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Paper des Monats
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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.
This dataset contains raw data resulting from Impact-Echo measurements at the reference concrete block "IE Platte", located at BAM (German Federal Institute for Materials Research and Testing).
The specimen contains three polystyrene slabs and one polyethylene foil to act as reflectors. The specimen was produced in a three-step process. First, the base plate was cast. Second, the reflectors were taped to the base plate. Finally, the upper layer was cast on top of base plate and reflectors. A drawing is contained in the dataset.
The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publications elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010).
The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition.
Measurements were conducted using a grid of 29x29 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s.
The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points.
The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools.
Several aspects were explored towards the standardization of a suitable procedure. The use of gaseous standards is necessary and a standard gas mixture containing 60 substances was successfully generated and employed for further investigations. The suitability of different chromatography columns was addressed: The use of PLOT (Porous Layer Open Tubular) columns is well suitable for VVOC analysis. The recoveries of the 60 analytes on several adsorbents and their combinations were determined: A combination of a graphitized carbon black and a carbon molecular sieve showed great results for all analytes. Carbon molecular sieves adsorb water which can impair the analysis. Different options such as purging, the use of a drying system or splitting were investigated for water removal. This contribution will present experimental results supporting the standardization of a method for VVOC analysis.
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.
Reliability assessment of Structural Health Monitoring (SHM) systems
poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements.
Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed.
Performance assessment for GuidedWave (GW)-based Structural Health Monitoring (SHM) systems is of major importance for industrial deployment.
With conventional feature extraction methods like damage indices, pathbased probability of detection (POD) analysis can be realized. To achieve reliability quantification enough data needs to be available, which is rarely the case.
Alternatives like methods for performance assessment on system level are still in development and in a discussion phase. In this contribution, POD results using an Artificial Intelligence (AI)-based data analysis are compared with those delivered by conventional data analysis. Using an open-access dataset from Open Guided Wave platform, the possibility of performance assessment for GW-based SHM systems using AI-based data analysis is shown in detail. An artificial neural network (ANN) classifier is trained to detect artificial damage in a stiffened CFRP plate. As input for the ANN, classical damage indicators are used. The ANN is tested to detect damage at another position, whose inspection data were not previously used in training. The findings show very high detection capabilities without sorting any specific path but only having a global view of current damage metrics. The systematic evaluation of the ANN predictions with respect to specific damage sizes allows to compute a probability of correct identification versus flaw dimension, somehow equivalent to and compared with the results achieved through classic path-based POD analysis. Also, sensitive paths are detected by ANN predictions allowing for evaluation of maximal distances between path and damage position. Finally, it is shown that the prediction performance of the ANN can be improved significantly by combining different damage indicators as inputs.
Temperature Compensation Strategies for Lamb Wave Inspection using Distributed Sensor Networks
(2022)
The application of temperature compensation strategies is crucial in structural health monitoring approaches based on guided waves. Actually, the varying temperature influences the performance of the inspection system inducing false alarms or missed detection, with a consequent reduction of reliability. This paper quantitatively describes a method to compensate the temperature effect, namely the optimal baseline selection (OBS), extending its application to the case of distributed sensor networks (DSN). The effect of temperature separation between baseline time-traces in OBS are investigated considering multiple couples of sensors employed in the DSN. A combined strategy that uses both OBS and frequent value warning is considered. Theoretical results are compared, using data from two several experiments, which use different frequency analysis with either predominantly A0 mode or S0 mode data or both. The focus is given on the fact that different paths are available in a sensor network and several possible combination of results are available. Nonetheless, introducing a frequent value warning it is possible to increase the efficiency of the OBS approach making use of fewer signal processing algorithms. These confirm that the performance of OBS quantitatively agrees with predictions and also demonstrate that the use of compensation strategies improve detectability of damage.
In this work, we report on our progress for investigating a new experimental approach for thermographic detection of internal defects by performing 2D photothermal super resolution reconstruction. We use modern high-power laser projector technology to repeatedly excite the sample surface photothermally with varying spatially structured 2D pixel patterns. In the subsequent (blind) numerical reconstruction, multiple measurements are combined by exploiting the joint-sparse nature of the defects within the specimen using nonlinear convex optimization methods. As a result, a 2D-sparse defect/inhomogeneity map can be obtained. Using such spatially structured heating combined with compressed sensing and computational imaging methods allows to significantly reduce the experimental complexity and to study larger test surfaces as compared to the one-dimensional approach reported earlier.
Acoustic methods are ideally suited for determining the mechanical properties of different materials non-destructively. The availability of such methods is particularly important for fiber-reinforced polymers (FRPs) because their properties strongly depend on the manufacturing process and in-service conditions. Since FRPs are mostly used in thin-walled components, properties can be derived from the dispersion curves of ultrasonic guided waves (UGWs).
Our approach is based on an inverse procedure in which the numerically calcu-lated dispersion curves are fitted to the measured curves. The acquisition is done by applying a broadband piezoelectric transducer (PZT) to excite and a 3D laser Doppler vibrometer (3D LDV) to record the waves. Compared to the ap-proaches based on laser excitation, the PZT provides a better signal-to-noise ra-tio because more energy is brought into the structure. Whereas the 3D LDV compared to a 1D LDV or a PZT allows capturing in-plane and out-of-plane components and thus providing more dispersion information. Since the inverse procedure requires many iterations before elastic properties are retrieved, an ef-ficient tool for the calculation of the dispersion curves is necessary. For this, the Scaled Boundary Finite Element Method is used. All in all, a good agreement between theoretical and experimental curves is demonstrated.
The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The challenges in the residual stress analysis of AM components are discussed on the basis on the show studies performed in BAM. Also, the synchrotron X-ray refraction technique, available in BAM, is presented, showing example of in-situ heating test of Al10SiMg AM material.
Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control. In fact, the optimization of both the AM process and the properties of TPMSS is impossible without considering structural characteristics as manufacturing accuracy, internal defects, and as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of laboratory X-ray computed tomography (XCT).
Quantification of the Total and Accessible Number of Functional Groups and Ligands on Nanomaterials
(2022)
Surface-functionalized organic and inorganic nanoparticles (NP) are of great interest in the life and material sciences, as they can be used e.g. as drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. NP performance in such applications depends not only on particle size, size distribution, and morphology, but also on surface chemistry, i.e. the total number of surface functional groups (FG) and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. Methods for FG quantification should be simple, robust, reliable, fast, and inexpensive, and allow for the characteriza-tion of a broad variety of nanomaterials differing in size, chemical composition, and optical properties.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG such as amine, carboxy, thiol and aldehyde functionalities, we investigated and compared various analytical methods commonly used for functional group quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance, mass spectrometry, and thermal analysis methods.
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.
Introduction: The influence of copper, iron and zinc concentrations on the formation of ß-amyloid plaques and neurofibrillary tangles in Alzheimer’s disease (AD) is widely discussed in the community. The results from human and animal studies so far are mixed with some studies showing a correlation and others not. From a number of studies, it is known that disease state and isotopic composition of essential elements can be coupled.
Aim: The aim of the study was to identify changes in element content and isotopic composition in two transgenic mouse models used in AD research compared to their genetic WT relatives and to establish whether element content and isotopic signature between different laboratories is comparable.
Methods: ß-amyloid (5xFAD) and tau overexpressing (L66) mice together with their matching wild-types were bred at dedicated facilities in accordance with the European Communities Council Directive (63/2010/EU). Serum and brain were sampled after sacrifice and the samples distributed among the participants of the study. The tissues were acid digested for total element determination and high-precision isotope ratio determination. Element content was determined by either sector-field or quadrupole-based inductively coupled plasma mass spectrometry (ICPMS). For the determination of isotope ratios multi-collector ICPMS was used.
Results: Total copper content was significantly higher for L66 and their matched WT compared to 5xFAD and WT. Brains of L66 mice contained more Fe in brain than their WT, Zn and Cu were not significantly different between L66 and WT. Whereas 5xFAD mice had a slightly lower Cu and slightly higher Zn concentration in brain compared to WT. The isotopic signature in brain of L66 mice for Fe was different from their controls, whereas Zn isotope ratios were influenced in 5xFAD mice compared to their WT. The Cu isotopic ratio did not seem to be influenced in either strain. In serum, the shifts were less pronounced.
Conclusion: Even though neither Tau-protein nor amyloid precursor protein are known to be metal-dependent / -containing proteins, the overexpression of both influences the Fe, Cu and Zn metabolism in brain and to some extent also in serum as can be seen not only using total element determination but probably more clearly studying the isotopic signature of Fe, Cu and Zn.
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.
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared.
Due to the fast growth of industry and the use of metal-containing compounds such as sewage sludge in agricultural fields, soil pollution associated with heavy metals presents a terrifying threat to the environment. Throughout the world, there are already 5 million sites of soil contaminated by heavy metals1. Some heavy metals pollutants can influence food chain safety and food quality, which in turn affects human health. According to the German Federal Soil Protection and Contaminated Site Ordinance (BBodSchV) 13 heavy metals such as arsenic (As), lead (Pb) and cadmium (Cd) are classified as heavily toxic to human health2. Therefore, elemental analysis and precise quantification of the heavy metals in soil are of great importance.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences3. For the first time, the applicability of MICAP-MS for elemental analysis of environmental soils is investigated in this work. For this purpose, 7 reference- and 3 random soil samples containing vanadium (V), cobalt (Co), zink (Zn), copper (Cu), chrome (Cr), mercury (Hg), As, Pb and Cd are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated using ICP-MS. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Moreover, the performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared
Laser-induced plasmas are widely used in many areas of science and technology; examples include spectrochemical analysis, thin film deposition, and material processing. Several topics will be addressed. First, general phenomenology of laser-induced plasmas will be discussed. Then, a chemical model will be presented based on a coupled solution of Navier-Stokes, state, radiative transfer, material transport, and chemical equations. Results of computer simulations for several chemical systems will be shown and compared to experimental observations obtained by optical imaging, spectroscopy, and tomography. The latter diagnostic tools will also be briefly discussed. Finally, a prospective application of laser-induced plasma and plasma modeling will be illustrated on the example of chemical vapor deposition of molybdenum borides and micro processing and coating of titanium dental implants.
IRWG strategy update
(2022)
In this study, carried out within the Joint Danube Survey 4, a comprehensive microplastic screening in the water column within a large European river basin from its source to estuary, including major tributaries, was realized. The objective was to develop principles of a systematic and practicable microplastic monitoring strategy using sedimentation boxes for collection of suspended particulate matter followed by its subsequent analysis using thermal extraction desorption-gas chromatography/mass spectrometry. In total, 18 sampling sites in the Danube River Basin were investigated. The obtained suspended particulate matter samples were subdivided into the fractions of >100 μm and <100 μm and subsequently analyzed for microplastic mass contents. The results showed that microplastics were detected in all samples, with polyethylene being the predominant polymer with maximum contents of 22.24 μg/mg, 3.23 μg/mg for polystyrene, 1.03 μg/mg for styrene-butadiene-rubber, and 0.45 μg/mg for polypropylene. Further, polymers such as different sorts of polyester, polyacrylates, polylactide, and natural rubber were not detected or below the detection limit. Additional investigations on possible interference of polyethylene signals by algae-derived fatty acids were assessed. In the context of targeted monitoring, repeated measurements provide more certainty in the interpretation of the results for the individual sites. Nevertheless, it can be stated that the chosen approach using an integrative sampling and determination of total plastic content proved to be successful.
In view of the increasing digitization of research and the use of data-intensive measurement and analysis methods, research institutions and their staff are faced with the challenge of documenting a constantly growing volume of data in a comprehensible manner, archiving them for the long term, and making them available for discovery and re-use by others in accordance with the FAIR principles. At BAM, we aim to facilitate the integration of research data management (RDM) strategies during the whole research cycle from the creation and standardized description of materials datasets to their publication in open repositories. To this end, we present the BAM Data Store, a central system for internal RDM that fulfills the heterogenous demands of materials science and engineering labs. The BAM Data Store is based on openBIS, an open-source software developed by the ETH Zurich that has originally been created for life science laboratories but that has since been deployed in a variety of research domains. The software offers a browser-based user interface for the digital representation of lab inventory entities (e.g., samples, chemicals, instruments, and protocols) and an electronic lab notebook for the standardized documentation of experiments and analyses.
