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Paper des Monats
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Raman spectroscopy is a well established tool for the analysis of vibration spectra, which then allow for the determination of individual substances in a chemical sample, or for their phase transitions. In the time-resolved-Raman-sprectroscopy the vibration spectra of a chemical sample are recorded sequentially over a time interval, such that conclusions for intermediate products (transients) can be drawn within a chemical process. The observed data-matrix M from a Raman spectroscopy can be regarded as a matrix product of two unknown matrices W and H, where the first is representing the contribution of the spectra and the latter represents the chemical spectra. One approach for obtaining W and H is the non-negative matrix factorization. We propose a novel approach, which does not need the commonly used separability assumption. The performance of this approach is shown on a real world chemical example.
This work addresses the problem of determining the number of components from sequential spectroscopic data analyzed by non-negative matrix factorization without separability assumption (SepFree NMF). These data are stored in a matrix M of dimension “measured times” versus “measured wavenumbers” and can be decomposed to obtain the spectral fingerprints of the states and their evolution over time. SepFree NMF assumes a memoryless (Markovian) process to underline the dynamics and decomposes M so that M = WH, with W representing the components’ fingerprints and H their kinetics. However, the rank of this decomposition (i.e., the number of physical states in the process) has to be guessed from pre-existing knowledge on the observed process. We propose a measure for determining the number of components with the computation of the minimal memory effect resulting from the decomposition; by quantifying how much the obtained factorization is deviating from the Markovian property, we are able to score factorizations of a different number of components. In this way, we estimate the number of different entities which contribute to the observed system, and we can extract kinetic information without knowing the characteristic spectra of the single components. This manuscript provides the mathematical background as well as an analysis of computer generated and experimental sequentially measured Raman spectra.
Performance Assessment for a Guided Wave-Based SHM System Applied to a Stiffened Composite Structure
(2022)
To assess the ability of structural health monitoring (SHM) systems, a variety of prerequisites and contributing factors have to be taken into account. Within this publication, this variety is analyzed for actively introduced guided wave-based SHM systems. For these systems, it is not possible to analyze their performance without taking into account their structure and their applied system parameters. Therefore, interdependencies of performance assessment are displayed in an SHM pyramid based on the structure and its monitoring requirements. Factors influencing the quality, capability and reliability of the monitoring system are given and put into relation with state-of-the-art performance analysis in a non-destructive evaluation. While some aspects are similar and can be treated in similar ways, others, such as location, environmental condition and structural dependency, demand novel solutions. Using an open-access data set from the Open Guided Waves platform, a detailed method description and analysis of path-based performance assessment is presented.The adopted approach clearly begs the question about the decision framework, as the threshold affects the reliability of the system. In addition, the findings show the effect of the propagation path according to the damage position. Indeed, the distance of damage directly affects the system performance. Otherwise, the propagation direction does not alter the potentiality of the detection approach despite the anisotropy of composites. Nonetheless, the finite waveguide makes it necessary to look at the whole paths, as singular phenomena associated with the reflections may appear. Numerical investigation helps to clarify the centrality of wave mechanics and the necessity to take sensor position into account as an influencing factor. Starting from the findings achieved, all the issues are discussed, and potential future steps are outlined.
The mechanism of mixed-ligand metal–organic framework (MOF) formation, and the possible role of intermediate single-ligand metal complexes during mechanosynthesis, have not been explored yet. For the first time, we report here in situ real-time monitoring of the mechanochemical formation mechanism of mixed-ligand MOFs. Our results show that binary phases can act as intermediates or competing products in one-pot and stepwise synthesis.
One of the challenges of high-temperature polymer electrolyte membrane fuel cells is the poisoning of the Pt catalyst with H3PO4. H3PO4 is imbibed into the routinely used polybenzimidazole-based membranes, which facilitate proton conductivity in the temperature range of 120−200 °C. However, when leached out of the membrane by water produced during operation, H3PO4 adsorbs on the Pt catalyst surface, blocking the active sites and hindering the oxygen reduction reaction (ORR).
