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Hybrid optical measurement technique for detection of defects in epitaxially grown 4H-SiC layers
(2022)
Recent developments in power electronics require the use of new wide bandgap compound semiconductors. Silicon carbide (SiC) is one of the most promising materials for power electronics due to its outstanding properties and commercial availability. Some types of defects in the SiC substrates or homoepitaxial SiC layers can affect the performance of electronic devices in a serious manner or make its operation even impossible. Optical methods such as imaging ellipsometry (IE) and white light interference microscopy (WLIM) were applied for fast and non-contact investigation of defects in the epitaxially grown 12 µm 4H-SiC layers on 4H- SiC substrates.
Ellipsometry enables the investigation of material properties over a broad spectral range. As a fast and non-destructive method, it is widely used in industry for quality assurance. Despite the wide application of ellipsometry and its high industrial relevance there are some material-specific standards and there have been no generally accepted standards dealing with model validation and measurement uncertainties. The first German standard DIN50989-1: 2018 Ellipsometry – Part1: Principles (currently international standard ISO 23131: 2021) marks the beginning of a 6-part standard series for ellipsometry, which was developed under consideration of GUM.
Luminescent semiconductor quantum dots (QDs) are frequently used in the life and material sciences as reporter for bioimaging studies and as active components in devices such as displays, light-emitting diodes, solar cells, and sensors. Increasing concerns regarding the use of toxic elements like cadmium and lead, and hazardous organic solvents during QD synthesis have meanwhile triggered the search for heavy-metal free QDs using green chemistry syntheses methods. Interesting candidates are ternary AgInS2 (AIS) QDs that exhibit broad photoluminescence (PL) bands, large effective Stokes shifts, high PL quantum yields (PL QYs), and long PL lifetimes, which are particularly beneficial for applications such as bioimaging, white light-emitting diodes, and solar concentrators. In addition, these nanomaterials can be prepared in high quality with a microwave-assisted (MW) synthesis in aqueous solution. The homogeneous heat diffusion and instant temperature rise of the MW synthesis enables a better control of QD nucleation and growth and thus increases the batch-to-batch reproducibility. In this study, we systematically explored the MW synthesis of AIS/ZnS QDs by varying parameters such as the order of reagent addition, precursor concentration, and type of stabilizing thiol ligand, and assessed their influence on the optical properties of the resulting AIS/ZnS QDs. Under optimized synthesis conditions, water-soluble AIS/ZnS QDs with a PL QY of 65% and excellent colloidal and long-term stability could be reproducible prepared.
Binary photoluminescent semiconductor nanocrystals (quantum dots, QDs) are one of the best studied fluorescent nanomaterials, and their unique optoelectronic properties paved the road to many applications in (bio)nanophotonics, optoelectronics, and photovoltaics. However, concerns related to their toxic constituents like cadmium or lead and the emerging interest in greener chemistry synthesis approaches hamper their future applicability. Interesting alternatives for some applications like biosensing or bioimaging are heavy-metal-free ternary QDs like AgInS2 (AIS), CuInS2 (CIS), and quaternary QDs such as AIS-ZnS (ZAIS). In this context, we explored the effect of ligand denticity on the organic-to-aqueous phase transfer of oleylamine-stabilized ZAIS QDs with the hydrophilic ligands mercaptopropionic acid (MPA), dihydrolipoic acid (DHLA), and 3-mercapto-2,2-bis(mercaptomethyl)propanoic acid (3MPA), bearing mono-, bi-, and trialkyl thiol groups. Spectroscopic studies of the resulting water-dispersible ZAIS QDs revealed a considerable influence of ligand denticity and ligand-to-QD ratio on the spectral position and width (FWHM; full width at half-maximum) of the photoluminescence (PL) bands, the PL quantum yields (PL QY), and the PL decay kinetics. Thiol capping and phase transfer resulted in a loss in PL by at least a factor of 2. The ligand-induced PL quenching observed particularly for ligands bearing two or three thiol groups was attributed to the facilitated formation of surface-bound disulfides. The best colloidal stability under high dilution conditions was observed for 3MPA.
Introduction:
With the introduction of accurate deep learning predictors, spectral matching applications might experience a renaissance in tandem mass spectrometry (MS/MS) driven proteomics. Deep learning models, e.g., Prosit, predict complete MS/MS spectra from peptide sequences and give the unprecedented ability to accurately predict mass spectra that may arise from any given proteome. However, the amount of spectral data is enormous when querying large search spaces, e.g., metaproteomes composed of many different species.
Current spectral library search software, such as SpectraST, is not equipped to meet run time and memory constraints imposed by such large MS/MS databases, covering several millions of peptide spectrum predictions.
Methods:
Inspired by the fragment index data structure that had been introduced with MSFragger, we implement an efficient peak matching algorithm for computing spectral similarity between query and library spectra. Mistle (Metaproteomic index and spectral library search engine) uses index partitioning and SIMD (Single instruction, multiple data) intrinsics, which greatly improves speed and memory efficiency for searching large spectral libraries. Mistle is written in C++20 and highly parallelized.