To investigate whether openBIS is a suitable framework for the BAM Data Store, we carried out a pilot phase during which five research groups with employees from 16 different BAM divisions were introduced to the software. The pilot groups were chosen to represent a diverse array of domain use cases and RDM requirements (e.g., small vs big data volume, heterogenous vs structured data types) as well as varying levels of prior IT knowledge on the users’ side.
Overall, the results of the pilot phase are promising: While the creation of custom data structures and metadata schemas can be time-intensive and requires the involvement of domain experts, the system offers specific benefits in the form of a simplified documentation and automation of research processes, as well as constituting a basis for data-driven analysis. In this way, heterogeneous research workflows in various materials science research domains could be implemented, from the synthesis and characterization of nanomaterials to the monitoring of engineering structures. In addition to the technical deployment and the development of domain-specific metadata standards, the pilot phase also highlighted the need for suitable institutional infrastructures, processes, and role models. An institute-wide rollout of the BAM Data Store is currently being planned.
The present Table of Standard Atomic Weights (TSAW) of the elements is perhaps one of the most familiar data sets in science. Unlike most parameters in physical science whose values and uncertainties are evaluated using the “Guide to the Expression of Uncertainty in Measurement” (GUM), the majority of standard atomic weight values and their uncertainties are consensus values, not GUM-evaluated values. The Commission on Isotopic Abundances and Atomic Weights of the International Union of Pure and Applied Chemistry (IUPAC) regularly evaluates the literature for new isotopic-abundance measurements that can lead to revised standard atomic-weight values, Ar(E) for element E.
The Commission strives to provide utmost clarity in products it disseminates, namely the TSAW and the Table of Isotopic Compositions of the Elements (TICE). In 2016, the Commission recognized that a guideline recommending the expression of uncertainty listed in parentheses following the standard atomic-weight value, for example, Ar(Se) = 78.971(8), did not agree with the GUM, which suggests that this parenthetic notation be reserved to express standard uncertainty, not the expanded uncertainty used in the TSAW and TICE. In 2017, to eliminate this noncompliance with the GUM, a new format was adopted in which the uncertainty value is specified by the “±” symbol, for example, Ar(Se) = 78.971 ± 0.008. To clarify the definition of uncertainty, a new footnote has been added to the TSAW. This footnote emphasizes that an atomic-weight uncertainty is a consensus (decisional) uncertainty. Not only has the Commission shielded users of the TSAW and TICE from unreliable measurements that appear in the literature as a result of unduly small uncertainties, but the aim of IUPAC has been fulfilled by which any scientist, taking any natural sample from commerce or research, can expect the sample atomic weight to lie within Ar(E) ± its uncertainty almost all of the time.
11 laser printers from 5 manufacturers were purchased in 2017 and tested for their UFP emissions. Size resolved sampling of the emitted particles was done with a 13 stage (30 nm to 10 µm) low pressure cascade impactor. The sampled particles were analysed for their chemical composition by thermal extraction (vaporization at 290°C) followed by GC-MS analysis. High boiling cyclic siloxanes (D10 to D16) were detected as constituents of UFP from laser printers. In comparison to measurements in 2008, aliphatic long-chain alkanes (C22 to C34) were detected additionally as chemical constituents of UFP from most of the tested printers and their amounts were higher than for cyclic siloxanes. Printers of one manufacturer showed very low UPF emissions compared to the other manufacturers.
Inductively coupled plasma-mass spectrometry (ICP-MS) is a well-established analytical method offering high sensitivity and multi-element analysis. ICP-MS has found acceptance in various application areas ranging from material analysis to applications in the life sciences. Within the last 15 years new strategies for the sensitive detection and accurate quantification of biomolecules in complex biomedical samples have been developed. Recent instrumental improvements have contributed to this progress.
As most of the biomolecules do not contain endogenous metals etectable with ICP-MS, bioconjugation with artificial metal-containing tags based on metal-loaded chelate complexes or nanoparticles is increasingly applied to determine biomolecules indirectly. Especially, the combination of immunohistochemical workflows using lanthanoid-tagged antibodies and ICP-MS detection provides new insights in the complexity and interdependency of cellular processes. Single-cell ICP-MS, also termed as mass cytometry, allows high-dimensional analysis of biomarkers in cell populations at single-cell resolution. For that purpose, lanthanoid isotope labelled antibodies are used to detect their corresponding target molecules. The visualisation of the elemental distribution is possible with laser ablation ICP-MS (LA-ICPMS) at high spatial resolution. Especially, the combination of LA with ICP time-of-flight mass spectrometry, also referred to as imaging mass cytometry (IMC), opens new possibilities for multiparametric tissue imaging at the single-cell level and even below. The lanthanoid localisation and concentration can be linked to their conjugated antibody target providing valuable information about surface markers, intracellular signalling molecules to measure biological function, and the network state of an individual cell in a tissue.
This book chapter focuses on new applications, where the multi-element capabilities of ICP-MS are used for the detection of lanthanoids applied as artificial elemental stains or tags for biomolecules and in particular antibodies.
Per- and polyfluorinated alkyl substances (PFASs) are a substance class of over 4730 individual compounds. Several PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their different chemical and physical properties as well as the high number of target substances. Target-based approaches (e.g., LC-MS/MS) are limited to the availability of analytical grade standards and are not suitable for the analysis of new/unknown PFASs and transformation products. Therefore, PFAS sum parameter methods become increasingly important to indicate a realistic PFAS pollution level.
PFAS sum parameters compromise the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. High resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for indirect fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification of c(F) 2.7 µg/L.
Here, we describe a fast and simple extraction method for the determination of the EOF using HR-CS-GFMAS in soil samples. Common approaches for the EOF determination use solid phase extraction (SPE). To omit the bias of this time consuming and expensive step we optimized a fast and simple SPE-free extraction method. The developed extraction method consists of a liquid-solid extraction using acidified methanol. Comparison of the method with and without an SPE clean-up step revealed a drastic underestimation of EOF concentrations using SPE. In the next step, the applicability of our method was tested for other solid matrices. In view of steadily increasing numbers of PFASs, our method will make an important contribution in assessing the pollution situation as well as support policy makers in deriving exposure limits for PFASs in the future.
Thermographic non-destructive testing is based on the interaction of thermal waves with inhomogeneities. The propagation of thermal waves from the heat source to the inhomogeneity and to the detection surface according to the thermal diffusion equation leads to the fact that two closely spaced defects can be incorrectly detected as one defect in the measured thermogram. In order to break this spatial resolution limit (super resolution), the combination of spatially structured heating and numerical methods of compressed sensing can be used. The improvement of the spatial resolution for defect detection then depends in the classical sense directly on the number of measurements. Current practical implementations of this super resolution detection still suffer from long measurement times, since not only the achievable resolution depends on performing multiple measurements, but due to the use of single spot laser sources or laser arrays with low pixel count, also the scanning process itself is quite slow. With the application of most recent high-power digital micromirror device (DMD) based laser projector technology this issue can now be overcome.
Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. The growing diversity of construction and demolition waste is leading to increasing difficulties in separating the individual materials. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions.
A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) and visual (VIS)/ near-infrared (NIR) spectroscopy. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.). Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic/technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.
First LIBS measurements show promising results in distinguishing various material types. A meaningful validation shall be achieved with further practical samples. Future works will investigate the combination of LIBS and VIS/NIR spectroscopy in a fully automated measurement setup with conveyor belt speeds of 3 m/s.
11 laser printers from 5 manufacturers were purchased in 2017 and tested for their UFP emissions. Size resolved sampling of the emitted particles was done with a 13 stage (30 nm to 10 µm) low pressure cascade impactor. The sampled particles were analysed for their chemical composition by thermal extraction (vaporization at 290°C) followed by GC-MS analysis. High boiling cyclic siloxanes (D10 to D16) were detected as constituents of UFP from laser printers. In comparison to measurements in 2008, aliphatic long-chain alkanes (C22 to C34) were detected additionally as chemical constituents of UFP from most of the tested printers and their amounts were higher than for cyclic siloxanes. Printers of one manufacturer showed very low UPF emissions compared to the other manufacturers.
Catalysts are important components in chemical processes because they lower the activation energy and thus determine the rate, efficiency and selectivity of a chemical reaction. This property plays an important role in many of today’s processes, including the electrochemical splitting of water. Due to the continuous development of catalyst materials, they are becoming more complex, which makes a reliable evaluation of physicochemical properties challenging even for modern analytical measurement techniques and industrial manufacturing.
We present a fast, vacuum-free and non-destructive analytical approach using multi-sample spectroscopic ellipsometry to determine relevant material parameters such as film thickness, porosity and composition of mesoporous IrOx–TiOy films. Mesoporous IrOx–TiOy films were deposited on Si wafers by sol–gel synthesis, varying the composition of the mixed oxide films between 0 and 100 wt%Ir. The ellipsometric modeling is based on an anisotropic Bruggeman effective medium approximation (a-BEMA) to determine the film thickness and volume fraction of the material and pores. The volume fraction of the material was again modeled using a Bruggeman EMA to determine the chemical composition of the materials. The ellipsometric fitting results were compared with complementary methods, such as scanning electron microscopy (SEM), electron probe microanalysis (EPMA) as well as environmental ellipsometric porosimetry (EEP).
Atomically precise gold nanoclusters are a fascinating class of nanomaterials that exhibit molecule-like properties and have outstanding photoluminescence (PL). Their ultrasmall size, molecular chemistry, and biocompatibility make them extremely appealing for selective biomolecule labeling in investigations of biological mechanisms at the cellular and anatomical levels. In this work, we report a simple route to incorporate a preformed Au25 nanocluster into a model bovine serum albumin (BSA) protein. A new approach combining small-angle X-ray scattering and molecular modeling provides a clear localization of a single Au25 within the protein to a cysteine residue on the gold nanocluster surface.
Attaching Au25 to BSA strikingly modifies the PL properties with enhancement and a redshift in the second near-infrared (NIR-II) window. This study paves the way to conrol the design of selective sensitive probes in biomolecules through a ligand-based strategy to enable the optical detection of biomolecules in a cellular environment by live imaging.
Biofilms are ubiquitous in nature and in the man-made environment. Given their harmful effects on human health, an in-depth understanding of biofilms and the monitoring of their formation and growth are important. Particularly relevant for many metabolic processes and survival strategies of biofilms is their extracellular pH. However, most conventional techniques are not suited for minimally invasive pH measurements of living biofilms. Here, a fluorescent nanosensor is presented for ratiometric measurements of pH in biofilms in the range of pH 4.5–9.5 using confocal laser scanning microscopy. The nanosensor consists of biocompatible polystyrene nanoparticles loaded with pH-inert dye Nile Red and is surface functionalized with a pH-responsive fluorescein dye. Its performance was validated by fluorometrically monitoring the time-dependent changes in pH in E. coli biofilms after glucose inoculation at 37 °C and 4 °C. This revealed a temperature-dependent decrease in pH over a 4-h period caused by the acidifying glucose metabolism of E. coli. These studies demonstrate the applicability of this nanosensor to characterize the chemical microenvironment in biofilms with fluorescence methods.
Asymmetrically bridged aroyl-S,N-ketene acetals and aroyl-S,N-ketene acetal multichromophores can be readily synthesized in consecutive three-, four-, or five-component syntheses in good to excellent yields by several successive Suzuki-couplings of aroyl-S,N-ketene acetals and bis(boronic)acid esters. Different aroyl-S,N-ketene acetals as well as linker molecules yield a library of 23 multichromophores with substitution and linker pattern-tunable emission properties. This allows control of different communication pathways between the chromophores and of aggregation-induced emission (AIE) and energy transfer (ET) properties, providing elaborate aggregation-based fluorescence switches.
