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Isotope ratio applications are on the increase and a major part of which are delta measurements, because they are easier to perform than the determination of absolute isotope ratios while offering lower measurement uncertainties. Delta measurements use artefact-based scales and therefore scale conversions are required due to the lack of the scale defining standards. Such scale conversions often form the basis for comparing data being generated in numerous projects andtherefore need to be as accurate as possible. In practice, users are tempted to apply linear approximations, which are not sufficiently exact, because delta values are defined by nonlinear relationships. The bias of such approximations often is beyond typical measurement uncertainties and its extent can hardly be predicted. Therefore, exact calculations are advised. Here, the exact equations and the bias of the approximations are presented, and calculations are illustrated by real-world examples. Measurement uncertainty is indispensable in this context and therefore, its calculation is described as well for determining delta values but also for scale conversions. Approaches for obtaining a single delta measurement and for repeated measurements are presented. For the latter case, a new approach for calculating the measurement uncertainty is presented, which considers covariances between the isotope ratios.
DNA long-term stability and integrity is of importance for applications in DNA based bio-dosimetry, data-storage, pharmaceutical quality-control, donor insemination and DNA based functional nanomaterials. Standard protocols for these applications involve repeated freeze-thaw cycles of the DNA, which can cause detrimental damage to the nucleobases, as well as the sugar-phosphate backbone and therefore the whole molecule. Throughout the literature three hypotheses can be found about the underlying mechanisms occurring during freeze-thaw cycles. It is hypothesized that DNA single-strand breaks during freezing can be induced by mechanical stress leading to shearing of the DNA molecule, by acidic pH causing damage through depurination and beta elimination or by the presence of metal ions catalyzing oxidative damage via reactive oxygen species (ROS). Here we test these hypotheses under well defined conditions with plasmid DNA pUC19 in high-purity buffer (1xPBS) at physiological salt and pH 7.4 conditions, under pH 6 and in the presence of metal ions in combination with the radical scavengers DMSO and Ectoine. The results show for the 2686 bp long plasmid DNA, that neither mechanical stress, nor pH 6 lead to degradation during repeated freeze-thaw cycles. In contrast, the presence of metal ions (Fe2+) leads to degradation of DNA via the production of radical species.
Measurement and calculation of x-ray production efficiencies for copper, zirconium, and tungsten
(2022)
Electron probe microanalysis (EPMA) is based on physical relations between measured X-ray intensities of characteristic lines and their Xray production efficiency, which depends on the specimen composition. The quality of the analysis results relies on how realistically the physical relations describe the generation and emission of X-rays. Special experiments are necessary to measure X-ray production efficiencies. A challenge in these experiments is the determination of the detection efficiency of the spectrometer as a function of the photon energy. An energy-dispersive spectrometer was used in this work, for which the efficiency was determined at metrological synchrotron beamlines with an accuracy of ±2%. X-ray production efficiencies for the L series and the Kα series of copper and zirconium and for the M and L series of tungsten were determined at energies up to 30 keV in a scanning electron microscope. These experimental values were compared with calculated X-ray production efficiencies using physical relations and material constants applied in EPMA. The objective of the comparison is the further improvement of EPMA algorithms as well as extending the available database for X-ray production efficiencies. Experimental data for the X-ray production efficiency are also useful for the assessment of spectrum simulation software.
The BAMline at the BESSY II synchrotron X-ray source has enabled research for more than 20 years in widely spread research fields such as materials science, biology, cultural heritage and medicine. As a nondestructive characterization method, synchrotron X-ray imaging, especially tomography, plays a particularly important role in structural characterization. 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. The upgraded detector (based on an sCMOS camera) also allows exploiting the higher flux with reduced readout times. Furthermore, an installed slip ring allows the sample stage to continuously rotate. The latter feature enables tomographic observation of processes occurring in the time scale of a few seconds.
A systematic study has been carried out to investigate the neutron transmission signal as a function of sample temperature. In particular, the experimentally determined wavelength-dependent neutron attenuation spectra for a martensitic steel at temperatures ranging from 21 to 700°C are compared with simulated data. A theoretical description that includes the Debye–Waller factor in order to describe the temperature influence on the neutron cross sections was implemented in the nxsPlotter software and used for the simulations. The analysis of the attenuation coefficients at varying temperatures shows that the missing contributions due to elastic and inelastic scattering can be clearly distinguished: while the elastically scattered intensities decrease with higher temperatures, the inelastically scattered intensities increase, and the two can be separated from each other by analysing unique sharp features in the form of Bragg edges. This study presents the first systematic approach to quantify this effect and can serve as a basis , for example, to correct measurements taken during in situ heat treatments, in many cases being a prerequisite for obtaining quantifiable results.
