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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.
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.
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.
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.