The reduction of H3PO4 to H3PO3, which occurs at the anode due to a combination of a low potential and the presence of gaseous H2, has been investigated as an additional important contributing factor to the observed poisoning effect. H3PO3 has an affinity toward adsorption on Pt surfaces even greater than that of H2PO4 −. In this work, we investigated the poisoning effect of both H3PO3 and H3PO4 using a half-cell setup with a gas diffusion electrode under ambient conditions. By means of in situ X-ray absorption spectroscopy, it was possible to follow the signature of different species adsorbed on the Pt nanoparticle catalyst (H, O, H2PO4 −, and H3PO3) at different potentials under ORR conditions in various electrolytes (HClO4, H3PO4, and H3PO3). It was found that H3PO3 adsorbs in a pyramidal configuration P(OH)3 through a Pt−P bond. The competition between H3PO4 and H3PO3 adsorption was studied, which should allow for a better understanding of the catalyst poisoning mechanism and thus assist in the development of strategies to mitigate this phenomenon in the future by minimizing H3PO3 generation by, for example, improved catalyst design or adapted operation conditions or changes in the electrolyte composition.
The Boltzmann plot is one of the most widely used methods for determining the temperature in different types of laboratory plasmas. It operates on the logarithm as a function of the dimensional argument, which assumes that the correct physical units are used. In many works using the Boltzmann method, there is no analysis of the dimension of this argument, which may be the cause of a potential error. This technical note offers a brief description of the method and shows how to correctly use physical units when using transcendental functions like the logarithm.
The performance of the Monte Carlo (MC) algorithm for calibration-free LIBS was studied on the example of a simulated spectrum that mimics a metallurgical slag sample. The underlying model is that of a uniform, isothermal, and stationary plasma in local thermodynamical equilibrium.
Based on the model, the algorithm generates from hundreds of thousands to several millions of simultaneous configurations of plasma parameters and the corresponding number of spectra. The parameters are temperature, plasma size, and concentrations of species. They are iterated until a cost function, which indicates a difference between synthetic and simulated slag spectra, reaches its minimum. After finding the minimum, the concentrations of species are read from the model and compared to the certified values. The algorithm is parallelized on a graphical processing unit (GPU) to reduce computational time. The minimization of the cost function takes several minutes on the GPU NVIDIA Tesla K40 card and depends on the number of elements to be iterated. The intrinsic accuracy of the MC calibration-free method is found to be around 1% for the eight elements tested. For a real experimental spectrum, however, the efficiency may turn out to be worse due to the idealistic nature of the model, as well as incorrectly chosen experimental conditions. Factors influencing the performance of the method are discussed.
Shape memory alloy structures for actuator and vibration damper applications may be manufactured using wire arc additive manufacturing (W AAM), which is one of the additive manufacturing technologies. Multilayer deposition causes heat accumulation during W AAM, which rises the preheat temperature of the previously created layer. This leads to process instabilities, which result in deviations from the desired dimensions and mechanical properties changes. During W AAM deposition of the wall structure, a systematic research is carried out by adjusting the interlayer delay from 10 to 30 s. When the delay period is increased from 10 to 30 s, the breadth decreases by 45% and the height increases by 33%. Grain refinement occurs when the interlayer delay duration is increased, resulting in better hardness, phase transformation temperature, compressive strength, and shape recovery behavior. This study shows how the interlayer delay affects the behavior of W AAM-built nickel-titanium alloy (NiTi) structures in a variety of applications.
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
This study will present a new approach to distinguishing writing inks that have the same elemental compositions and visual appearances. The approach is based on displaying the intensity of elemental distributions as heat maps that represent data recorded with a scanning μX-ray fluorescence spectrometer. The heat maps present the data so as to facilitate digitally identifying and distinguishing between inks used to produce, correct, and reink two medieval Torah scrolls. As ritual objects, Torah scrolls had to be written in accordance with exacting standards that evolved over time. This requirement led to successive stages of modifications, sometimes over centuries. Both vitriolic and non-vitriolic inks used to modify Torah scrolls can be visually identical to each other. Furthermore, different non-vitriolic inks usually have an identical elemental composition. The solid material analysis evidence and its presentation as heat maps made it possible to discriminate between original and altered portions of text that in some cases would have been impossible. Our interdisciplinary work brought together conservation, material science, paleog-raphy, and philology to enable the identification of complex stratigraphy in multiple stages of production, correction, and reinking. ©2 0 2 2 Published by Elsevier Masson SAS.
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.