Laser metal deposition is a rapidly evolving method for additive manufacturing that combines high performance and simplified production routine. Quality of production depends on an instrumental design and operational parameters, which require constant control during the process. In this work, feasibility of using optical spectroscopy as a control method is studied via modeling and experimentally. A simplified thermal model is developed based on the time-dependent diffusion-conduction heat equation and geometrical light collection into detection optics. Intense light emitted by a laser-heated spot moving across a sample surface is collected and processed to yield the temperature and other temperature-related parameters. In the presence of surface defects, the temperature field is distorted in a specific manner that depends on shape and size of the defect. Optical signals produced by such the distorted temperature fields are simulated and verified experimentally using a 3D metal printer and a sample with artificially carved defects. Three quantities are tested as possible metrics for monitoring the process: temperature, integral intensity, and correlation coefficient. The shapes of the simulated signals qualitatively agree with the experimental signals; this allows for a cautious inference that optical spectroscopy can detect surface defects and, possibly, predict their characters, e.g., inner or protruding.
Global supply chains rely on the compliance and safety of their products, processes, and facilities. These vital services (often referred to as ‘quality assurance’ or ‘conformity assessment’ services) are provided by Conformity Assessment Bodies (CABs). This empirical study explores the impact of the COVID-19 pandemic on CABs as well as their response to the resulting challenges. Data was gathered through an online survey among all accredited CABs in Germany, which resulted in 555 valid responses. Taking a resilience perspective, we reveal that CABs were hit hard by the disruptions caused by the pandemic, albeit to different degrees, in part due to their type of services, size, and sectors served. Furthermore, we find that contingency plans do not directly cushion order declines (as the main indicator of the economic impact of the pandemic) but rather indirectly through helping CABs respond more quickly, which in turn mitigates their order declines. However, our results show that contingency plans can also have adverse effects if they hinder flexible reaction to the crisis. The findings of our study help managers and policymakers learn from the COVID-19 pandemic and improve the resilience of the conformity assessment sector and quality assurance in the event of future crises.
The services of Conformity Assessment Bodies (CABs) are essential to provide for trust in and safety of digital products and services by demonstrating that requirements from standards are met. Thus, it is vital that CABs are ready to fulfil their tasks also in the digital transformation, having the necessary capabilities and resources. Our study is the first to comprehensively assess the digital maturity in the CA industry and to provide some insights into the readiness of the industry to support and at the same time benefit from the digital age. To this end, we developed and implemented a digital maturity model tailored to the CA industry. In this paper, we present first results from our survey among 354 accredited CABs in Germany. With our research we contribute to better understand the digital transformation and maturation of CABs along distinctive stages. The findings suggest that the transformation process in the CA industry is just at the beginning, with the majority of CABs still in early stages of digital maturity. Also, only a few of them already exploit the latest digital technologies and applications like artificial intelligence, blockchain or big data analytics. Nevertheless, CABs regard digitalization as a big
opportunity – for themselves and their industry.
The finite volume method (FVM), like the finite element method (FEM), is a numerical method for determining an approximate solution for partial differential equations. The derivation of the two methods is based on very different considerations, as they have historically evolved from two distinct engineering disciplines, namely solid mechanics and fluid mechanics. This makes FVM difficult to learn for someone familiar with FEM. In this paper we want to show that a slight modification of the FEM procedure leads to an alternative derivation of the FVM. Both numerical methods are starting from the same strong formulation of the problem represented by differential equations, which are only satisfied by their exact solution. For an approximation of the exact solution, the strong formulation must be converted to a so-called weak form. From here on, the two numerical methods differ. By appropriate choice of the trial function and the test function, we can obtain different numerical methods for solving the weak formulation of the problem. While typically in FEM the basis functions of the trial function and test function are identical, in FVM they are chosen differently. In this paper, we show which trial and test function must be chosen to derive the FVM alternatively: The trial function of the FVM is a “shifted” trial function of the FEM, where the nodal points are now located in the middle of an integration interval rather than at the ends. Moreover, the basis functions of the test function are no longer the same as those of the trial function as in the FEM, but are shown to be a constant equal to 1. This is demonstrated by the example of a 1D Poisson equation.
Sound production due to main-flow oriented vorticity-nozzle interaction in absence of a net swirl
(2022)
The downstream acoustic response due to the interaction of main-flow oriented vorticity with a choked nozzle in a swirl-free flow was experimentally demonstrated. The response was obtained by means of impulsive radial air injection in the pipe upstream from the nozzle. The resulting downstream acoustic data are shown to obey a scaling rule that differs, from the one for swirl-nozzle interaction, which according to the literature is proportional to the square of the swirl number. In contrast, here evidence is presented that points to the scaling of main-flow oriented vorticity noise with the cross-sectional average of the square of the transversal velocity at the throat divided by the square of the critical sound speed.
In this study, the concept of a Zero Mass Flow Liner is evaluated. The concept enables impedance control by the induction of periodic bias flow through the perforated facing sheet of the liner. The periodic bias flow is generated by a secondary high amplitude acoustic actuation. By means of the periodic bias flow, the liner can be tuned to different operating points in a given range of grazing flow velocities. The equivalent fluid impedance model for perforated plates is modified to account for the effects of periodic bias flow and grazing flow. An optimization routine, based on a genetic algorithm, is implemented. The method is applicable to any liner concept and uses the impedance of the lined surface as boundary condition in a numerical simulation. Thereby, a set of liner parameters is derived in order to obtain the desired damping characteristics. Based on the results of the optimization, a Zero Mass Flow Liner is manufactured and consequently evaluated experimentally. The damping characteristics are evaluated in form of the dissipated energy along the lined surface. Prediction and measurements show agreement. The Zero Mass
Flow Liner delivers broad band dissipation of high peak value over a range of grazing flow Mach numbers. Under grazing ow conditions, the effect of periodic bias flow is reduced. This poses high energy requirements in high Mach number flow regimes which might restrict the applicability of the Zero Mass Flow concept to grazing flows of low Mach numbers.
Compact NMR Spectroscopy in the field: A Versatile Tool for Automated Continuous-Flow Production
(2022)
Chemical companies must find new paths to successfully survive in a changing environment. The potential of digital technologies belongs to these. Flexible and modular chemical plants can produce various high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce time to market for new products. Intensified continuous production plants allow for difficult to produce compounds.
Therefore, fully automated “chemical” process control along with real-time quality control are prerequisites to such concepts and thus should be based on “chemical” information. A commercially available benchtop NMR spectrometer was integrated to the full requirements of an automated chemical production environment such as, e.g., explosion safety, field communication, and robust evaluation of sensor data. It was thereof used for direct loop advanced process control and real-time optimization of the process. Field studies in modular and conventional production plant setups show promising results gaining process knowledge for further optimization. NMR appeared as preeminent online analytical method and allow using a modular data analysis tool, which even served as reliable reference method for further PAT applications (e.g. NIR spectroscopy). In the future, such fully integrated and intelligently interconnecting “smart” systems and processes can speed up the high-quality production of specialty chemicals and pharmaceuticals.
A new method combining isotope dilution mass spectrometry (IDMS) and standard addition has been developed to determine the mass fractions w of different elements in complex matrices: (a) silicon in aqueous tetramethylammonium hydroxide (TMAH), (b) sulfur in biodiesel fuel, and (c) iron bound to transferrin in human serum. All measurements were carried out using inductively coupled plasma mass spectrometry (ICP–MS). The method requires the gravimetric preparation of several blends (bi)—each consisting of roughly the same masses (mx,i) of the sample solution (x) and my,i of a spike solution (y) plus different masses (mz,i) of a reference solution (z).
Only these masses and the isotope ratios (Rb,i) in the blends and reference and spike solutions have to be measured. The derivation of the underlying equations based on linear regression is presented and compared to a related concept reported by Pagliano and Meija. The uncertainties achievable, e.g., in the case of the Si blank in extremely pure TMAH of urel (w(Si)) = 90% (linear regression method, this work) and urel (w(Si)) = 150% (the method reported by Pagliano and Meija) seem to suggest better applicability of the new method in practical use due to the higher robustness of regression analysis.
Boron isotope fractionation in soil-plant systems and its influence on biogeochemical cycling
(2022)
Boron (B) is an essential mineral nutrient for higher plants. Although B plant nutrition is well studied, the B isotope fractionation at the soil-plant interface, within plant metabolism, and its influence on biogeochemical cycling is not fully understood. Boron concentrations and isotope variations (δ11B) of the dicotyledonous plants of Chenopodium album and Brassica napus and their growing soils along a climatic gradient were analyzed to decipher these unresolved issues of the B behavior. The boron concentrations and δ11B values show an increasing trend from roots to leaves for both plants, while a decreasing trend from flower to shell and to seed for Brassica napus. A large boron isotope fractionation occurs within the plants with median Δ11Bleaf-root ≈ +20‰, which is related to different boron transporters and transportation ways. Formation of borate dimerized rhamnogalacturonan II in cell and B(OH)3 transportation in xylem lead to heavier δ11B values from root to stem and leaf while B(OH)4 transportation in phloem lead to lighter δ11B values from flower to shell and seed. Although samples cover a distinct transect with systematically different climatic conditions, Δδ11B within the individual plant compartments and between the bulk plants and the soil available B do not show any systematic variation.
This suggests that B uptake from the soil into Chenopodium album and Brassica napus occurs without a distinct isotope fractionation at the soil-plant interface (median Δ11Bbulkplant-soil = 0.2‰) and plants are able to regulate boron uptake. Both the observed large B fractionation within plant and low or absent B isotope fractionation at the soil-plant interface may have profound implications for the biological and geological B cycle. If this observed boron behavior also exists in other plants, their litters would be an important source for exporting 11B-rich biological material from continental ecosystems via rivers to the global oceans. This may be helpful for the explanation of ocean B cycle and the increasing δ11B values over the Cenozoic.
Prostate cancer (PCa) is one of the most common cancers in men. For detection and diagnosis of PCa, non-invasive methods, including magnetic resonance imaging (MRI), can reduce the risk potential of surgical intervention. To explore the molecular characteristics of the tumor, we investigated the applicability of ferumoxytol in PCa in a xenograft mouse model in two different tumor volumes, 500 mm3 and 1000 mm3. Macrophages play a key role in tumor progression, and they are able to internalize iron-oxide particles, such as ferumoxytol. When evaluating T2*-weighted sequences on MRI, a significant decrease of signal intensity between pre- and post-contrast images for each tumor volume (n = 14; p < 0.001) was measured. We, furthermore, observed a higher signal loss for a tumor volume of 500 mm3 than for 1000 mm3. These findings were confirmed by histological examinations and laser ablation inductively coupled plasma-mass spectrometry. The 500 mm3 tumors had 1.5% iron content (n = 14; sigma = 1.1), while the 1000 mm3 tumors contained only 0.4% iron (n = 14; sigma = 0.2). In vivo MRI data demonstrated a correlation with the ex vivo data (R2 = 0.75). The results of elemental analysis by inductively coupled plasma-mass spectrometry correlated strongly with the MRI data (R2 = 0.83) (n = 4). Due to its long retention time in the blood, biodegradability, and low toxicity to patients, ferumoxytol has great potential as a contrast agent for visualization PCa.
The residual stresses and load transfer in multiphase metal alloys and their composites (with both random planar-oriented short fibers and particles) will be shown, as studied by neutron diffraction, by X-ray computed tomography, and by a model based on the reformulation of classic Maxwell’s homogenization method.
Contrary to common understanding and state-of-the-art models, we experimentally observe that randomly oriented phases possess non-hydrostatic residual stress. Moreover, we disclose that the unreinforced matrix alloy stays under hydrostatic compression even under external uniaxial compression.
The recently developed modeling approach allows calculating the residual stress in all phases of the composites. It rationalizes the presence of deviatoric stresses accounting for the interaction of random oriented phases with fibers having preferential orientation. It also allows the explanation of the unconventional in-situ behavior of the unreinforced alloy and the prediction of the micromechanical behavior of other similar alloys.
Phosphotyrosine residues are essential functional switches in health and disease. Thus, phosphotyrosine biomimetics are crucial for the development of chemical tools and drug molecules. We report here the discovery and investigation of pentafluorophosphato amino acids as novel phosphotyrosine biomimetics. A mild acidic pentafluorination protocol was developed and two PF5-amino acids were prepared and employed in peptide synthesis. Their structures, reactivities, and fluorine-specific interactions were studied by NMR and IR spectroscopy, X-ray diffraction, and in bioactivity assays. The mono-anionic PF5 motif displayed an amphiphilic character binding to hydrophobic surfaces, to water molecules, and to protein-binding sites, exploiting charge and H−F-bonding interactions. The novel motifs bind 25- to 30-fold stronger to the phosphotyrosine binding site of the protein tyrosine phosphatase PTP1B than the best current biomimetics, as rationalized by computational methods, including molecular dynamics simulations.