During their life span, concrete structures interact with many kinds of external mechanical loads. Most of these loads are considered in advance and result in reversible deformations. Nevertheless, some of the loads cause irreversible, sometimes unnoticed changes below the macroscopic scale depending on the type and dimension of the impact. As the functionality of concrete structures is often relevant to safety and society, their condition must be known and, therefore, assessed on a regular basis. Out of the spectrum of non-destructive monitoring methods, Coda Wave Interferometry using embedded ultrasonic sensors is one particularly sensitive technique to evaluate changes to heterogeneous media. However, there are various influences on Coda waves in concrete, and the interpretation of their superimposed effect is ambiguous. In this study, we quantify the relations of uniaxial compression and uniaxial tension on Coda waves propagating in normal concrete. We found that both the signal correlation of ultrasonic signals as well as their velocity variation directly reflect the stress change in concrete structures in a laboratory environment. For the linear elastic range up to 30% of the strength, we calculated a velocity variation of −0.97‰/MPa for compression and 0.33%/MPa for tension using linear regression. In addition, these parameters revealed even weak irreversible changes after removal of the load. Furthermore, we show the time-dependent effects of shrinkage and creep on Coda waves by providing the development of the signal parameters over time during half a year together with creep recovery. Our observations showed that time-dependent material changes must be taken into account for any comparison of ultrasonic signals that are far apart in time. The study’s results demonstrate how Coda Wave Interferometry is capable of monitoring stress changes and detecting even small-size microstructural changes. By indicating the stated relations and their separation from further impacts, e.g., temperature and moisture, we anticipate our study to contribute to the qualification of Coda Wave Interferometry for its application as an early-warning system for concrete structures.
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.
Current trends in materials and life sciences are flanked by the need to push detection limits to single molecules or single cells, enable the characterization of increasingly complex matrices or sophisticated nanostructures, speed up the time of analysis, reduce instrument complexity and costs, and improve the reliability of data. This requires suitable analytical tools such as spectroscopic, separation and imaging techniques, mass spectrometry, and hyphenated techniques as well as sensors and their adaptation to application-specific challenges in the environmental, food, consumer product, health sector, nanotechnology, and bioanalysis. Increasing concerns about health threatening known or emerging pollutants in drinking water, consumer products, and food and about the safety of nanomaterials led to a new awareness of the importance of analytical sciences. Another important driver in this direction is the increasing demand by legislation, particularly in view of the 17 sustainable development goals by the United Nations addressing clean energy, industry, and innovation, sustainable cities, clean water, and responsible consumption and production. In this respect, also the development of analytical methods that enable the characterization of material flows in production processes and support recycling concepts of precious raw materials becomes more and more relevant. In the future, this will provide the basis for greener production in the chemical industry utilizing recycled or sustainable starting materials.
This makes analytical chemistry an essential player in terms of the circular economy helping to increase the sustainability of production processes. In the life sciences sector, products based on proteins, such as therapeutic and diagnostic antibodies, increase in importance. These increasingly biotechnologically produced functional biomolecules pose a high level of complexity of matrix and structural features that can be met only by highly advanced methods for separation, characterization, and detection. In addition, metrological traceability and target definition are still significant challenges for the future, particularly in the life sciences.
However, innovative reference materials as required for the health and food sector and the characterization of advanced materials can only be developed when suitable analytical protocols are available. The so-called reproducibility crisis in sciences underlines the importance of improved measures of quality control for all kinds of measurements and material characterization. This calls for thorough method validation concepts, suitable reference materials, and regular interlaboratory comparisons of measurements as well as better training of scientists in analytical sciences.
The important contribution of analytical sciences to these developments is highlighted by a broad collection of research papers, trend articles, and critical reviews from these different application fields. Special emphasis is dedicated to often-overlooked quality assurance and reference materials.