Lithium and boron are trace components of magmas, released during exsolution of a gas phase during volcanic activity. In this study, we determine the difusivity and isotopic fractionation of Li and B in hydrous silicate melts. Two glasses were synthesized with the same rhyolitic composition (4.2 wt% water), having diferent Li and B contents; these were studied in difusion-couple experiments that were performed using an internally heated pressure vessel, operated at 300 MPa in the temperature range 700–1250 °C for durations from 0 s to 24 h. From this we determined activation energies for Li and B difusion of 57±4 kJ/mol and 152±15 kJ/mol with pre-exponential factors of 1.53 × 10–7 m2/s and 3.80× 10–8 m2 /s, respectively. Lithium isotopic fractionation during difusion gave β values between 0.15 and 0.20, whereas B showed no clear isotopic fractionation. Our Li difusivities and isotopic fractionation results difer somewhat from earlier published values, but overall confrm that Li difusivity increases with water content. Our results on B difusion show that similarly to Li, B mobility increases in the presence of water. By applying the Eyring relation, we confrm that B difusivity is limited by viscous fow in silicate melts. Our results on Li and B difusion present a new tool for understanding degassing-related processes, ofering a potential geospeedometer to measure volcanic ascent rates.
Heterogeneous Oxysulfide@Fluoride Core/ Shell Nanocrystals for Upconversion-Based Nanothermometry
(2022)
Lanthanide (Ln3+)-doped upconversion nanoparticles (UCNPs) often suffer from weak luminescence, especially when their sizes are ultrasmall (less than 10 nm). Enhancing the upconversion luminescence (UCL) efficiency of ultrasmall UCNPs has remained a challenge that must be undertaken if any practical applications are to be envisaged. Herein, we present a Ln3+-doped oxysulfide@fluoride core/shell heterostructure which shows efficient UCL properties under 980nm excitation and good stability in solution. Through epitaxial heterogeneous growth, a ∼4 nm optically inert β-NaYF4 shell was coated onto ∼5 nm ultrasmall Gd2O2S:20%Yb,1%Tm. These Gd2O2S:20%Yb,1%Tm@NaYF4 core/shell UCNPs exhibit a more than 800-fold increase in UCL intensity compared to the unprotected core, a 180-fold increase in luminescence decay time of the 3H4 → 3H6 Tm3+ transition from 5 to 900 μs, and an upconversion quantum yield (UCQY) of 0.76% at an excitation power density of 155 W/cm2. Likewise, Gd2O2S:20%Yb,2%Er@NaYF4 core/shell UCNPs show a nearly 5000-fold
increase of their UCL intensity compared to the Gd2O2S:20%Yb,2%Er core and a maximum UCQY of 0.61%. In the Yb/Er core−shell UCNP system, the observed variation of luminescence intensity ratio seems to originate from a change in lattice strain as the temperature is elevated. For nanothermometry applications, the thermal sensitivities based on thermally coupled levels are estimated for both Yb/Tm and Yb/Er doped Gd2O2S@NaYF4 core/shell UCNPs.
The ability of industrial X-ray computed tomography (CT) to scan an object with several internal and external features at once causes increasing adoption in dimensional metrology. In order to evaluate the quality of a measurement value, the task-specific measurement uncertainty has to be determined. Currently, VDI/VDE 2630 part 2.1 gives a guideline to determine the uncertainty of CT measurements experimentally by conducting repeated measurements. This is costly and time-consuming. Thus, the aim is to determine the task-specific measurement uncertainty numerically by simulations (e. g. according to the guide to expression of uncertainty in measurement (GUM) Supplement 1). To achieve that, a digital twin is necessary. This contribution presents a simple first approach how a digital twin can be built. In order to evaluate this approach, a study comparing measurements and simulations of different real CT systems was carried out by determining the differences between the measurement results of the digital twin and of the measurement results of the real-world CT systems. The results have shown a moderate agreement between real and simulated data. To improve on this aspect, a standardized method to characterize CT systems and methods to implement CT parameters into the simulation with sufficient accuracy will be developed.
Ultrasonic probes for high-temperature applications are provided with metallic wedges, which can withstand the contact with the high temperature of the inspected structure. The ultrasonic signal travels within the wedge and gets reflected from its boundaries, causing interference signals called “ghost echoes”. The current work presents an investigation of the additional damping effect provided by porous sintered metal plates applied onto the surface of the wedge. In particular, the study evaluates the effect of damping plate thickness on the interference signal level at different transmission frequencies. Damping plates made of sintered metal SIKA-R 15 AX were attached to a wedge prototype made of steel 1.4301. The study revealed, that the most effective thickness of damping plates in the selected frequency interval of 1 to 4 MHz is equal to 4 mm. The evaluation of the interference signal has shown that the application of such damping plates to the wedge surface contributes to an additional attenuation of an interference signal of 10 to 30 dB after 500 μs of signal propagation.