Functionalized nanomaterials (NM) with their unique size-dependent properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing, electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties.1 Besides other key parameters, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups and ligands, must be considered for a better performance, stability, and processibility of NM, as well as their interaction with the environment. Thus, particle standards with well-designed surfaces and methods for functional group quantification can foster the sustainable development of functional and safe(r) NM.2 Here we provide a brief overview of the ongoing research in division Biophotonics to design tailored amorphous silica reference particles with bioanalytically relevant functional groups and ligands, for the development of standardized and validated surface functional group quantification methods.
We demonstrate here using a disulfide system the first example of reversible, selective, and quantitative transformation between three crystalline polymorphs by ball mill grinding. This includes the discovery of a previously unknown polymorph. Each polymorph is reproducibly obtained under well-defined neat or liquid-assisted grinding conditions, revealing subtle control over the apparent thermodynamic stability. We discovered that the presence of a contaminant as low as 1.5% mol mol−1 acting as a template is required to enable all these three polymorph transformations. The relative stabilities of the polymorphs are determined by the sizes of the nanocrystals produced under different conditions and by surface interactions with small amounts of added solvent. For the first time, we show evidence that each of the three polymorphs is obtained with a unique and reproducible crystalline size. This mechanochemical approach gives access to bulk quantities of metastable polymorphs that are inaccessible through recrystallisation.
The overall interest in nanotoxicity, triggered by the increasing use of nanomaterials in the material and life sciences, and the synthesis of an ever increasing number of new functional nanoparticles calls not only for standardized test procedures1,2 and for efficient approaches to screen the potential genotoxicity of these materials, but also for standardized and validated methods for surface analysis.
4,5 The analysis and quantification of surface chemistry is hence in the focus of an increasing number of standardization organizations and interlaboratory comparisons with different analytical methods are being done.5 For the monitoring of nanomaterial synthesis and the fast assessment of the number of functional groups such as carboxyl and amino functionalities, which are very commonly used functionalities in the life sciences, simple and validated methods are needed that can be performed with common laboratory instrumentation. 5,6 Here we provide a brief overview of the ongoing research in division Biophotonics employing quantitative NMR (qNMR), conductometry, and colorimetric and fluorometric optical assays for the determination of the total and the accessible number of carboxyl and amino groups on differently sized polymer and silica nano- and microparticles.5-7
The fabrication of laser-generated surface structures on titanium and titanium alloys has recently gained remarkable interests, being technologically relevant for applications in optics, medicine, fluid transport, tribology, and wetting of surfaces. The morphology of these structures, and so their chemistry, is influenced by the different laser processing parameters such as the laser fluence, wavelength, pulse repetition rate, the effective number of laser pulses per beam spot area, etc. A simple way to characterize laser-generated surface structures is by means of optical microscopy (OM) or white light interference microscopy (WLIM). The latter can address the surface topography, while having a lateral resolution limit of ~(lambda)/2 (lambda = illumination wavelength). To resolve morphologies with spatial periods significantly smaller than (lambda)/2, scanning electron microscopy (SEM) is often used, taking benefit of the reduced de Broglie wavelength associated to the electrons of several keV energy. However, all the above-mentioned techniques lack the necessary depth-resolution to reveal and quantify sub-surface material modifications of these laser-generated structures. Time-of-Flight secondary ion mass spectrometry (ToF-SIMS) represents a promising surface analytical technique for studying laser-induced chemical surface alterations since the method combines a high surface sensitivity with the capability to perform a depth-profiling of the laser-affected surface zone. In this study we combine WLIM and high-resolution SEM with ToF-SIMS to fully characterize the evolution of various types of laser-generated micro- and nanostructures formed on Ti-6Al-4V alloys upon irradiation by near infrared ultrashort laser pulses (1030 nm, 925 fs) at different laser fluence levels, effective number of pulses, and at different pulse repetition rates (1 – 400 kHz). We show how this combined surface analytical approach allows to evaluate alterations in the surface chemistry and topography of the laser-generated surface structures depending on the laser processing parameters
Even though we often do not knowingly recognize them, nanoparticles are present these days in most areas of our daily life, including food and its packaging, medicine, pharmaceuticals, cosmetics, pigments as well as electronic products, such as computer screens. The majority of these particles exhibits a core-shell morphology either intendedly or unintendedly. For the purpose of practicability, this core-shell nanoparticle (CSNP) morphology is often assumed to be ideal, namely a spherical core fully encapsulated by a shell of homogeneous thickness with a sharp interface between core and shell material. It is furthermore widely presumed that all nanoparticles in the sample possess the same shell thickness. As a matter of fact, most real CSNPs deviate in several ways from this ideal model with quite often severe impact on how efficiently they perform in a specific application.
The topic of this cumulative PhD thesis is the accurate characterization of the actual morphology of CSNPs by advanced X-ray analytical techniques, namely X-ray photoelectron spectroscopy (XPS) and scanning transmission X-ray microscopy (STXM). A special focus is on CSNPs which deviate from an ideal core-shell morphology. In the paper from 2019 nanoparticle shell thicknesses are extracted from the elastic-peak intensities in an XPS spectrum based on an ideal particle morphology. This happens for a series of CSNP samples comprising a poly(tetrafluoroethylene) (PTFE) core and either a poly(methyl methacrylate) (PMMA) or polystyrene (PS) shell. The same paper as well as the paper from 2020 demonstrate for the first time, that the analysis of the inelastic background in an XPS spectrum of CSNPs can identify and quantify the heterogeneity of the shell and the incomplete encapsulation of the core.
The result from an XPS experiment is always an average across a large nanoparticle ensemble. Deviations from an ideal morphology within a single particle of the sample cannot be assessed separately. As opposed to that, a spatial resolution of 35 nm enables STXM to visualize the interior of single CSNPs which exhibit a sufficient X-ray absorption contrast between core and shell material. In the paper from 2018 a STXM analysis is demonstrated based on the example of the PTFE-PS CSNP samples already mentioned in the previous paragraph.
In the publication from 2021 (Ca/Sr)F₂ core-shell like nanoparticle ensembles for the practical use in, among others, antireflective coatings are investigated. These nanoparticles do not possess a sharp interface between core and shell material, which is why a shell thickness determination as described in the second paragraph is inappropriate. Instead, in-depth profiles of the chemical composition are obtained by XPS experiments based on synchrotron radiation with variable X-ray photon energy to elucidate the internal morphology of the particles. Additionally, theoretical in-depth profiles of Ca and Sr XPS peak intensities are simulated, in order to facilitate the interpretation of the experiments. Thus, an enrichment of CaF₂ at the particle surface was determined, which could hardly have been assessed by any other analytical technique. Because this kind of non-destructive depth profiling by XPS is very demanding, more than usual effort is spent on gapless documentation of the experiments to ensure full reproducibility.
Due to the vast diversity of nanoparticles differing in material, composition and shape, a measurement procedure cannot unalteredly be transferred from one sample to another. Nevertheless, because the papers in this thesis present a greater depth of reporting on the experiments than comparable publications, they constitute an important guidance for other scientists on how to obtain meaningful information about CSNPs from surface analysis.
Here, we present a study on agarose thin-film samples that represent a model system for the exopolysaccharide matrix of biofilms. Povidone-iodide (PVP-I) was selected as an antibacterial agent to evaluate our x-ray photoelectron spectroscopy (XPS)-based methodology to trace specific marker elements, here iodine, commonly found in organic matrices of antibiotics. The in-depth distribution of iodine was determined by XPS analyses with variable excitation energies and in combination with argon gas cluster ion beam sputter cycles. On mixed agarose/PVP-I nanometer-thin films, both methods were found to solve the analytical task and deliver independently comparable results. In the mixed agarose/PVP-I thin film, we found the outermost surface layer depleted in iodine, whereas the iodine is homogeneously distributed in the depth region between this outermost surface layer and the interface between the thin film and the substrate. Depletion of iodine from the uppermost surface in the thin-film samples is assumed to be caused by ultrahigh vacuum exposure resulting in a loss of molecular iodine (I2) as reported earlier for other iodine-doped polymers.
A large and increasing number of scientific domains pushes for high neutron imaging resolution achieved in reasonable times. Here we present the principle, design and performance of a detector based on infinity corrected optics combined with a crystalline Gd3Ga5O12 : Eu scintillator, which provides an isotropic sub-4 μm true resolution. The exposure times are only of a few minutes per image. This is made possible also by the uniquely intense cold neutron flux available at the imaging beamline NeXT-Grenoble. These comparatively rapid acquisitions are compatible with multiple high quality tomographic acquisitions, opening new venues for in-operando testing, as briefly exemplified here.
Morpho-Chemical Characterisation of Me-TiO2 Nanoparticles for Enhanced Photocatalytical Activity
(2022)
The conversion of solar energy into electricity and solar fuels is of crucial importance for a green and sustainable future. Water splitting using semiconductor photo-catalysts is considered a sustainable method to produce clean hydrogen (H2) fuel. Nevertheless, H2 photo-production efficiency remains still low, although extensive research works to understand better the mechanisms of the Hydrogen Evolution Reaction (HER) and the Oxygen Evolution Reaction (OER) are being carried out. In this respect, TiO2 is a key photoactive material, usually employed with a co-catalyst deposited onto the surface to enhance charge carriers’ separation and catalyze surface charge transfer reactions. The deposition of a co-catalyst on the TiO2 nanoparticle surface represents one successful way to enhance the activity of the photocatalyst through a modification of its surface and redox properties. In this context, high-resolution scanning electron microscopy coupled with elemental analysis by energy-dispersive X-ray spectroscopy (EDS) is fundamental for studying and understanding the effect of the nanoparticle morphology on the functional properties of shape-controlled TiO2 crystals (bipyramides, platelets, and elongated particles). Different types of metal-semiconductor combinations, TiO2 shapes and dopant metals (Ag, Pt, etc) and metal concentrations will be discussed.
microscopy (AFM), or X-ray reflectometry. For the additional determination of thin film composition, techniques like X-ray photoelectron spectroscopy (XPS) or mass spectrometry-based techniques can be used. An alternative non-destructive technique is electron probe microanalysis (EPMA). This method assumes a sample of homogenous (bulk) chemical composition, so that it cannot be usually applied to thin film samples. However, in combination with the thin film software StrataGEM, the thickness as well as the composition of such films on a substrate can be determined.
This has been demonstrated for FeNi on Si and SiGe on Al2O3 film systems. For both systems five samples with different elemental composition and a reference were produced and characterised by Korean research institute KRISS using inductively coupled plasma mass spectrometry (ICP-MS), Rutherford backscattering (RBS), and transmission electron microscopy (TEM). These samples were used for an international round robin test.
In 2021, a new and open-source thin film evaluation programme called BadgerFilm has been released. It can also be used to determine thin film composition and thickness from intensity ratios of the unknown sample and standards (k-ratios).
In this contribution, we re-evaluated the data acquired for the FeNi and SiGe systems using the BadgerFilm software package and compared the resulting composition and thickness with the results of the established StrataGEM software and other reference methods. With the current evaluation, the BadgerFilm software shows good agreement with the composition and thickness calculated by StrataGEM and as the reference values provided by the KRISS.
The recent development of x-ray photoelectron spectroscopy using excitation sources different from the usual lab-source Mg Kα and Al Kα and spectrometers with more sophisticated lens systems requires flexible approaches for determining the transmission function. Therefore, the approach using quantified peak areas (QPA) was refined.1 A new algorithm allows a more precise estimation of the transmission function which could be shown by comparing the results obtained with the new version with former calculations. Furthermore, next to the established reference materials Cu, Ag and Au, ionic liquids can be used for estimating the transmission function at beamlines with variable excitation energies. Comparison between the measured and stoichiometric composition shows that a transmission function was determined which allows a reasonable quantification.