The acquisition and appropriate processing of relevant information about the considered system remains a major challenge in assessment of existing structures. Both the values and the validity of computed results such as failure probabilities essentially depend on the quantity and quality of the incorporated knowledge. One source of information are onsite measurements of structural or material characteristics to be modeled as basic variables in reliability assessment. The explicit use of (quantitative) measurement results in assessment requires the quantification of the quality of the measured information, i.e., the uncertainty associated with the information acquisition and processing. This uncertainty can be referred to as measurement uncertainty. Another crucial aspect is to ensure the comparability of the measurement results.This contribution attempts to outline the necessity and the advantages of measurement uncertainty calculations in modeling of measurement data-based random variables to be included in reliability assessment. It is shown, how measured data representing time-invariant characteristics, in this case non-destructively measured inner geometrical dimensions, can be transferred into measurement results that are both comparable and quality-evaluated. The calculations are based on the rules provided in the guide to the expression of uncertainty in measurement (GUM). The GUM-framework is internationally accepted in metrology and can serve as starting point for the appropriate processing of measured data to be used in assessment. In conclusion, the effects of incorporating the non-destructively measured data into reliability analysis are presented using a prestressed concrete bridge as case-study.
Designing the shape and size of catalyst particles, and their interfacial charge, at the nanometer scale can radically change their performance. We demonstrate this with ceria nanoparticles. In aqueous media, nanoceria is a functional mimic of haloperoxidases, a group of enzymes that oxidize organic substrates, or of peroxidases that can degrade reactive oxygen species (ROS) such as H2O2 by oxidizing an organic substrate. We show that the chemical activity of CeO2−x nanoparticles in haloperoxidase- and peroxidaselike reactions scales with their active surface area, their surface charge, given by the ζ-potential, and their surface defects (via the Ce3+/Ce4+ ratio). Haloperoxidase-like reactions are controlled through the ζ-potential as they involve the adsorption of charged halide anions to the CeO2 surface, whereas peroxidase-like reactions without charged substrates are controlled through the specific surface area SBET. Mesoporous CeO2−x particles, with large surface areas, were prepared via template-free hydrothermal reactions and characterized by small-angle X-ray scattering. Surface area, ζ-potential and the Ce3+/Ce4+ ratio are controlled in a simple and predictable manner by the synthesis time of the hydrothermal reaction as demonstrated by X-ray photoelectron spectroscopy, sorption and ζ-potential measurements. The surface area increased with synthesis time, whilst the Ce3+/Ce4+ ratio scales inversely with decreasing ζ-potential. In this way the catalytic activity of mesoporous CeO2−x particles could be tailored selectively for haloperoxidase- and peroxidase-like reactions. The ease of tuning the surface properties of mesoporous CeO2x particles by varying the synthesis time makes the synthesis a powerful general tool for the preparation of nanocatalysts according to individual needs.
The COVID-19 pandemic posed new and manifold challenges to organizations and their operations worldwide. Conformity assessment bodies (CABs), such as testing or medical laboratories, certification, and inspection bodies, were also affected by the associated disruptions. Their role in this crisis is highly relevant, as CABs are essential pillars of the quality infrastructure: their activities ensure that products and services meet requirements as defined in standards and regulations, thereby contributing to their safety and reliability. The question arises of how CABs and their operations were affected by the pandemic and how they responded. To this end, we present the results of an international survey of 986 CABs of all types in Germany, the UK, Italy, and New Zealand. Overall, CABs reported, on average, a reduction in demand for their services during the pandemic, facing restrictions in all countries. In addition, the pandemic had an overall negative impact on the CABs’ investment and innovation activities. However, investments in digital infrastructure were increased as a countermeasure, with CABs reporting a higher need for digitalization. The paper highlights and discusses results from in-depth analyses relevant to policymakers and industry alike.
The aim of this study was to identify specific truffle marker substances within the truffle aroma. The aroma profile of different truffle species was analyzed using static headspace sampling with gas chromatography mass spectrometry analysis (SHS/GC-MS). Possible marker substances were identified, taking the additional literature into account. The selected marker substances were tested in an experiment with 19 truffle dogs. The hypothesis “If trained truffle dogs recognize the substances as supposed truffles in the context of an experiment, they can be regarded as specific” was made. As it would be nearly impossible to investigate every other possible emitter of the same compounds to determine their specificity, this hypothesis was a reasonable approximation. We were interested in the question of what it is the dogs actually search for on a chemical level and whether we can link their ability to find truffles to one or more specific marker substances. The results of the dog experiment are not as unambiguous as could have been expected based on the SHS/GC-MS measurements. Presumably, the truffle aroma is mainly characterized and perceived by dogs by dimethyl sulfide and dimethyl disulfide. However, as dogs are living beings and not analytical instruments, it seems unavoidable that one must live with some degree of uncertainty regarding these results.