Analysis of electrochemical and liver microsomal transformation products of lasalocid by LC/HRMS
(2022)
Rationale: Lasalocid (LAS), an ionophore, is used in cattle and poultry farming as feed additive for its antibiotic and growth-promoting properties. Literature on transformation products (TP) resulting from LAS degradation is limited. So far, only hydroxylation is found to occur as the metabolic reaction during the LAS degradation. To investigate potential TPs of LAS, we used electrochemistry (EC) and liver microsome (LM) assays to synthesize TPs, which were identified using liquid chromatography high-resolution mass spectrometry (LC/HRMS).
Methods: Electrochemically produced TPs were analyzed online by direct coupling of the electrochemical cell to the electrospray ionization (ESI) source of a Sciex Triple-TOF high resolution mass spectrometer. Then, EC-treated LAS solution was collected and analyzed offline using LC/HRMS to confirm stable TPs and improve their annotation with a chemical structure due to informative MS/MS spectra. In a complementary approach, TPs formed by rat and human microsomal incubation were investigated using LC/HRMS. The resulting data were used to investigate LAS modification reactions and elucidate the chemical structure of obtained TPs.
Results: The online measurements identified a broad variety of TPs, resulting from modification reactions like (de-)hydrogenation, hydration, methylation, oxidation as well as adduct formation with methanol. We consistently observed different ion complexations of LAS and LAS-TPs (Na+; 2Na+ K+; NaNH4 +; KNH4 +). Two stable methylated EC-TPs were found, structurally annotated, and assigned to a likely modification reaction. Using LM incubation, seven TPs were formed, mostly by oxidation/hydroxylation. After the identification of LM-TPs as Na+-complexes, we identified LM-TPs as K+-complexes.
Conclusion: We identified and characterized TPs of LAS using EC- and LM-based methods. Moreover, we found different ion complexes of LAS-based TPs. This knowledge, especially the different ion complexes, may help elucidate the metabolic and environmental degradation pathways of LAS.
Diffraction enhanced imaging (DEI) is an advanced digital radiographic imaging technique employing the refraction of X-rays to contrast internal interfaces. This study aims at qualitatively and quantitatively evaluating images acquired using this technique and to assess how different fitting functions to the typical rocking curves (RCs) influence the quality of images. RCs are obtained for every image pixel. This allows the separate determination of the absorption and the refraction properties of the material in a position-sensitive manner. Comparison of various types of fitting functions reveals that the Pseudo-Voigt (PsdV) function is best suited to fit typical RCs. A robust algorithm was developed in the Python programming language, which reliably extracts the physically meaningful information from each pixel of the image. We demonstrate the potential of the algorithm with two specimens: a silicone gel specimen that has well-defined interfaces, and an additively manufactured polycarbonate specimen.
CS particles show unique properties by merging individual characteristics of the core and the shell materials. An alteration particularly in their surface roughness affects the final performance of the particles in the targeted application. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task employing microscopic techniques being scarce and showing large differences in terms of methodology and results.
In our previous work, we have reported a systematic study with a reliable analysis tool, which evaluates profile roughness quantitatively, for individual core-shell microparticles using electron microscopy (EM) images of both types, Scanning Electron Microscopy (SEM) and transmission mode SEM (or TSEM). The SEM images contain two-dimensional (2D) information, therefore, provide profile roughness data only from the projection in the horizontal plane (in other words, from the “belly”) of a spherical particle. The present study offers a practical procedure to give access to more information by tilting the sample holder and hence allowing images of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, extended information on surface roughness of the particle can be extracted. Thus, instead of obtaining 2D information from a single SEM image, three-dimensional (3D) information is obtained from 2D projections recorded at different particle orientations.