Nanoforms with at least one dimension below 100 nm have an important part to play in more and more areas of our daily life. Therefore, risk assessment of these materials is becoming increasingly important. In this context, the European Chemical Agency (ECHA) considered eleven physico-chemical properties as relevant, of which the following six are essential for the registration: chemical composition, crystallinity, particle size, particle shape, surface chemistry and specific surface area. Four of these priority properties can be obtained with electron microscopy and surface analytics like XPS and ToF-SIMS. The reliability of this data must be ensured, especially for their use for grouping and read across approaches. On the other hand, the “reproducibility” crisis has revealed major shortcomings in the reliability of published data.
In a case study, we show how the quality of the data can be ensured by using existing standards and protocols of each step in the workflow of sample characterization. As exemplary samples, two Al-coated TiO2 samples as nanopowders were selected from the JRC repository, capped either with a hydrophilic or a hydrophobic organic ultrathin shell. SEM results provided the size and shape of the nanoparticles, a first overview about the composition was obtained with EDS. XPS and ToF-SIMS supplied the surface chemistry, especially information about the shell and the coating of the particles. Standards and protocols of all steps of the analytical workflow including preparation and data reduction are discussed regarding reliable and reproducible data. Additionally, uncertainties for the different steps are specified.
Only such a detailed description of all these factors allows a comprehensive physico-chemical characterization of the nanoparticles with understanding of their potential risk assessment.
VAMAS-Enabling international standardisation for increasing the take up of Emerging Materials
(2022)
VAMAS (Versailles Project on Advanced Materials and Standards) supports world trade in products dependent on advanced materials technologies by providing technical basis for harmonized measurements, testing, specification, reference materials and standards. The major tools for fulfilling this task are interlaboratory comparisons (ILC). The organisation structure of VAMAS is presented. It is discussed, how a new technical activity can initiate.
Lifestyle modifications could prevent almost one‑third to one‑half of all cancer cases. The awareness of cancer risk factors could motivate people to make such changes in their behaviors and lifestyles. This work aims to investigate the cancer awareness level in the Pakistani population. Telephone interviews of 657 individuals in Pakistan were carried out using the Cancer Awareness Measure (CAM) and Cancer Awareness Measure–MYthical Causes Scale (CAM‑MY). We observed that participants scored significantly better on the CAM scale than the CAM‑MY scale, and CAM scores were negatively associated with CAM‑MY scores. Years of formal education or a biology major at undergraduate or graduate level did not affect our population’s cancer awareness levels. Age displayed a weak but statistically significant negative association with CAM scores. Most participants failed to identify modifiable cancer risk factors, e.g., low physical activity. Efforts should be made to improve awareness of modifiable risk factors. We observed that brief training sessions could markedly improve people’s understanding of cancer risk factors and myths.
Due to the diffusive nature of heat propagation in solids, the detection and resolution of internal defects with active thermography based non-destructive testing is commonly limited to a defect-depth-to-defect-size ratio greater than or equal to one. In the more recent past, we have already demonstrated that this limitation can be overcome by using a spatially modulated illumination source and photothermal super resolution-based reconstruction. Furthermore, by relying on compressed sensing and computational imaging methods we were able to significantly reduce the experimental complexity to make the method viable for investigating larger regions of interest. In this work we share our progress on improving the defect/inhomogeneity characterization using fully 2D spatially structured illumination patterns instead of scanning with a single laser spot. The experimental approach is based on the repeated blind pseudo-random illumination using modern projector technology and a high-power laser. In the subsequent post-processing, several measurements are then combined by taking advantage of the joint sparsity of the defects within the sample applying 2D-photothermal super resolution reconstruction. Here, enhanced nonlinear convex optimization techniques are utilized for solving the underlying ill-determined inverse problem for typical simple defect geometries. As a result, a higher resolution defect/inhomogeneity map can be obtained at a fraction of the measurement time previously needed.
In the face of rising energy demand and the impending climate change the development of a sustainable, fossil-free fuel and chemical production is of global importance. One possible goal is the development of electrochemical conversion processes using catalysts. Porous materials play an important role in such energy applications. The activity and stability of each catalyst is highly dependent on the properties of the coating, i.e., phase composition, crystallinity, accessible surface area, and many other factors. The key to the development of improved catalysts is a better understanding of the relations between their performance, stability and physico-chemical properties. However, the complex morphology of such catalysts constitutes a challenge even for modern analytical techniques. Spectroscopic ellipsometry (SE) is a versatile method for studying material properties by using appropriate models (e.g., film thickness, optical and electronic properties). Ellipsometric models need to be validated in order to produce accurate results. In a first step, the model for the ellipsometric fit studies of a calcination series of mesoporous iridium oxide films (300 – 600 °C) was investigated and validated with respect to their material properties.[4] The information on electronic structure of the catalysts shows a direct correlation with electrochemical activities. The development of an environmental electrochemical cell offers the possibility of investigations under operando conditions. Thus, changes in optical and electronic properties can be induced and monitored during the electrocatalytic oxygen evolution reaction.
In this work, we present the recent in-situ imaging developments at the BAMline (of synchrotron BESSY II, HZB), focused on the in-situ characterization and understanding of microstructural evolution of additively manufactured materials subjected to different environments. Two show cases are presented. In the first, X-ray refraction radiography (SXRR) was combined with in-situ heat treatment to monitor the microstructural evolution as a function of temperature in a laser powder bed fusion (LPBF) manufactured AlSi10Mg alloy. We show that SXRR allows detecting the changes in the Si-phase morphology upon heating using statistically relevant volumes. SXRR also allows observing the growth of pores (i.e., thermally induced porosity), usually studied via X-ray computed tomography (XCT), but using much smaller fields-of-view. In the second case study, XCT was combined with in-situ tensile test to investigate the damage mechanism in a LPBF Aluminum Metal Matrix Composite (MMC). In-situ SXCT test disclosed the critical role of the defects in the failure mechanism along with pre-cracks in the reinforcement phase of MMC. We found that cracks were initiated from lack-of-fusion defects and propagated through coalescence with other defects.
Hundreds of papyrus rolls, carbonized during the 79CE eruption of Mount Vesuvius, were discovered in 1754 at Herculaneum. Sophisticated mechanical methods for unrolling the best-preserved scrolls have been applied, with varying success. However, such processes have been abandoned, to prevent risk from irremediable damage or loss and to preserve the integrity of the extremely fragile rolls. Following the development of X-ray based non-invasive techniques, attempts to virtually unroll the scrolls were made. The most common ink in Antiquity was carbon-based, and the main element of carbonized papyrus is carbon, making these investigations difficult. However, some attempts with synchrotron X-ray phase-contrast tomography (XPCT) were successful. Recently, the identification of antique inks containing metals raised hope that if some of the inks contain metal the rolls can be virtually unrolled using conventional CT- technique. We investigated the inks of a selection of partially unrolled fragments stored at the Biblioteca Nazionale di Napoli with X-ray fluorescence in order to select the best candidates for tomography. Despite the many difficulties (analysis of several layers sticking together, letters barely visible, difficulty to separate contribution from the ink and from the papyrus, inhomogeneity of the support, fragility of the fragments…), encouraging results were found, with a number of inks from Greek fragments found to contain additions to the soot (Fe, Pb, Cu P).
Per- and polyfluoroalkyl substances (PFAS) are a large group of organofluorine surfactants used in the formulations of thousands of consumer goods, including aqueous film-forming foams (AFFF) used to suppress aviation fires in training scenarios, non-stick cookware, fast-food wrappers, water-repellent fabrics, medical equipment, and plastic and leather products. As a result of the perpetual use of PFAS containing products, effluents and sewage sludge from wastewater treatment plants (WWTPs) have been observed to be an important pathway for PFAS into the environment. In Germany, phosphorus and other nutrients from sewage sludge and wastewater should be recycled in WWTPs of cities with a large population. However, it is not clear if PFAS contamination from wastewater and sewage sludge end up in novel wastewater-based fertilizers. Normally, PFAS are analyzed using PFAS protocols typically with time-consuming extraction steps and LC-MS-MS quantification. However, for screening of PFAS contaminations in sewage sludge or wastewater-based fertilizers also passive sampler based on the Diffusive Gradients in Thin-films (DGT) technique can be used for the PFAS extraction. Afterwards, combustion ion chromatography (CIC) can be applied to analyse the “total” amount of PFAS on the passive sampler. Here, we show results from the DGT method in comparison to those of the extractable organic fluorine (EOF) method for a variety of wastewater-based fertilizers. Additionally, we analysed the adsorption of PFAS on the weak anion exchanger (WAX) based DGT passive sampler binding layer by infrared and fluorine K-edge X-ray adsorption near-edge structure (XANES) spectroscopy.
Equilibrium model of titanium laser induced plasma in air with reverse deposition of titanium oxides
(2022)
A chemical-hydrodynamic model of laser induced plasma is developed to study a process of deposition of titanium oxides from titanium laser induced plasma to the titanium target surface. The model is relevant to texturing and coating of titanium bone implants that is done by scanning the ablation laser across implant surfaces. Such the procedure improves the biocompatibility and durability of the implants. The model considers plasma chemical reactions, formation of condensed species inside the plasma plume, and deposition and accumulation of these species on the ablation surface. A chemical part of the model is based on minimization of Gibbs free energy of the chemical system; it is used to calculate the chemical composition of the plasma. A hydrodynamic part uses the 2D fluid-dynamic equations that model a 3D axisymmetric plasma plume and assumes the mass and energy exchange between the plasma and the surface. The initial parameters for the model are inferred from experiment.
The model shows that condensed titanium oxides, mostly TiO2, form in a peripheral plasma zone and gradually adhere to the surface during the plasma plume evolution. The model predicts the major component and thickness of the deposit and can be applied for the optimization of experiments aimed at surface modification.
The deposition of titanium oxides during titanium laser ablation in air has been experimentally and numerically investigated. A titanium sample was irradiated by nanosecond pulses from an Yb-fber laser with a beam scanned across the sample surface for its texturing. As a result, the hierarchical structure was observed consisting of a microrelief formed by the laser ablation and a nanoporous coating formed by the reverse deposition from the laser induced plasma plume. The chemical and phase composition of the nanoporous coating, as well as the morphology and structure of the surface, were studied using scanning electron microscopy, atomic force microscopy, and X-ray microanalysis. It was found that the deposit consists mostly of porous TiO2 with 26% porosity and inclusions of TiO, Ti2O3, and Ti2O3N. Optical emission spectroscopy was used to control the plasma composition and estimate the effective temperature of plasma plume. The chemical-hydrodynamic model of laser induced plasma was developed to get a deeper insight into the deposition process. The model predicts that condensed titanium oxides, formed in peripheral plasma
zones, gradually accumulate on the surface during the plasma plume evolution. A satisfactory agreement between the experimental and calculated chemical composition of the plasma plume as well as between the experimental and calculated composition and thickness of the deposited film was demonstrated. This allows a cautious conclusion that the formation of condensed oxides in the plasma and their consequent deposition onto the ablation surface are among the key mechanisms of formation of porous surface films.
