. 289, 983–994], which is compared with fits of analytical size distributions via the non-linear least-squares method; and (d) new structure factors, especially for ordered nano- and meso-scaled material systems, as well as the Ornstein–Zernike solver for numerical determination of particle interactions and the resulting structure factor when no analytical solution is available, with the aim of incorporating its effects into the small-angle scattering intensity model used for fitting with SASfit.
Der Bunsen-Kirchhoff-Preis 2022 wurde am 23.06.2022 anlässlich der analytica conference in München an Dr. Carlos Abad verliehen - in Anerkennung seiner exzellenten Entwicklungen im Bereich der continuum source atomic absorption spectrometry (CS-AAS).
Dr. Carlos Abad ist ein herausragender Experte auf dem Gebiet der Atom- und molekularen Absorptionsspektrometrie. insbesondere trug er maßgeblich zur substanziellen Weiterentwicklung von Echelle-Spektrometern für die CS-AAS bei. So gelang es, einen quantitativen Zugang zu Elementen wie Bor, Chlor, Fluor und Schwefel, mittels AAS zu erreichen. Erstmals demonstriert Dr. Carlos Abad am Beispiel eines Zr-Modifier, dass durch die Zeitauflösung der eingesetzten Echelle-Systeme mechanistische Untersuchungen zur Wirkung des Modifiers im Graphitrohrofen möglich sind.
Besonders hervorzuheben sind seine Arbeiten zum Einsatz der CS-AAS für die Analyse von Isotopen, die eine Genauigkeit aufweist, welche an die der Multikollektor-induktiv gekoppelten Plasma-Massenspektrometrie (MC-ICP-MS) heranreicht. Damit ergeben sich völlig neue Einsatzmöglichkeiten für technologisch hochrelevante Applikationen, wie z.B. die Untersuchung der Alterung von Lithium-Batterien oder die Lithium-Analyse in Blutserum.
Calcium isotope analysis can be an important tool for paleoclimate studies of the carbon cycle, as well in carbon capture technology, but its utility is limited by challenges using conventional mass spectrometry. We propose a new fast, precise, and high-throughput technology based on multiple complementary high-resolution spectroscopies analyzed by machine-learning.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.
Glow discharge optical emission spectroscopy (GD-OES) is a technique for the analysis of solids such as metals, semiconductors, and ceramics. A low-pressure glow discharge plasma is applied in this system, which ‘sputters’ and promotes the sample atoms to a higher energy state. When the atoms return to their ground state, they emit light with characteristic wavelengths, which a spectrometer can detect. Thus, GD-OES combines the advantages of ICP-OES with solid sampling techniques, which enables it to determine the bulk elemental composition and depth profiles. However, direct solid sampling methods such as glow-discharge spectroscopy require reference materials for calibration due to the strong matrix effect.
Reference materials are essential when the accuracy and reliability of measurement results need to be guaranteed to generate confidence in the analysis. These materials are frequently used to determine measurement uncertainty, validate methods, suitability testing, and quality assurance. In addition, they guarantee that measurement results can be compared to recognized reference values. Unfortunately, the availability of certified reference materials suited to calibrate all elements in different matrix materials is limited. Therefore various calibration strategies and the preparation of traceable matrix-matched calibration standards will be discussed.
Machine learning is an essential component of the growing field of data science. Through statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. Therefore, it was tried in our work to combine GD-OES with machine learning strategies to establish a new and robust calibration model, which can be used to identify the elemental composition and concentration of metals from a single spectrum. For this purpose, copper reference materials from different manufacturers, which contain various impurity elements, were investigated using GD-OES. The obtained spectra information are evaluated with different algorithms (e.g., gradient boosting and artificial neural networks), and the results are compared and discussed in detail.
Isotope analysis is a tool for material research. For example, it may provide information about the provenance of a sample or changes in dynamic systems. Here is presented optical spectroscopy as an analytical alternative to mass spectrometry for isotope quantification based on the isotopic shift of atoms and diatomic molecules.
Mechanochemistry offers a unique opportunity to modify or synthesize new crystal forms. Although the method is very promising, little is known about the mechanochemical means to control the synthesis of a solid form. Using an polymorphic organic cocrystal system, we show here that mechanochemistry can be used to obtain a polymorph transformation under the apparently conventional (thermal) transition point.