A first tricolor fluorescent pH nanosensor is presented, which was rationally designed from biocompatible carboxylated polystyrene nanoparticles and two analyte-responsive molecular fluorophores. Its fabrication involved particle staining with a blue-red-emissive dyad, consisting of a rhodamine moiety responsive to acidic pH values and a pH-inert quinoline fluorophore, followed by the covalent attachment of a fluorescein dye to the particle surface that signals neutral and basic pH values with a green fluorescence. These sensor particles change their fluorescence from blue to red and green, depending on the pH and excitation wavelength, and enable ratiometric pH measurements in the pH range of 3.0−9.0. The localization of the different sensor dyes in the particle core and at the particle surface was confirmed with fluorescence microscopy utilizing analogously prepared polystyrene microparticles. To show the application potential of these polystyrene-based multicolor sensor particles, fluorescence microscopy studies with a human A549 cell line were performed, which revealed the cellular uptake of the pH nanosensor and the differently colored emissions in different cell organelles, that is, compartments of the endosomal-lysosomal pathway. Our results demonstrate the underexplored potential of biocompatible polystyrene particles for multicolor and multianalyte sensing and bioimaging utilizing hydrophobic and/or hydrophilic stimuli-responsive luminophores.
A fluorolytic sol–gel method was used for the fast and simple synthesis of small cubic-phase SrF2:Yb3+, Er3+ upconversion (UC) nanocrystals (UCNC) of different composition at room temperature. Systematic studies of the crystal phase and particle size of this Yb3+,Er3+-concentration series as well as excitation power density (P)-dependent UC luminescence (UCL) spectra, UCL quantum yields (ΦUCL), and UCL decay kinetics yielded maximum UCL performance for doping amounts of Yb3+ of 13.5% and Er3+ of 1.3% in the studied doping and P-range (30–400 W cm−2). Furthermore, ΦUCL were determined to be similar to popular β-NaYF4:Yb3+,Er3+. The relative spectral UCL distributions revealed that all UCNC show a strong red emission in the studied doping and P-range (30–400 W cm−2) and suggest that the UCL quenching pathway for unshelled cubic-phase SrF2:Yb3+,Er3+ UCNC differs from the commonly accepted population and depopulation pathways of β-NaYF4:Yb3+,Er3+ UCNC. In SrF2:Yb3+,Er3+ UCNC the 4S3/2 →
4I13/2 transition exhibits a notably stronger sensitivity towards P and reveals increasing values for decreasing Yb3+–Yb3+ distances while the 4I9/2 → 4I15/2 transition is significantly less affected by P and energy migration facilitated UCL quenching. These results emphasize the complexity of the UC processes and the decisive role of the crystal phase and symmetry of the host lattice on the operative UCL quenching mechanism in addition to surface effects. Moreover, the room temperature UCNC synthesis enabled a systematic investigation of the influence of the calcination temperature on the crystal phase of powder-UCNC and the associated UCL properties. Calcination studies of solid UCNC of optimized doping concentration in the temperature range of 175 °C and 800 °C showed the beneficial influence of temperature-
induced healing of crystal defects on UCL and the onset of a phase separation connected with the oxygenation of the lanthanide ions at elevated temperature. This further emphasizes the sensitivity of the UC process to the crystal phase and quality of the host matrix.
Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
Li-rich nanoparticles of Li1+xMn2–xO4 doped with Al, Co, or Ni are successfully synthesized using a facile, fast, and efficient microwave-assisted hydrothermal route. Synchrotron X-ray diffraction confirms the formation of the crystalline cubic spinel phase type. X-ray absorption spectroscopy analysis at the Co and Ni K- and L-edges verifies that the dopants are within the Li1+xMn2–xO4 spinel structure and are inactive during cycling in the bulk and at the surface. Moreover, we demonstrate that nanocrystallinity and cationic doping play an important role in improving the electrochemical performance with respect to LiMn2O4 microparticles. They significantly reduce the charge-transfer resistance, lower the first cycle irreversible capacity loss to 6%, and achieve a capacity retention between 85 and 90% after 380 cycles, with excellent Coulombic efficiency close to 99% without compromising the specific charge at a 5C cycling rate. Furthermore, the Mn K- and L-edges attest that after long cycling, the Mn oxidation state in the bulk differs from that at the surface caused by the Mn disproportion reaction; however, the cationic doping helps mitigate the Mn dissolution with respect to the undoped Li1+xMn2–xO4 nanoparticles, as indicated by inductively coupled plasma atomic emission spectrometry.