Following the reviews of atomic-weight determinations and other cognate data in 2015, 2017, 2019 and 2021, the IUPAC (International Union of Pure and Applied Chemistry) Commission on Isotopic Abundances and Atomic Weights (CIAAW) reports changes of standard atomic weights. The symbol Ar(E) was selected for standard atomic weight of an element to distinguish it from the atomic weight of an element E in a specific substance P, designated Ar(E, P). The CIAAW has changed the values of the standard atomic weights of five elements based on recent determinations of terrestrial isotopic abundances:
Ar (argon): from 39.948 ± 0.001 to [39.792, 39.963]
Hf (hafnium): from 178.49 ± 0.02 to 178.486 ± 0.006
Ir (iridium): from 192.217 ± 0.003 to 192.217 ± 0.002
Pb (lead): from 207.2 ± 0.1 to [206.14, 207.94]
Yb (ytterbium): from 173.054 ± 0.005 to 173.045 ± 0.010
The standard atomic weight of argon and lead have changed to an interval to reflect that the natural variation in isotopic composition exceeds the measurement uncertainty of Ar(Ar) and Ar(Pb) in a specific substance. The standard atomic weights and/or the uncertainties of fourteen elements have been changed based on the Atomic Mass Evaluations 2016 and 2020 accomplished under the auspices of the International Union of Pure and Applied Physics (IUPAP). Ar of Ho, Tb, Tm and Y were changed in 2017 and again updated in 2021:
Al (aluminium), 2017: from 26.981 5385 ± 0.000 0007 to 26.981 5384 ± 0.000 0003
Au (gold), 2017: from 196.966 569 ± 0.000 005 to 196.966 570 ± 0.000 004
Co (cobalt), 2017: from 58.933 194 ± 0.000 004 to 58.933 194 ± 0.000 003
F (fluorine), 2021: from 18.998 403 163 ± 0.000 000 006 to 18.998 403 162 ± 0.000 000 005
(Ho (holmium), 2017: from 164.930 33 ± 0.000 02 to 164.930 328 ± 0.000 007)
Ho (holmium), 2021: from 164.930 328 ± 0.000 007 to 164.930 329 ± 0.000 005
Mn (manganese), 2017: from 54.938 044 ± 0.000 003 to 54.938 043 ± 0.000 002
Nb (niobium), 2017: from 92.906 37 ± 0.000 02 to 92.906 37 ± 0.000 01
Pa (protactinium), 2017: from 231.035 88 ± 0.000 02 to 231.035 88 ± 0.000 01
Pr (praseodymium), 2017: from 140.907 66 ± 0.000 02 to 140.907 66 ± 0.000 01
Rh (rhodium), 2017: from 102.905 50 ± 0.000 02 to 102.905 49 ± 0.000 02
Sc (scandium), 2021: from 44.955 908 ± 0.000 005 to 44.955 907 ± 0.000 004
(Tb (terbium), 2017: from 158.925 35 ± 0.000 02 to 158.925 354 ± 0.000 008)
Tb (terbium), 2021: from 158.925 354 ± 0.000 008 to 158.925 354 ± 0.000 007
(Tm (thulium), 2017: from 168.934 22 ± 0.000 02 to 168.934 218 ± 0.000 006)
Tm (thulium), 2021: from 168.934 218 ± 0.000 006 to 168.934 219 ± 0.000 005
(Y (yttrium), 2017: from 88.905 84 ± 0.000 02 to 88.905 84 ± 0.000 01)
Y (yttrium), 2021: from 88.905 84 ± 0.000 01 to 88.905 838 ± 0.000 002
Anear-infrared (NIR) light-triggered release method for nitric oxide (NO) was developed utilizing core/shell NaYF4: Tm/Yb/Ca@NaGdF4:Nd/Yb up-conversion nanoparticles (UCNPs) bearing a mesoporous silica (mSiO2) shell loaded with theNOdonor S-nitroso-N-acetyl-DL-penicillamine (SNAP). To avoid overheating in biological samples, Nd3+ was chosen as a sensitizer, Yb3+ ions as the bridging sensitizer, andTm3+ ions as UV-emissive activator while co-doping with Ca2+ was done to enhance the luminescence of the activatorTm3+.NOrelease from SNAP was triggered by an NIR-UV up-conversion process, initiated by 808nmlight absorbed by the Nd3+ ions.NOrelease was confirmed by the Griess method. Under 808nmirradiation, the viability of the liver cancer cell line HepG2 significantly decreased with increasing UCNPs@mSiO2-SNAP concentration. For a UCNPs@mSiO2-SNAP concentration of 200 μgml−1, the cell survival probability was 47%. These results demonstrate that UCNPs@mSiO2-SNAP can induce the release of apoptosis-inducingNOby NIR irradiation.
For more than 110 years, BAM has been producing reference materials for a wide range of application fields. With the development of new analytical methods and new applications as well as continuously emerging more stringent requirements of laboratory accreditation with regard to quality control and metrological traceability, the demand and requirements for reference materials are increasing. This trend article gives an overview of general developments in the field of reference materials as well as developments in selected fields of application in which BAM is active. This includes inorganic and metal analysis, gas analysis, food and consumer products, and geological samples. In addition to these more traditional fields of application, developments in the areas of optical spectroscopy, particulary fluorescence methods, and nanomaterials are considered.
Thermographic photothermal super resolution reconstruction enables the resolution of internal defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. Based on a combination of the application of special sampling strategies and a subsequent numerical optimization step in post-processing, thermographic super resolution has already proven to be superior to standard thermographic methods in the detection of one-dimensional defect/inhomogeneity structures. In our work, we report an extension of the capabilities of the method for efficient detection and resolution of defect cross sections with fully two-dimensional structured laser-based heating. The reconstruction is carried out using one of two different algorithms that are proposed within this work. Both algorithms utilize the combination of several coherent measurements using convex optimization and exploit the sparse nature of defects/inhomogeneities as is typical for most nondestructive testing scenarios. Finally, the performance of each algorithm is rated on reconstruction quality and algorithmic complexity. The presented experimental approach is based on repeated spatially structured heating by a high power laser. As a result, a two-dimensional sparse defect/inhomogeneity map can be obtained. In addition, the obtained results are compared with those of conventional thermographic inspection methods that make use of homogeneous illumination. Due to the sparse nature of the reconstructed defect/inhomogeneity map, this comparison is performed qualitatively.
An experimental cold-gas study of the response of a choked convergent–divergent nozzle to swirl perturbations is presented. The perturbations were obtained by means of upstream unsteady tangential injections into initially steady flows with different values of steady background swirl. The swirl perturbations induced changes in the axial mass-flow rate, due to either their ingestion or evacuation by the nozzle. This in turn caused a downstream acoustic response. For low-intensity background swirl the responses were found to be similar to those obtained without steady background swirl. Perturbations of a high-intensity background swirl led to different effects. For long injection times, the negative mass-flow rate modulation occurred in two stages. The first stage was similar to that of the background-swirl free case. The second stage occurred after a short time delay, and induced a much stronger negative acoustic response. This unexpected behavior suggests that a significant part of the tangentially injected fluid flows upstream inducing an accumulation of swirl, which is – after tangential injection is ceased – suddenly cleared out through the nozzle. A scaling rule for the amplitudes of these acoustic responses is reported. Furthermore, quasi-steady models, based on steady-state measurements are proposed. These models predict the downstream acoustic response amplitude within a factor two. Additionally, preliminary empirical evidence of the effect of swirl on the downstream acoustic response due to the interaction of entropy patches with a choked nozzle is reported. This was obtained by comparison of sound produced by abrupt radial or tangential sonic injection, upstream from the choked nozzle, of air from a reservoir at room temperature to that from a reservoir with a higher stagnation temperature. Because the mass flow through the nozzle does not increase instantaneously, the injected higher-enthalpy air accumulates upstream of the injection-port position in the main flow. This eventually induces a large downstream acoustic pulse when tangential injection is interrupted. The magnitude of the resulting sound pulse can reach that of a quasi-steady response of the nozzle to a large air patch with a uniform stagnation temperature equal to that of the upstream-injected heated air. This hypothesis is consistent with the fact that the initial indirect-sound pulse is identical to one obtained with unheated air injection. The authors posit that – given all of the insight gleaned from them in this case – acoustic measurements of indirect sound appear to be a potentially useful diagnostic tool.
Core–shell nanoparticles have attracted much attention in recent years due to their unique properties and their increasing importance in many technological and consumer products. However, the chemistry of nanoparticles is still rarely investigated in comparison to their size and morphology. In this review, the possibilities, limits, and challenges of X-ray photoelectron spectroscopy (XPS) for obtaining more insights into the composition, thickness, and homogeneity of nanoparticle coatings are discussed with four examples: CdSe/CdS quantum dots with a thick coating and a small core; NaYF4-based upconverting nanoparticles with a large Yb-doped core and a thin Er-doped coating; and two types of polymer nanoparticles with a poly(tetrafluoroethylene) core with either a poly(methyl methacrylate) or polystyrene coating. Different approaches for calculating the thickness of the coating are presented, like a simple numerical modelling or a more complex simulation of the photoelectron peaks. Additionally, modelling of the XPS background for the investigation of coating is discussed. Furthermore, the new possibilities to measure with varying excitation energies or with hard-energy X-ray sources (hard-energy X-ray photoelectron spectroscopy) are described. A discussion about the sources of uncertainty for the determination of the thickness of the coating completes this review.
Iron nitride (Fe3N) and iron carbide (Fe3C) nanoparticles can be prepared via sol−gel synthesis. While sol−gel methods are simple, it can be difficult to control the crystalline composition, i.e., to achieve a Rietveld-pure product. In a previous in situ synchrotron study of the sol−gel synthesis of Fe3N/Fe3C, we showed that the reaction proceeds as follows:
Fe3O4 → FeOx → Fe3N → Fe3C. There was considerable overlap between the different phases, but we were unable to ascertain whether this was due to the experimental setup (side-on heating of a quartz capillary which could lead to thermal gradients) or whether individual particle reactions proceed at different rates. In this paper, we use in situ wide- and small-angle X-ray scattering (wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS)) to demonstrate that the overlapping phases are indeed due to variable reaction rates. While the initial oxide nanoparticles have a small range of diameters, the size range expands considerably and very rapidly during the oxide−nitride transition. This has implications for the isolation of Rietveld-pure Fe3N, and in an extensive laboratory study, we were indeed unable to isolate phasepure Fe3N. However, we made the surprising discovery that Rietveld-pure Fe3C nanoparticles can be produced at 500 °C with a sufficient furnace dwell time. This is considerably lower than the previous reports of the sol−gel synthesis of Fe3C nanoparticles.
Towards Unbiased Evaluation of Ionization Performance in LC-HRMS Metabolomics Method Development
(2022)
As metabolomics increasingly finds its way from basic science into applied and regulatory environments, analytical demands on nontargeted mass spectrometric detection methods continue to rise. In addition to improved chemical comprehensiveness, current developments aim at enhanced robustness and repeatability to allow long-term, inter-study, and meta-analyses. Comprehensive metabolomics relies on electrospray ionization (ESI) as the most versatile ionization technique, and recent liquid chromatography-high resolution mass spectrometry (LC-HRMS) instrumentation continues to overcome technical limitations that have hindered the adoption of ESI for applications in the past. Still, developing and standardizing nontargeted ESI methods and instrumental setups remains costly in terms of time and required chemicals, as large panels of metabolite standards are needed to reflect biochemical diversity. In this paper, we investigated in how far a nontargeted pilot experiment, consisting only of a few measurements of a test sample dilution series and comprehensive statistical analysis, can replace conventional targeted evaluation procedures. To examine this potential, two instrumental ESI ion source setups were compared, reflecting a common scenario in practical method development. Two types of feature evaluations were performed, (a) summary statistics solely involving feature intensity values, and (b) analyses additionally including chemical interpretation.
Results were compared in detail to a targeted evaluation of a large metabolite standard panel. We reflect on the advantages and shortcomings of both strategies in the context of current harmonization initiatives in the metabolomics field.
A brief introduction is given into our data collection and organization procedure, and why we have settled on the HDF5-based NeXus format for describing experimental data.
The links between NeXus and the SciCat data catalog is also provided, showing how the NeXus metadata is automatically added as searchable metadata in the catalog.
Core-shell (CS) particles have been increasingly used for a wide range of applications due to their unique properties by merging individual characteristics of the core and the shell materials. The functionality of the designed particles is strongly influenced by their surface roughness. Quantitative evaluation of the roughness of CS microparticles is, however, a challenging task for Scanning Electron Microscopy (SEM).
The SEM images contain two-dimensional (2D) information providing contour roughness data only from the projection of the particle in the horizontal plane. This study presents a practical procedure to achieve more information by tilting the sample holder, hence allowing images of different areas of a single particle to be recorded at different orientations under the same view angle. From the analysis of these images, quasi three-dimensional (3D) information is obtained.
Three types of home-made particles were investigated: i) bare polystyrene (PS) particles, ii) PS particles decorated with a first magnetic iron oxide (Fe3O4) nanoparticle shell forming CS microbeads, iii) PS/Fe3O4 particles closed with a second silica (SiO2) shell forming core-shell-shell (CSS) microbeads. A series images of a single particle were taken with stepwise tilted sample holder up to 10° by an SEM with high-resolution and surface sensitive SE-InLens® mode.
A reliable analysis tool has been developed by a script in Python to analyze SEM images automatically and to evaluate profile roughness quantitatively, for individual core-shell microparticles. Image analysis consists of segmentation of the images, identifying contour and the centre of the particle, and extracting the root mean squared roughness value (RMS-RQ) of the contour profile from the particle projection within a few seconds.