Mechanochemistry offers a unique opportunity to modify and manipulate crystal forms, often providing new products as compared with conventional solution methods. While promising, there is little known about how to control the solid form through mechanochemical means, demanding dedicated investigations. Using a model organic cocrystal system (isonicotinamide:glutaric acid), we here demonstrate that with mechanochemistry, polymorphism can be induced in molecular solids under conditions seemingly different to their conventional thermodynamic (thermal) transition point. Whereas Form II converts to Form I upon heating to 363 K, the same transition can be initiated under ball milling conditions at markedly lower temperatures (348 K). Our results indicate that mechanochemical techniques can help to reduce the energy barriers to solid form transitions, offering new insights into controlling polymorphic forms. Moreover, our results suggest that the nature of mechanochemical transformations could make it difficult to interpret mechanochemical solid form landscapes using conventional equilibrium-based tools.
In X-ray computed tomography (XCT), an X-ray beam of intensity I0 is transmitted through an object and its attenuated intensity I is measured when it exits the object. The attenuation of the beam depends on the attenuation coefficients along its path. The attenuation coefficients provide information about the structure and composition of the object and can be determined through mathematical operations that are referred to as reconstruction. The standard reconstruction algorithms are based on the filtered backprojection (FBP) of the measured data. While these algorithms are fast and relatively simple, they do not always succeed in computing a precise reconstruction, especially from under-sampled data. Alternatively, an image or volume can be reconstructed by solving a system of linear equations. Typically, the system of equations is too large to be solved but its solution can be approximated by iterative methods, such as the Simultaneous Iterative Reconstruction Technique (SIRT) and the Conjugate Gradient Least Squares (CGLS). This dissertation focuses on the development of a novel iterative algorithm, the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT). After its reconstruction principle is explained, its performance is assessed for real parallel- and cone-beam CT (including under-sampled) data and compared to that of other established algorithms. Finally, it is demonstrated how the shape of the measured object can be modelled into DIRECTT to achieve even better reconstruction results.
Gold films coated with a graphene sheet are being widely used as sensors for the detection of label-free binding interactions using surface plasmon resonance (SPR). During the preparation of such sensors, it is often essential to subject the sensor chips to a high-temperature treatment in order to ensure a clean graphene surface. However, sensor chips used currently, which often use chromium as an adhesion promoter, cannot be subjected to temperatures above 250 °C, because under such conditions, chromium is found to reorganize and diffuse to the surface, where it is easily oxidized, impairing the quality of SPR spectra. Here we present an optimized preparation strategy involving a three-cycle tempering coupled with chromium (oxide) etching, which allows the graphene-coated SPR chips to be annealed up to 500 °C with little deterioration of the surface morphology. In addition, the treatment delivers a surface that shows a clear enhancement in spectral response together with a good refractive index sensitivity. We demonstrate the applicability of our sensors by studying the kinetics of avidin–biotin binding at different pH repeatedly on the same chip. The possibility to anneal can be exploited to recover the original surface after sensing trials, which allowed us to reuse the sensor for at least six cycles of biomolecule adsorption.
Vertebrate bones are made of a nanocomposite consisting of water, mineral and organics. Water helps bone material withstand mechanical stress and participates in sensation of external loads. Water diffusion across vertebrae of medaka (bone material lacking osteocytes) and zebrafish (bone material containing osteocytes) was compared using neutron tomography. Samples were measured both wet and following immersion in deuterated-water (D2O). By quantifying H+ exchange and mutual alignment with X-ray lCT scans, the amount of water expelled from complete vertebra was determined. The findings revealed that anosteocytic bone material is almost twice as amenable to D2O diffusion and H2O exchange, and that unexpectedly, far more water is retained in osteocytic zebrafish bone. Diffusion in osteocytic bones (only 33 % – 39 % water expelled) is therefore restricted as compared to anosteocytic bone (~ 60 % of water expelled), presumably because water flow is confined to the lacunar-canalicular network (LCN) open-pore system. Histology and Raman spectroscopy showed that anosteocytic bone contains less proteoglycans than osteocytic bone. These findings identify a previously unknown functional difference between the two bone materials. Therefore, this study proposes that osteocytic bone retains water, aided by non-collagenous proteins, which contribute to its poroelastic mechano-transduction of water flow confined inside the LCN porosity.