Validation of a fast and traceable radiographic scale calibration of dimensional computed tomography
(2022)
A fast and highly precise method of determining the geometrical scale factor of computed tomography (CT) measurements has been validated successfully by Bundesanstalt für Materialforschung und -prüfung (BAM), the Federal Institute of Metrology (METAS) and Physikalisch-Technische Bundesanstalt (PTB) within the scope of AdvanCT (Advanced Computed Tomography for dimensional and surface measurements in industry), a project funded in the European Metrology Programme for Innovation and Research (EMPIR). The method has been developed by PTB and requires only two radiographic images of a calibrated thin 2D standard (hole grid standard) from two opposite directions. The mean grid distance is determined from both radiographs. From this and with the help of the calibration result, the radiographic scale and therefore the voxel size is determined. The procedure takes only a few minutes and avoids a time-consuming CT scan. To validate the method, the voxel sizes determined via this method were compared with voxel sizes determined from CT scans of calibrated objects. Relative deviations between the voxel sizes in the range of 10−5 were
achieved with minimal effort using cone-beam CT systems at moderate magnifications.
Methodologies for model parameterization of virtual CTs for measurement uncertainty estimation
(2022)
X-ray computed tomography (XCT) is a fast-growing technology for dimensional measurements in industrial applications. However, traceable and efficient methods to determine measurement uncertainties are not available. Guidelines like the VDI/VDE 2630 Part 2.1 suggest at least 20 repetitions of a specific measurement task, which is not feasible for industrial standards. Simulation-based approaches to determine task specific measurement uncertainties are promising, but require closely adjusted model parameters and an integration of error sources like geometrical deviations during a measurement. Unfortunately, the development of an automated process to parameterize and integrate geometrical deviations into XCT models is still an open issue. In this work, the whole processing chain of dimensional XCT measurements is taken into account with focus on the issues and requirements to determine suitable parameters of geometrical deviations. Starting off with baseline simulations of different XCT systems, two approaches are investigated to determine and integrate geometrical deviations of reference measurements. The first approach tries to iteratively estimate geometric deviation parameter values to match the characteristics of the missing error sources. The second approach estimates those values based on radiographs of a known calibrated reference object. In contrast to prior work both approaches only use a condensed set of parameters to map geometric deviations. In case of the iterative approach, some major issues regarding unhandled directional dependencies have been identified and discussed. Whereas the radiographic method resulted in task specific expanded measurements uncertainties below one micrometre even for bi-directional features, which is a step closer towards a true digital twin for uncertainty estimations in dimensional XCT.
Probe diagnostics is used to determine the electron temperature and electron number density in a low pressure inductively coupled plasma (ICP) ignited in the mixture of SiF4, Ar and H2. Emission spectra of mixtures with different stoichiometry of components are investigated and the electron density distribution function (EDDF) is estimated. The optimal conditions for high conversion of SiF4 into Si are found by studying the dependence of the yield of silicon upon the ratio of reagents. The maximum achieved yield of silicon is 85% under the optimal conditions. Based on the analysis of IR and MS spectra of exhaust gases, 5% of initial SiF4 converts into volatile fluorosilanes. A rate of production of Si is 0.9 g/h at the energy consumption 0.56 kWh /g.
Mechanochemistry has become a sustainable and attractive cost-effective synthetic technique, largely used within the frame of crystal engineering. Cocrystals, namely, crystalline compounds made of different chemical entities within the same crystal structure, are typically synthesized in bulk via mechanochemistry; however, whereas the macroscopic aspects of grinding are becoming clear, the fundamental principles that underlie mechanochemical cocrystallization at the microscopic level remain poorly understood. Time-resolved in situ (TRIS) monitoring approaches have opened the door to exceptional detail regarding mechanochemical reactions. We here report a clear example of cocrystallization between two solid coformers that proceeds through the formation of a metastable low melting binary eutectic phase. The overall cocrystallization process has been monitored by time-resolved in situ (TRIS) synchrotron X-ray powder diffraction with a customized ball milling setup, currently available at μ Spot beamline at BESSY-II, Helmholtz-Zentrum Berlin. The binary system and the low melting eutectic phase were further characterized via DSC, HSM, and VT-XRPD.
Fire-gilding is a historic technique for the application of golden layers on a number of different base materials utilizing a gold amalgam. This technique leaves a significant amount of Hg in the golden layer, giving archeometrists a reliable indicator to identify firegildings.