The variation in roughness from batch-to-batch was determined with the purpose to set the method as a routine quality check procedure. Flow cytometry measurements provided complementary data. Measurement uncertainties associated to various particle orientations were also estimated.
Mass spectrometry-based proteomics provides a holistic snapshot of the entire protein set of living cells on a molecular level. Currently, only a few deep learning approaches exist that involve peptide fragmentation spectra, which represent partial sequence information of proteins. Commonly, these approaches lack the ability to characterize less studied or even unknown patterns in spectra because of their use of explicit domain knowledge. Here, to elevate unrestricted learning from spectra, we introduce ‘ad hoc learning of fragmentation’ (AHLF), a deep learning model that is end-to-end trained on 19.2 million spectra from several phosphoproteomic datasets. AHLF is interpretable, and we show that peak-level feature importance values and pairwise interactions between peaks are in line with corresponding peptide fragments. We demonstrate our approach by detecting post-translational modifications, specifically protein phosphorylation based on only the fragmentation spectrum without a database search. AHLF increases the area under the receiver operating characteristic curve (AUC) by an average of 9.4% on recent phosphoproteomic data compared with the current state of the art on this task. Furthermore, use of AHLF in rescoring search results increases the number of phosphopeptide identifications by a margin of up to 15.1% at a constant false discovery rate. To show the broad applicability of AHLF, we use transfer learning to also detect cross-linked peptides, as used in protein structure analysis, with an AUC of up to 94%.
Hundreds of papyrus rolls, carbonized during the 79CE eruption of Mount Vesuvius, were discovered in 1754 at Herculaneum. Sophisticated mechanical methods for unrolling the best-preserved scrolls have been applied, with varying success. However, such processes have been abandoned, to prevent risk from irremediable damage or loss and to preserve the integrity of the extremely fragile rolls. Following the development of X-ray based non-invasive techniques, attempts to virtually unroll the scrolls were made. The most common ink in Antiquity was carbon-based, and the main element of carbonized papyrus is carbon, making these investigations difficult. However, some attempts with synchrotron X-ray phase-contrast tomography (XPCT) were successful. Recently, the identification of antique inks containing metals raised hope that if some of the inks contain metal the rolls can be virtually unrolled using conventional CT- technique. We investigated the inks of a selection of partially unrolled fragments stored at the Biblioteca Nazionale di Napoli with X-ray fluorescence in order to select the best candidates for tomography. Despite the many difficulties (analysis of several layers sticking together, letters barely visible, difficulty to separate contribution from the ink and from the papyrus, inhomogeneity of the support, fragility of the fragments…), encouraging results were found, with a number of inks from Greek fragments found to contain additions to the soot (Fe, Pb, Cu P).
Background Due to physical coupling between mechanical stress and magnetization in ferromagnetic materials, it is assumed in the literature that the distribution of the magnetic stray field corresponds to the internal (residual) stress of the specimen.
The correlation is, however, not trivial, since the magnetic stray field is also influenced by the microstructure and the geometry of component. The understanding of the correlation between residual stress and magnetic stray field could help to evaluate the integrity of welded components.
Objective This study aims at understanding the possible correlation of subsurface and bulk residual stress with magnetic stray field in a low carbon steel weld. Methods The residual stress was determined by synchrotron X-ray diffraction (SXRD, subsurface region) and by neutron diffraction (ND, bulk region). SXRD possesses a higher spatial resolution than ND. Magnetic stray fields were mapped by utilizing high-spatial-resolution giant magneto resistance (GMR) sensors.
Results The subsurface residual stress overall correlates better with the magnetic stray field distribution than the bulk stress.
This correlation is especially visible in the regions outside the heat affected zone, where the influence of the microstructural features is less pronounced but steep residual stress gradients are present.
Conclusions It was demonstrated that the localized stray field sources without any obvious microstructural variations are associated with steep stress gradients. The good correlation between subsurface residual stress and magnetic signal indicates that the source of the magnetic stray fields is to be found in the range of the penetration depth of the SXRD measurements.
Changes in the global bulk and local structures, of three different barium compounds (BaZrO3, BaF2, and BaFCl),were induced by mechanical milling and followed using X-ray powder diffraction (PXRD), subsequent microstructure analysis, and 137Ba solid state NMR spectroscopy. Harder materials like BaZrO3 experience significantly higher structural changes upon milling than softer materials like BaF2. Moreover, soft materials with layered structures, like BaFCl, show a pronounced structural change during the milling process. By combining PXRD and solid state NMR, detailed information on the changes to the global and local structures were obtained, which are of interest for mechanochemical synthesis, mechanically treated catalysts or ionic conductors.
MALDI-TOF-MS-Based Identification of Monoclonal Murine Anti-SARS-CoV-2 Antibodies within One Hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
The dataset presented contains ultrasonic data recorded in pulse echo mode. The investigated specimen is made of the isotropic homogeneous material polyamide and has a drill hole of constant diameter running parallel to the surface, which was scanned in a point grid using an automatic scanner system. At each measuring position, a pitch-catch measurement was performed using a sampling rate of 2 MHz. The probes used are arrays consisting of a spatially separated receiving and in-phase transmitting unit. The transmitting and receiving sides each consist of 12 point-shaped single probes. These dry-point contact (DPC) probes operate according to the piezoelectric principle at nominal frequencies of 55 kHz (shear waves) and 100 kHz (longitudinal waves), respectively, and do not require a coupling medium. The measurements are performed with longitudinal (100 kHz) and transverse (55 kHz) waves with different geometric orientations of the probe on the measurement surface. The data presented in the article provide a valid source for evaluating reconstruction algorithms for imaging in the low-frequency ultrasound range.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer‐based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented
algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Natural zeolite clinoptilolite CLIN with a framework ratio of Si/Al ≥ 4 containing mainly potassium and calcium ions in its internal channel system was used as a starting material. The acidic HCLIN catalysts were prepared under soft conditions avoiding the use of environmental less benign mineral acids. The starting material was ion exchanged using a 0.2 M aqueous ammonium nitrate solution at a temperature 80 ◦C for 2 h. The obtained NH4CLIN was converted into the acid HCLIN catalyst by calcination at 300–600 ◦C. The obtained samples were characterized by XRD, FTIR, SEM/TEM, AAS, and EDX element mapping. The state of aluminium and silicon was studied by 27Al- and 29SiMAS NMR spectroscopy. The textural properties of the catalysts were investigated by nitrogen adsorption and desorption measurements. The Brønsted acidity of the HCLIN catalysts was studied by temperature-programmed decomposition of the exchanged ammonium ions releasing ammonia as well as 1H MAS NMR, {1H–27Al} Trapdor, and {1H–27Al}
Redor experiments. The strongly agglomerated samples were crystalline and thermally stable up to >500 ◦C. Although a part of the clinoptilolite framework is maintained up to 600 ◦C, a loss of crystallinity is already observed starting from 450 ◦C. The specific surface areas of the starting CLIN and ammonium exchanged NH4CLIN are low with ca. 26 m2/g. The pores are nearly blocked by the exchangeable cations located in the zeolite pores. The thermal decomposition of the ammonium ions by calcination at 400 ◦C causes an opening of the pore entrances and a markable increase in the specific micropore area and micropore volume to ca. 163 m2/g and 0.07 cm3/g, respectively. It decreases with further rising calcination temperature indicating some structural loss. The catalysts show a broad distribution of Brønsted acid sites (BS) ranging from weak to strong sites as indicated the
thermal decomposition of exchanged ammonium ions (TPDA). The ammonium ion decomposition leaving BS, i.e., H+ located at Al–O–Si framework bridges, starts at ≥250 ◦C. A part of the Brønsted sites is lost after calcination specifically at 500 ◦C. It is related to the formation of penta-coordinated aluminium at the expense of tetrahedral framework aluminium. The Brønsted sites are partially recreated after repeated ammonium ion exchange. The catalytic performance of the acidic HCLIN
catalysts was tested in the etherification of glycerol as a green renewable resource with different C1 -C4 alcohols. The catalysts are highly active in the etherification of glycerol, especially with alcohols containing the branched, tertiary alkyl groups. Highest activity is observed with the soft activated catalyst HCLIN300 (300 ◦C, temperature holding time: 1 min). A total of 78% conversion of glycerol to mono and di ether were achieved with tert-butanol at 140 ◦C after 4 h of reaction.
The mono- and di-ether selectivity were 75% and 25%, respectively. The catalyst can be reused.
Objectives: Using a murine model of multiple sclerosis, we previously showed that repeated administration of gadopentetate dimeglumine led to retention of gadolinium (Gd) within cerebellar structures and that this process was enhanced with inflammation. This study aimed to compare the kinetics and retention profiles of Gd in inflamed and healthy brains after application of the macrocyclic Gd-based contrast agent (GBCA) gadobutrol or the linear GBCA gadopentetate. Moreover, potential Gd-induced neurotoxicity was investigated in living hippocampal slices ex vivo.
Materials and Methods: Mice at peak of experimental autoimmune encephalomyelitis (EAE; n = 29) and healthy control mice (HC; n = 24) were exposed to a cumulative dose of 20 mmol/kg bodyweight of either gadopentetate dimeglumine or gadobutrol (8 injections of 2.5 mmol/kg over 10 days). Magnetic resonance imaging (7 T) was performed at baseline as well as at day 1, 10, and 40 post final injection (pfi) of GBCAs. Mice were sacrificed after magnetic resonance imaging and brain and blood Gd content was assessed by laser ablation-inductively coupled plasma (ICP)-mass spectrometry (MS) and ICP-MS, respectively. In addition, using chronic organotypic hippocampal slice cultures, Gd-induced neurotoxicity was addressed in living brain tissue ex vivo, both under control or inflammatory (tumor necrosis factor α [TNF-α] at 50 ng/μL) conditions.
Results: Neuroinflammation promoted a significant decrease in T1 relaxation times after multiple injections of both GBCAs as shown by quantitative T1 mapping of EAE brains compared with HC. This corresponded to higher Gd retention within the EAE brains at 1, 10, and 40 days pfi as determined by laser ablation-ICP-MS. In inflamed cerebellum, in particular in the deep cerebellar nuclei (CN), elevated Gd retention was observed until day 40 after last gadopentetate application (CN: EAE vs HC, 55.06 ± 0.16 μM vs 30.44 ± 4.43 μM). In contrast, gadobutrol application led to a rather diffuse Gd content in the inflamed brains, which strongly diminished until day 40 (CN: EAE vs HC, 0.38 ± 0.08 μM vs 0.17 ± 0.03 μM). The analysis of cytotoxic effects of both GBCAs using living brain tissue revealed an elevated cell death rate after incubation with gadopentetate but not gadobutrol at 50 mM. The cytotoxic effect due to gadopentetate increased in the presence of the inflammatory mediator TNF-α (with vs without TNF-α, 3.15% ± 1.18% vs 2.17% ± 1.14%; P = 0.0345).
Conclusions: In the EAE model, neuroinflammation promoted increased Gd retention in the brain for both GBCAs. Whereas in the inflamed brains, efficient clearance of macrocyclic gadobutrol during the investigated time period was observed, the Gd retention after application of linear gadopentetate persisted over the entire observational period. Gadopentetate but not gadubutrol appeared to be neurotoxic in an ex vivo paradigm of neuronal inflammation.
Atmospheric pressure plasmas interact in various physical ways with their surroundings. They release heat and generate charge carriers, which leads to two effects. The first effect is the generation of acoustic waves due to heat release, known as the thermoacoustic effect, and the second effect is the perturbation of the resting fluid provoked by the release of charge carriers, called “ionic wind”. The direct connection between the charge carrier production of the discharge arrangement and the surroundings also allows the detection of acoustic waves by tracking the electrical current of the arrangement.
This contribution introduces a multi-fluid model approach to describe the acoustic interaction of atmospheric plasmas. In addition, we present experimental results on commercially available and in-house fabricated discharge arrangements for either emitting or receiving acoustic waves.