Quantitative 1H Nuclear Magnetic Resonance (qNMR) of Aromatic Amino Acids for Protein Quantification
(2022)
qNMR is a valuable technique for metrological studies due to the uniformity of its signal response for all chemical species of an isotope of interest, which enables compound-independent calibration. However, protein quantification remained challenging as large molecules produce wide, low-intensity signals that reduce the already low sensitivity. Combining qNMR with the hydrolysis of protein samples into amino acids circumvents many of these issues and facilitates the use of NMR spectroscopy for absolute protein and peptide quantification.In this work, different conditions have been tested for quantifying aromatic amino acids and proteins. First, we examined the pH-based signal shifts in the aromatic region. The preferable pH depends on the selection of the amino acids for quantification and which internal standard substance should be used to avoid peak overlap. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, have been applied as internal standards. The quantification of amino acids from an amino acid standard, as well as from a certified reference material (bovine serum albumin), was performed. Using the first two suggested internal standards, recovery was ~ 97 % for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98 ± 2 and 88 ± 4 %, respectively, at a protein concentration of 16 g/L or 250 µM.
Hydration is the exothermic reaction between anhydrous cement and water, which forms the solid cement matrix of concrete. Being able to evaluate the hydration is of high interest for the use of both conventional and more climate-friendly building materials. The experimental monitoring is based on temperature or moisture measurements. The first needs adiabatic conditions, which can only be achieved in laboratory. The latter is often measured comparing the weight of the material sample before and after oven drying, which is time-consuming. This study investigates the moisture content of two cement-based and two calcium sulphate based mixtures for the first 90 days by using the calcium carbide method and oven drying at 40 °C and 105 °C (Darr method). Thereby, the amount of chemically bound water is determined to derive the degree of hydration. The calcium carbide measurements highly coincide with oven drying at 40 °C. The calcium carbide method is therefore evaluated as a suitable alternative to the time-consuming Darr drying. The prompt results are seen as a remarkable advantage and can be obtained easily in laboratory as well as in the field.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
New Reference Materials for Quantification and Standardization of Fluorescence-based Measurements
(2022)
Luminescence techniques are amongst the most commonly used analytical methods in the life and material sciences due to their high sensitivity and non-destructive and multiparametric character. Photoluminescence signals are, however, affected by wavelength-, polarization-, and time-dependent instrument specific effects and the compound-specific photoluminescence quantum yield. The former hamper the comparability of fluorescence measurements, while the relative determination of the latter requires suitable quantum yield standards with well-known photoluminescence quantum yields. For the simple correction of instrument specific effects in the wavelength region of 300 nm to 950 nm, the set of the five certified spectral fluorescence standards (CRM) BAM-F001 – BAM-F005, has been extended to the NIR range by including two new fluorescence standards currently under certification.
XPS of GR2M
(2022)
High-resolution absorption isotopic spectrometry as a tool for aging studies of Li-ion batteries
(2022)
Lithium (Li) is the key element in the manufacturing of batteries. Isotopic study of Li may help to identify the causes of battery aging due to isotopic fractionation during charge/discharge cycles.
Isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←22S electronic transition around 670.788 nm. In this work, we propose improvements to our previous work [1] by using a higher-resolution double echelle modular spectrometer (HR-DEMON II) coupled to a continuum source graphite furnace atomic absorption spectrometer (HR-CS-GF-AAS) for the isotopic analysis of Li.
The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm (XGBoost). A set of samples with 6Li isotope amount fractions ranging from 0.0004 to 0.99 mol mol-1 was used for the algorithm's training. Subsequently, the procedure was validated by a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material, a cathode material (NMC111). Finally, the ML model was applied to determine the isotope ratio of geological samples, including anorthosite, granite, soil, rhyolite, nepheline syenite, and basalt and battery samples. These samples were measured as digested without any further purification step.
Improvements in the optical resolution resolve the lithium isotopic components of the atomic spectra. In the studied geological samples, were found δ7Li values between -0.5 and 4.5 ‰ with a precision range of 1 to 2 ‰. In addition, the proposed method was validated with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), and these results are comparable and compatible.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in New Zealand. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
In this study, the concept of a zero mass flow liner is evaluated. The concept enables impedance control by theinduction of, acoustically actuated, periodic bias flowthrough the facing sheet of the liner. Bymeans of the periodic bias flow, the impedance of the liner is adapted to different grazing flowconditions.The equivalent fluid impedancemodel for perforated plates is modified to account for the effects of periodic bias and grazing flow. A generally applicable optimization routine, using the impedance of the lined surface as a boundary condition in a numeric calculation, is implemented. Based on the results of the optimization, a zero mass flow liner is manufactured and evaluated experimentally. The damping characteristics are assessed in the form of dissipated energy along the lined surface.