Recent findings on presumably fire-gilded objects have shown in several cases significantly lower Hg content than previously studied objects. This prompted a synchrotron-based X-ray fluorescence investigation into the Hg distribution along the material–gilding interface, as well as a series of measurements regarding the Hg content development in fire-gilded samples during artificial aging. This work presents findings on laboratory-prepared fire-gildings, indicating an Hg enrichment at the interface of firegilded silver samples. Notably, such an enrichment is missing in fire-gilded copper samples. Further, it is confirmed that fire-gilded layers typically do not undercut an Hg bulk content of 5%. In this light, it seems improbable that ancient samples that contain <5% Hg are fire-gilded. The results presented in this study might lead to a non-destructive method to identify the Hg enrichment at the interface. This might be obtained by a combination of different non-destructive measurements and might also work unambiguously in samples in which the gold top layer is altered.
EXAFS analysis of pure elements, binary and ternary equiatomic refractory alloys within the Nb-Zr-Ti-Hf- Ta system is performed at the Nb and Zr K-edges to analyze the evolution of the chemical local environ- ment and the lattice distortion. A good mixing of the elements is found at the atomic scale. For some compounds, a distribution of distances between the central atom and its neighbors suggests a distortion of the structure. Finally, analysis of the Debye-Waller parameters shows some correlation with the lat- tice distortion parameter δ², and allows to quantify experimentally the static disorder in medium entropy alloys.
Within this work, the combination of a microdroplet generator and an ICP-ToF-MS for nanoparticle analysis is presented. For the size determination of platinum nanoparticles an on-line isotope dilution analysis approach was developed. The 194Pt/195Pt isotopic ratio was used for the characterization of the particles, while the 182W/183W isotopic ratio was monitored simultaneously for mass bias correction. The on-line ID-MDG-sp-ICP-ToF-MS approach was deployed for the size determination of three platinum nanoparticle samples (50 nm, 63 nm, 70 nm); for validation, complementary size characterization techniques (sp-ICP-ToF-MS and TEM) were used. The robustness of this technique was evidenced, by using sodium chloride concentrations up to 100 mg L−1 as a matrix component. Our new on-line ID MDG-sp-ICP-ToF-MS approach is a promising tool for the fast and reliable determination of nanoparticles' size in severe matrix concentrations, e.g., environmental samples.
The spatial distribution and concentration of lanthanide activator and sensitizer dopant ions are of key importance for the luminescence color and efficiency of upconverting nanoparticles (UCNPs). Quantifying dopant ion distributions and intermixing, and correlating them with synthesis methods require suitable analytical techniques. Here, X-ray photoelectron spectroscopy depth-profiling with tender X-rays (2000–6000 eV), providing probe depths ideally matched to UCNP sizes, is used to measure the depth-dependent concentration ratios of Er3+ to Yb3+, [Er3+]/[Yb3+], in three types of UCNPs prepared using different reagents and synthesis methods. This is combined with data simulations and inductively coupled plasma-optical emission spectroscopy (ICP-OES) measurements of the lanthanide ion concentrations to construct models of the UCNPs’ dopant ion distributions. The UCNP sizes and architectures are chosen to demonstrate the potential of this approach. Core-only UCNPs synthesized with XCl3·6H2O precursors (β-phase) exhibit a homogeneous distribution of lanthanide ions, but a slightly surface-enhanced [Er3+]/[Yb3+] is observed for UCNPs prepared with trifluroacetate precursors (α-phase). Examination of Yb-core@Er-shell UCNPs reveals a co-doped, intermixed region between the single-doped core and shell. The impact of these different dopant ion distributions on the UCNP's optical properties is discussed to highlight their importance for UCNP functionality and the design of efficient UCNPs.
Electron microscopy (EM) is the gold standard for the characterisation of the morphology (size and shape) of nanoparticles. Visual observation of objects under examination is always a necessary first step in the characterisation process. Several questions arise when undertaking to identify and count particles to measure their size and shape distribution. In addition to challenges with the dispersion and identification of the particles, more than one protocol for counting particles is in use. This paper focuses on precise rules for the counting of particles in EM micrographs, as this influences the measurement accuracy of the number of particles, thus implicitly affecting the size values of the counted particles. We review and compare four different, commonly used methods for counting, which we then apply in case studies. The impact of the selected counting rule on the obtained final particle size distribution is highlighted. One main aim of this analysis is to support the application of a specific, well-defined counting approach in accordance with regulatory
requirements to contribute to achieving more reliable and reproducible results. It is also useful for the new harmonised measurement procedures for determining the particle size and particle size distribution of nanomaterials.