Catalysts derived from pyrolysis of metal organic frameworks (MOFs) are promising candidates to replace expensive and scarce platinum-based electrocatalysts commonly used in polymer electrolyte membrane fuel cells. MOFs contain ordered connections between metal centers and organic ligands. They can be pyrolyzed into metal- and nitrogen-doped carbons, which show electrocatalytic activity toward the oxygen reduction reaction (ORR). Furthermore, metal-free heteroatom-doped carbons, such as N-F-Cs, are known for being active as well. Thus, a carbon material with Co-N-F doping could possibly be even more promising as ORR electrocatalyst. Herein, we report the mechanochemical synthesis of two polymorphs of a zeolitic imidazole framework, Co-doped zinc 2-trifluoromethyl-1H-imidazolate (Zn0.9Co0.1(CF3-Im)2). Time-resolved in situ X-ray diffraction studies of the mechanochemical formation revealed a direct conversion of starting materials to the products. Both polymorphs of Zn0.9Co0.1(CF3-Im)2 were pyrolyzed, yielding Co-N-F containing carbons, which are active toward electrochemical ORR.
Formation Mechanism of a Nano-Ring of Bismuth Cations and Mono-Lacunary Keggin-Type Phosphomolybdate
(2022)
A new hetero-bimetallic polyoxometalate (POM) nano-ring was synthesized in a one-pot procedure. The structure consists of tetrameric units containing four bismuth-substituted monolacunary Keggin anions including distorted [BiO8] cubes. The nano-ring is formed via self-assembly from metal precursors in aqueous acidic medium. The compound (NH4)16[(BiPMo11O39)4] ⋅ 22 H2O; (P4Bi4Mo44) was characterized by single-crystal X-ray diffraction, extended X-ray absorption fine structure spectroscopy (EXAFS), Raman spectroscopy, matrix-assisted laser desorption/ionisation-time of flight mass spectrometry (MALDI-TOF), and thermogravimetry/differential scanning calorimetry mass spectrometry (TG-DSC-MS). The formation of the nano-ring in solution was studied by time-resolved in situ small- and wide-angle X-ray scattering (SAXS/WAXS) and in situ EXAFS measurements at the Mo−K and the Bi−L3 edge indicating a two-step process consisting of condensation of Mo-anions and formation of Bi−Mo-units followed by a rapid self-assembly to yield the final tetrameric ring structure.
This article presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super-resolution (SR) imaging. The photothermal SR approach is a well-known technique to overcome the spatial resolution limitation in photothermal imaging by extracting high-frequency spatial components based on the deconvolution with the thermal point spread function (PSF). However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, handcrafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, this article proposes Photothermal-SR-Net, which performs deconvolution by deep unfolding considering the underlying physics. Since defects appear sparsely in materials, our approach includes trained block-sparsity thresholding in each convolutional layer. This enables to super-resolve 2-D thermal images for nondestructive testing (NDT) with a substantially improved convergence rate compared to classic approaches. The performance of the proposed approach is evaluated on various deep unfolding and thresholding approaches. Furthermore, we explored how to increase the reconstruction quality and the computational performance. Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
Lake Magadi, East African Rift Valley, is a hyperalkaline and saline soda lake highly enriched in Na+, K+, CO32–, Cl–, HCO3–, and SiO2 and depleted in Ca2+ and Mg2+, where thick evaporite deposits and siliceous sediments have been forming for 100 000 years. The hydrogeochemistry and the evaporite deposits of soda lakes are subjects of growing interest in paleoclimatology, astrobiology, and planetary sciences. In Lake Magadi, different hydrates of sodium carbonate/bicarbonate and other saline minerals precipitate. The precipitation sequence of these minerals is a key for understanding the hydrochemical evolution, the paleoenvironmental conditions of ancient evaporite deposits, and industrial crystallization. However, accurate determination of the precipitation sequence of these minerals was challenging due to the dependency of the different hydrates on temperature, water activity, pH and pCO2, which could induce phase transformation and secondary mineral precipitation during sample handling. Here, we report a comprehensive methodology applied for monitoring the evaporitic mineral precipitation and hydrochemical evolution of Lake Magadi. Evaporation and mineral precipitations were monitored by using in situ video microscopy and synchrotron X-ray diffraction of acoustically levitated droplets. The mineral patterns were characterized by ex situ Raman spectroscopy, X-ray diffraction, and scanning electron microscopy. Experiments were coupled with thermodynamic models to understand the evaporation and precipitation-driven hydrochemical evolution of brines. Our results closely reproduced the mineral assemblages, patterns, and textural relations observed in the natural setting. Alkaline earth carbonates and fluorite were predicted to precipitate first followed by siliceous sediments. Among the salts, dendritic and acicular trona precipitate first via fractional crystallization─reminiscent of grasslike trona layers of Lake Magadi. Halite/villiaumite, thermonatrite, and sylvite precipitate sequentially after trona from residual brines depleted in HCO3–. The precipitation of these minerals between trona crystals resembles the precipitation process observed in the interstitial brines of the trona layers. Thermonatrite precipitation began after trona equilibrated with the residual brines due to the absence of excess CO2 input. We have shown that evaporation and mineral precipitation are the major drivers for the formation of hyperalkaline, saline, and SiO2-rich brines. The discrepancy between predicted and actual sulfate and phosphate ion concentrations implies the biological cycling of these ions. The combination of different in situ and ex situ methods and modeling is key to understanding the mineral phases, precipitation sequences, and textural relations of modern and ancient evaporite deposits. The synergy of these methods could be applicable in industrial crystallization and natural brines to reconstruct the hydrogeochemical and hydroclimatic conditions of soda lakes, evaporite settings, and potentially soda oceans of early Earth and extraterrestrial planets.
Due to the diffusive nature of heat propagation in solids, the detection and resolution of internal defects with active thermography based non-destructive testing is commonly limited to a defect-depth-to-defect-size ratio greater than or equal to one. In the more recent past, we have already demonstrated that this limitation can be overcome by using a spatially modulated illumination source and photothermal super resolution-based reconstruction. Furthermore, by relying on compressed sensing and computational imaging methods we were able to significantly reduce the experimental complexity to make the method viable for investigating larger regions of interest. In this work we share our progress on improving the defect/inhomogeneity characterization using fully 2D spatially structured illumination patterns instead of scanning with a single laser spot. The experimental approach is based on the repeated blind pseudo-random illumination using modern projector technology and a high-power laser. In the subsequent post-processing, several measurements are then combined by taking advantage of the joint sparsity of the defects within the sample applying 2D-photothermal super resolution reconstruction. Here, enhanced nonlinear convex optimization techniques are utilized for solving the underlying ill-determined inverse problem for typical simple defect geometries. As a result, a higher resolution defect/inhomogeneity map can be obtained at a fraction of the measurement time previously needed.
Additively manufactured (and in particular laser powder bed fused) materials represent a manyfold challenge for the materials scientist and engineer because of their distinctive microstructure. If laser powder bed fusion is used to produce components, the complexity level increases because meso-structures (e.g., overhanging features, surface and internal defects) gain importance. Furthermore, if the main advantage of additive manufacturing, i.e., the freedom of design, is to be fully exploited, and geometrically complex structures, such as lattices, are manufactured, then such structures become meta-materials. This means that the geometry and the materials properties become equally important.
This matryoshka-like (more literary than the dry “multi-scale”) complexity makes the characterization of the residual stress fields by means of diffraction methods so difficult with the current means, that new paradigms are necessary to tackle the challenge.
Indeed, classic open problems acquire an extra layer of difficulty, such that new solutions need to be found and the sometimes-dormant debate needs to be re-opened. Examples include the determination of: a- the unstrained reference: this reference can become location-dependent and needs to be carefully determined; b- the so-called diffraction elastic constants, which becomes immensely challenging since even the single-crystal elastic constants are not known for additively manufactured materials.
On top of this, other problems arise. The determination of the principal axes of stress becomes non-trivial because the hatching strategy sometimes dominates over the sample geometry. Even further, in complex structures, such as lattices, the textbook statement that the strain measurement in six independent directions uniquely identifies the strain tensor becomes simply invalid. The peculiar surface features of additively manufactured materials transform trivial tasks into formidable challenges: the precise alignment of a specimen in a beam or the determination of surface stresses with laboratory X-rays need to be thoroughly re-discussed and lay far from being routine tasks.
In this paper, we will show a few examples of the cases mentioned above. We will demonstrate that sometimes the classic approach works very well, but other times surprising conclusions can be drawn from in-depth studies of the residual stress in additively manufactured materials. In short, we predicate that classic methods cannot be used on additively manufactured materials and structures without a critical evaluation of their validity and application range.
Quality assessment of components produced by metal based additive manufacturing (AM) technologies such as laser powder bed fusion is rising in importance due to the increased use of AM in industrial production. Here, the presence of internal porosity was identified as a limiting factor for the final component quality. The utilization of thermography as an in-situ monitoring technique allows the determination of the part’s thermal history which was found to be connected to the porosity formation [1]. Combining the local thermal information derived from thermography with the porosity information obtained by x-ray micro computed tomography, machine learning algorithms can be utilized to predict the porosity distribution in the part. In this study, a first approach for the prediction of keyhole porosity in a cylindric specimen from AISI 316L stainless steel is presented. It is based on data augmentation using the “SmoteR” algorithm [2] to cure the dataset imbalance and a 1-dimensional convolutional neural network.
[1] C.S. Lough et al., Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared thermal feature porosity probability maps. Journal of Materials Processing Technology, 302, p. 117473 (2022)
https://dx.doi.org/10.1016/j.imatprotec.2021.117473
[2] L. Torgo et al., SMOTE for Regression. Progress in Artificial Intelligence, Chapter 33, p. 378-289 (2013)
https://dx.doi.org/10.1007/978-3-642-40669-0_33
Atmospheric pressure plasmas interact in various physical ways with their surroundings. They release heat and generate charge carriers, which leads to two effects. The first effect is the generation of acoustic waves due to heat release, known as the thermoacoustic effect, and the second effect is the perturbation of the resting fluid provoked by the release of charge carriers, called “ionic wind”. The direct connection between the charge carrier production of the discharge arrangement and the surroundings also allows the detection of acoustic waves by tracking the electrical current of the arrangement.
This contribution introduces a multi-fluid model approach to describe the acoustic interaction of atmospheric plasmas. In addition, we present experimental results on commercially available and in-house fabricated discharge arrangements for either emitting or receiving acoustic waves.
The molecular ruby analogue [Cr(ddpd)2]3+ (ddpd=N,N’-dimethyl-N,N’-dipyridine-2-ylpyridine-2,6-diamine) exhibits near infrared (NIR) emission with a high photoluminescence (PL) quantum yield ΦPL of 11 % and a lifetime of 898 μs in deaerated water at room temperature. While ligand-based control of the photophysical properties has received much attention, influences of the counter anions and microenvironment are still underexplored. In this study, the luminescence properties of the molecular ruby were systematically examined for the counter anions Cl−, Br−, [BF4]−, [PF6]−, [BPh4]−, and [BArF24]− in acetonitrile (MeCN) solution, in crystals, and embedded into polystyrene nanoparticles (PSNP). Stern-Volmer analyses of the oxygen quenching studies in the intensity and lifetime domain showed the highest oxygen sensitivity of the complexes with the counter anions of [BF4]− and [BArF24]−, which also revealed the longest luminescence lifetimes. Embedding [Cr(ddpd)2][PF6]3 in PSNPs and shielding with poly(vinyl alcohol) yields a strongly NIR-emissive oxygen-insensitive material with a record ΦPL of 15.2 % under ambient conditions.
Sensitized triplet-triplet annihilation upconversion (sTTA-UC) mainly relies on precious metal complexes thanks to their high intersystem crossing (ISC) efficiencies, excited state energies, and lifetimes, while complexes of abundant first-row transition metals were only rarely utilized and with often moderate UC quantum yields. [Cr(bpmp)2]3+ (bpmp = 2,6-bis(2-pyridylmethyl)pyridine) containing earth-abundant chromium possesses an absorption band suitable for green light excitation, a doublet excited state energy matching the triplet energy of 9,10-diphenyl anthracene (DPA), a close to millisecond excited state lifetime, and high photostability. Combined ISC and doublet-triplet energy transfer from excited [Cr(bpmp)2]3+ to DPA gives 3DPA with close-to-unity quantum yield. TTA of 3DPA furnishes greento-blue UC with a quantum yield of 12.0 % (close to the theoretical maximum). Sterically less-hindered anthracenes undergo a [4+4] cycloaddition with [Cr(bpmp)2]3+ and green light.