Prediction and measurements show reasonable agreement. The zero mass flow liner delivers broadband dissipation of high peak value over a range of grazing flow Mach numbers. Under grazing flow, the effect of periodic bias flow is reduced. For a ratio of grazing to bias flow velocities larger than five, no appreciable effect is found. This poses considerable energy requirements on the actuation source for the application in high-Mach-number flow regimes.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in West Africa. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Mexico. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Peru. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
Per- and polyfluorinated alkyl substances (PFASs) are a group of several thousand individual compounds. Many 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.
PFAS sum parameters display the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. High resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) 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.
In the present work a HR-CS-GFMAS method for EOF analysis was utilized for suspended particulate matter (SPM) analysis in German rivers in time lines from 2005–2020. Therefore, time and spatial resolved trends were investigated. In addition, SPM samples were analyzed for the Σ41PFAS using target analysis based on UHPLC-HRMS. Overall, target analysis drastically underestimated the total PFAS burden in SPM of German rivers compared to the EOF HR-CS-GFMAS analysis. Using a fluorine mass balance approach, only 0.2% to 38.6% of the EOF was explainable using the Σ41PFAS determined with target analysis. Our study highlights the need to integrate PFAS sum parameters (e.g., EOF with HR-CS-GFMAS) in PFAS risk assessment strategies.
This presentation summarizes major findings from an international study in 16 countries and regions on digital transformation in conformity assessment bodies such as testing and calibration laboratories or certification and inspection bodies. It draws from survey data of 1.476 participants and specifically highlights findings on the digital maturity of the organizations, providing an international comparison.
The isotopic analysis of lithium is also relevant to the study of geological phenomena.1 In this work we propose improvements to the method for the isotopic analysis of lithium using a high-resolution continuum source atomic absorption spectrometer (HR-CS-AAS) coupled to a double echelle modular spectrometer (DEMON). 2 This tool for isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←2 2S electronic transition around 670.788 nm. The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm. For the training of the algorithm (XGBoost), a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol-1 was used. Subsequently, the procedure was validated of a set of stock chemicals (Li2CO3, LiNO3, LiCl and LiOH) and a BAM candidate reference material, the cathode material LiNi1/3Mn1/3Co1/3O2 (NMC111). Finally, the ML model was applied to the set of geological samples, previously digested, for the determination of their isotope ratio. The optical resolution was improved from 140,000 to 790,000 to better deconvolution the lithium isotopic components in the atomic spectrum. And the method was compared with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). The results are metrologically comparable.
Estrogens are endocrine disrupting chemicals and of high concerns due to demonstrated harmful effects on the environment and low effect levels. For monitoring and risk assessment, several estrogens were included in the "watch list" of the EU Water Framework Directive which sets very low environmental quality standard (EQS) levels for Estrone (E1) and 17β-Estradiol (E2) of 0.4 ng L−1 and for 17α-Ethinylestradiol (EE2) of 0.035 ng L−1 requiring sensitive detection methods, as well as extensive sample preparation. A sensitive, derivatization-free, isotope dilution calibration HPLC-MS/MS method for a panel of 5 selected estrogens (including the 3 estrogens of the EU WFD watchlist), and a procedure for the reproducible preparation of a representative whole water matrix including mineral water, humic acids and solid particulate matter are presented. These are used in a diligent comparison of classical solid phase extraction (SPE) on hydrophilic-lipophilic balanced (HLB) phase to SPE on an estrogen-specific molecularly imprinted polymer phase (MISPE) for ultra-trace levels of the analytes (1–10 ng L−1). Additionally, a two-step procedure combining HLB SPE disks followed by MISPE is evaluated. The tow-step procedure provides superior enrichment, matrix removal and sample throughput while maintaining comparable recovery rates to simple cartridge SPE. Estimated method quantification limits (MQLs) range from 0.109–0.184 ng L−1 and thus meet EQS-levels for E1 and E2, but not EE2. The representative whole water matrix provides a reproducible comparison of sample preparation methods and lays the foundation for a certified reference material for estrogen analysis. The presented method will serve as the basis for an extended validation study to assess its use for estrogen monitoring in the environment.
X-ray fluorescence imaging is a well-established tool in materials characterization. In this work, we present the adaption of coded aperture imaging to full-field X-ray fluorescence imaging at the synchrotron. Coded aperture imaging has its origins in astrophysics, and has several advantages: Coded apertures are relatively easy to fabricate, achromatic, allow a high photon throughput, and high angular acceptance. Coded aperture imaging is a two-step-process, consisting of the measurement process and a reconstruction step. Different programs have been written, for the raytracing/forward projection and the reconstruction. Experiments with coded aperture in combination with a Color X-ray Camera and an energy-dispersive area detector, have been conducted at the BAMline. Measured samples were successfully reconstructed, and gave a 9.1-fold increase in count rate compared to a polycapillary optic.