Mechanically stable structures with interconnected hierarchical porosity combine the benefits of both small
and large pores, such as high surface area, pore volume, and good mass transport capabilities. Hence, lightweight micro-/meso-/macroporous monoliths are prepared from ordered mesoporous silica COK-12 by means of spark plasma sintering (SPS, S-sintering) and compared to conventionally (C-) sintered monoliths. A multi-scale model is developed to fit the small angle X-ray scattering data and obtain information on the hexagonal lattice parameters, pore sizes from the macro to the micro range, as well as the dimensions of the silica population. For both sintering techniques, the overall mesoporosity, hexagonal pore ordering, and amorphous character are preserved. The monoliths' porosity (77–49%), mesopore size (6.2–5.2 nm), pore volume (0.50–0.22 g cm-3
), and specific surface area (451–180 m2 g-1) decrease with increasing processing temperature and pressure. While the difference in porosity is enhanced, the
structural parameters between the C-and S-sintered monoliths are largely converging at 900 C, except for the mesopore size and lattice parameter, whose dimensions are more extensively preserved in the
S-sintered monoliths, however, coming along with larger deviations from the theoretical lattice. Their higher mechanical properties (biaxial strength up to 49 MPa, 724 MPa HV 9.807 N) at comparable porosities and ability to withstand ultrasonic treatment and dead-end filtration up to 7 bar allow S-sintered monoliths to reach a high permeance (2634 L m-2 h-1 bar-1), permeability (1.25 x 10^-14 m2), and ability to reduce the chemical oxygen demand by 90% during filtration of a surfactant-stabilized oil in water emulsion, while indicating reasonable resistance towards fouling.
Nebivolol (NEB), a β-blocker frequently used to treat cardiovascular diseases, has been widely detected in aquatic environments, and can be degraded under exposure to UV radiation, leading to the formation of certain transformation products (UV-TPs). Thus, the toxic effects of NEB and its UV-TPs on aquatic organisms are of great importance for aquatic ecosystems. In the present study, the degradation pathway of NEB under UV radiation was investigated. Subsequently, zebrafish embryos/larvae were used to assess the median lethal concentration (LC50) of NEB, and to clarify the sub-lethal effects of NEB and its UV-TPs for the first time. It was found that UV radiation could reduce the toxic effects of NEB on the early development of zebrafish. Transcriptomic analysis identified the top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in zebrafish larvae exposed to NEB, most of which were associated with the antioxidant, nervous, and immune systems. The number of differentially expressed genes (DEGs) in the pathways were reduced after UV radiation. Furthermore, the analysis of protein biomarkers, including CAT and GST (antioxidant response), AChE and ACh (neurotoxicity), CRP and LYS (immune response), revealed that NEB exposure reduced the activity of these biomarkers, whereas UV radiation could alleviate the effects. The present study provides initial insights into the mechanisms underlying toxic effects of NEB and the detoxification effects of UV radiation on the early development of zebrafish. It highlights the necessity of considering the toxicity of UV-TPs when evaluating the toxicity of emerging pollutants in aquatic systems.
Inflammatory bowel diseases (IBD) comprise mainly ulcerative colitis (UC) and Crohn´s disease (CD). Both forms present with a chronic inflammation of the (gastro) intestinal tract, which induces excessive changes in the composition of the associated extracellular matrix (ECM). In UC, the inflammation is limited to the colon, whereas it can occur throughout the entire gastrointestinal tract in CD. Tools for early diagnosis of IBD are still very limited and highly invasive and measures for standardized evaluation of structural changes are scarce. To investigate an efficient non-invasive way of diagnosing intestinal inflammation and early changes of the ECM, very small superparamagnetic iron oxide nanoparticles (VSOPs) in magnetic resonance imaging (MRI) were applied in two mouse models of experimental colitis: the dextran sulfate sodium (DSS)-induced colitis and the transfer model of colitis. For further validation of ECM changes and inflammation, tissue sections were analyzed by immunohistochemistry. For in depth ex-vivo investigation of VSOPs localization within the tissue, Europium-doped VSOPs served to visualize the contrast agent by imaging mass cytometry (IMC). VSOPs accumulation in the inflamed colon wall of DSS-induced colitis mice was visualized in T2* weighted MRI scans. Components of the ECM, especially the hyaluronic acid content, were found to influence VSOPs binding. Using IMC, colocalization of VSOPs with macrophages and endothelial cells in colon tissue was shown. In contrast to the DSS model, colonic inflammation could not be visualized with VSOP-enhanced MRI in transfer colitis. VSOPs present a potential contrast agent for contrast-enhanced MRI to detect intestinal inflammation in mice at an early stage and in a less invasive manner depending on hyaluronic acid content.