A tool for merging and/or rebinning single or multiple datasets to achieve a lower point density with best possible statistics. highly scriptable, CLI, no GUI
Version 0.1: works but could do with a cleanup. Weighting by uncertainty currently always on, but should be optional for use as an azimuthal or radial averager
IsoCor
(2022)
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.
The formation of irregularities such as keyhole porosity pose a major challenge to the manufacturing of metal parts by laser powder bed fusion (PBF-LB/M). In-situ thermography as a process monitoring technique shows promising potential in this manner since it is able to extract the thermal history of the part which is closely related to the formation of irregularities. In this study, we investigate the utilization of machine learning algorithms to detect keyhole porosity on the base of thermographic features. Here, as a referential technique, x-ray micro computed tomography is utilized to determine the part's porosity. An enhanced preprocessing workflow inspired by the physics of the keyhole irregularity formation is presented in combination with a customized model architecture. Furthermore, experiments were performed to clarify the role of important parameters of the preprocessing workflow for the task of defect detection . Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
The appearance of irregularities such as keyhole porosity is a major challenge for the production of metal parts by laser powder bed fusion (PBF-LB/M). The utilization of thermographic in-situ monitoring is a promising approach to extract the thermal history which is closely related to the formation of irregularities. In this study, we investigate the utilization of convolutional neural networks to predict keyhole porosity based on thermographic features. Here, the porosity information calculated from an x-ray micro computed tomography scan is used as reference. Feature engineering is performed to enable the model to learn the complex physical characteristics of the porosity formation. The model is examined with regard to the choice of hyperparameters, the significance of thermal features and characteristics of the data acquisition. Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
Attenuation of ultrasonic signals in concrete has the potential to carry much information about the microstructure of the material. In this work a series of concrete specimens of varying porosities and pore size distributions were internally imaged with x-ray computed tomography (CT), and then subsequently examined with throughtransmission ultrasound. The CT images were used to quantify both capillary porosity of cement paste as well as internal interfaces that are likely to produce elastic wave scattering. Ultrasound signals were represented as a diffusion process such that absorption and scattering attenuation could be isolated. As implemented, the diffusion model was a poor predictor of capillary porosity, while diffusivity was a reasonable predictor of scattering interfaces. Diffusivity was found to scale extremely well with small scale porosity, which made it a good predictor of compressive strength.
The retroreflective corner echo is used, for example, in ultrasonic non-destructive testing of metals to find fatigue cracks in tubes or shafts. If the much weaker crack tip signal is additionally detected, the crack length can also be determined. A corner reflection occurs in cases of surface breaking cracks with predominantly perpendicular orientation to the surface. The intensity of the corner reflection depends on the angle of incidence and on the ultrasonic wave mode used. For the reliable detection of vertical surface breaking cracks in metals, transversal waves are commonly used, which propagate at an angle of 37° to 53° to the inspection surface. As shown in this contribution, the wide spread low frequency ultrasonic arrays with dry point contact sources available for ultrasonic testing of concrete also allow to receive corner echoes. These devices generate transversal waves in concrete structures with a large divergence of the sound field. A series of experiments was carried out with such dry point contact arrays on concrete specimens with artificial test defects and controlled induced cracks of different depths. The ultrasonic time-of-flight signals were recorded, exported and reconstructed utilising the SAFT (Synthetic Aperture Focusing Technique) algorithm. The SAFT reconstruction parameters were adjusted to visualize the corner echo indication. As will be shown, with this targeted processing, the reproducible detection of surface breaking cracks in concrete is possible. The retroreflective corner echo can thus be exploited in civil engineering for non-destructive inspection of concrete.
Muon tomography applied to assessment of concrete structures: First experiments and simulations.
(2022)
Non-destructive techniques for reinforced or prestressed concrete inspection such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened new fields of application. As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. In a second step, we have performed simulations to assess the potential for a set of important testing problems such as grouting defects in tendon ducts. The next steps include the development of mobile detectors and optimizing acquisition and imaging parameters.
This contribution summarizes actual developments and draft fundamental teaching topics in the field of nondestructive testing in civil engineering (NDT-CE). It is based on the first memorandum on teaching and research in the field of NDT-CE at German speaking universities and provides an overview of the academic education and highlights possible focuses, especially in teaching but also takes into account noteworthy developments and topics in research in the field of NDT-CE.
Suggestions are given for the development and advancement of the teaching curricula in regards to a comprehensive and sound professional education of students in civil engineering and adjacent disciplines.