Rapid, cost-efficient, and eco-friendly methods are desired today for routine analysis of the Fusarium mycotoxin zearalenone (ZEN) in edible vegetable oils. Liquid chromatography with fluorescence detection (HPLC-FLD) is commonly used to reliably control the specified ZEN maximum levels, which requires efficient sample clean-up to avoid matrix interferences. Therefore, a highly selective extraction and clean-up method based on reversible covalent hydrazine chemistry (RCHC) using hydrazine-functionalized silica was developed. This efficient solid-phase extraction (SPE) involves reversible hydrazone formation of ZEN with the hydrazine moiety covalently bound to a solid phase. Optimal conditions were achieved with 1 mL SPE cartridges filled with 400 mg of hydrazine-functionalized silica. The developed RCHC-SPE method was validated in an interlaboratory comparison study (ILC) with twelve participants analyzing six edible vegetable oils with a focus on maize oils. The derived method parameters (ZEN recovery 83%, repeatability 7.0%, and reproducibility 18%) meet the performance criteria of Commission Regulation (EC) No 401/2006. The developed RCHC-SPE-based HPLC-FLD method allows the reliable quantification of ZEN in the range of 47–494 μg/kg for different types of edible vegetable oils, also for matrix-reach native oils. Due to the high efficiency, the significantly reduced matrix load helps to extend the lifetime of analytical equipment. Furthermore, the re-useability of the RCHC-SPE cartridges contributes to an eco-friendly approach and reduced analysis costs. To our knowledge, this is the first report on ZEN quantification in edible vegetable oils based on manual RCHC-SPE cartridges. Due to its high performance, the developed RCHC-SPE method is a promising alternative to the current European standard method EN 16924:2017 (HPLC-FLD part).
NaYF4:Yb3+/Tm3+@NaGdF4:Nd3+/Yb3+ upconversion nanoparticles (UCNPs) were prepared using a solvothermal method, and the effects of key factors such as the content of sensitiser Nd 3+ and Yb3+ on their luminescence properties were investigated. The nanoparticles are homogeneous in size and well dispersed. Under 808 nm excitation, it can produce strong upconversion fluorescence. At the same time, the nanoparticles have good temperature-sensing properties at the thermally coupled energy levels of 700 nm and 646 nm for Tm3+. Using its fluorescence intensity ratio (FIR), accurate temperature measurements can be performed, and it has been found that it exhibits different temperature sensing properties in low and high-temperature regions. The maximum relative sensitivity was found to be 0.88% K-1 and 1.89% K-1 for the lowtemperature region of 285 K-345 K and the high-temperature region of 345 K-495 K. The nanoparticles were applied to the internal temperature measurement of lithium batteries and the actual high-temperature environment, respectively, and were found to have good temperature measurementt performance.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2022)
Block-sparse regularization is already well known in active thermal imaging and is used for multiple-measurement-based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. We show the benefits of using a learned block iterative shrinkage thresholding algorithm (LBISTA) that is able to learn the choice of regularization parameters, without the need to manually select them. In addition, LBISTA enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present LBISTA and compare it with state-of-the-art block iterative shrinkage thresholding using synthetically generated and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations. Thus, this allows us to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super-resolution imaging.
A new “green” and mild synthesis of highly stable microcrystalline Cs2AgxNa1-xBiyIn1-yCl6 (CANBIC) perovskites under ambient conditions was developed that is scalable to the multi-gram production. Under UV illumination, the CANBIC perovskites emit intense broadband photoluminescence (PL) with a quantum yield (QY) of 92% observed for x = 0.35 and y = 0.01-0.02. The combination of strong UV absorbance and broadband visible emission, high PL QY, and long PL lifetimes of up to 1.4 μs, along with an outstanding stability makes these CANBICs a promising material class for many optical applications.