Results:
We demonstrate the efficiency of Mistle on two predicted spectral libraries for the lab-assembled microbial communities 9MM and SIHUMIx. Compared to the spectral library search engine SpectraST, Mistle shows a >10-fold runtime improvement and is also faster than msSLASH, which uses locality-sensitive hashing. Although Mistle is slower than MSFragger, Mistle‘s memory footprint is an order of magnitude smaller. Furthermore, we find evidence that the spectral matching approach to predicted libraries identifies peptides with higher precision. Mistle detects peptides not found by database search via MSFragger and in turn uncovers unnoticed false discoveries among their matches.
Conclusion:
In this study, we show that predicted spectral libraries can enhance peptide identification for metaproteomics. Mistle provides the means to efficiently search large-scale spectral libraries, highlighted for the microbiota 9MM and SIHUMIx.
Applying data-driven AI systems makes it possible to extract patterns from given data, generate predictions and helps making decisions. Material research and testing holds a plethora of AI-based applications, for example, for the automatized search and synthesis of new materials, the detection of materials defects, or the prediction of process and materials parameters (inverse problems). However, AI algorithms can often only be as good as the training data from which the corresponding models are learned. Therefore, it is also indispensable to develop measures for the standardization and quality assurance of such data.
For this purpose, we develop and implement methods from transferring data from various sources into a homogeneous data repository with uniform data descriptions. Through the standardization and corresponding machine-readable interfaces, research data can be made usable and reusable for further data analyses. In addition to the technical implementation of integrative platforms, it is crucial that quality-assured research data management is recognized and implemented as an integral part of daily scientific work. Finally, we provide a vision of how the Federal Institute for Materials Research and Testing can benefit from data-driven AI systems. We discuss early applications and take a peek at future research.
Metaproteomics has substantially grown over the past years and supplements other omics approaches by bringing valuable functional information, enabling genotype- phenotype linkages and connections to metabolic outputs. Currently, a wide variety of metaproteomic workflows is available, yet their impact on the results remains to be thoroughly assessed.
Here, we carried out the first community-driven, multi-lab comparison in metaproteomics: the critical assessment of metaproteome investigation (CAMPI) study. Based on well-established workflows, we evaluated the influence of sample preparation, mass spectrometry acquisition, and bioinformatic analysis using two samples: a simplified, lab-assembled human intestinal model and a human fecal sample.
Although bioinformatic pipelines contributed to variability in peptide identification, wet-lab workflows were the most important source of differences between analyses. Overall, these peptide-level differences largely disappeared at the protein group level. Differences were observed between peptide- and protein-centric approaches for the predicted community composition but similar functional profiles were found across workflows.
The CAMPI findings demonstrate the robustness of current metaproteomics research and provide a perspective for future benchmarking studies.
Driven by recent technological advances and the need for improved viral diagnostic applications, mass spectrometry-based proteomics comes into play for detecting viral pathogens accurately and efficiently. However, the lack of specific algorithms and software tools presents a major bottleneck for analyzing data from host-virus samples. For example, accurate species- and strain-level classification of a priori unidentified organisms remains a very challenging task in the setting of large search databases. Another prominent issue is that many existing solutions suffer from the protein inference issue, aggravated because many homologous proteins are present across multiple species. One of the contributing factors is that existing bioinformatic algorithms have been developed mainly for single-species proteomics applications for model organisms or human samples. In addition, a statistically sound framework was lacking to accurately assign peptide identifications to viral taxa. In this presentation, an overview is given on current bioinformatics developments that aim to overcome the above-mentioned issues using algorithmic and statistical methods. The presented methods and software tools aim to provide tailored solutions for both discovery-driven and targeted proteomics for viral diagnostics and taxonomic sample profiling. Furthermore, an outlook is provided on how the bioinformatic developments might serve as a generic toolbox, which can be transferred to other research questions, such as metaproteomics for profiling microbiomes and identifying bacterial pathogens.
Calibration-free methods in laser-induced breakdown spectroscopy, CF LIBS, serve as an alternative to calibration-based LIBS techniques. Their major advantage is the ability for fast chemical analysis in situations where matrix-matched standards are not readily available (as, e.g., in the analysis of biological materials and remote analysis) or amount of samples are limited. Their main applications are in the industry, geology, biology, archeology, and even space exploration. This chapter overviews the principle of operation and performance of CF LIBS techniques.
Protein adsorption at the air–water interface is a serious problem in cryogenic electron microscopy (cryoEM) as it restricts particle orientations in the vitrified ice-film and promotes protein denaturation. To address this issue, the preparation of a graphene-based modified support film for coverage of conventional holey carbon transmission electron microscopy (TEM) grids is presented. The chemical modification of graphene sheets enables the universal covalent anchoring of unmodified proteins via inherent surface-exposed lysine or cysteine residues in a one-step reaction. Langmuir–Blodgett (LB) trough approach is applied for deposition of functionalized graphene sheets onto commercially available holey carbon TEM grids. The application of the modified TEM grids in single particle analysis (SPA) shows high protein binding to the surface of the graphene-based support film. Suitability for high resolution structure determination is confirmed by SPA of apoferritin. Prevention of protein denaturation at the air–water interface and improvement of particle orientations is shown using human 20S proteasome, demonstrating the potential of the support film for structural biology.
Uncertainty quantification of multimodal surface wave inversion using artificial neural networks
(2023)
An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time.
EN 16516 sets specifications for the determination of emissions into indoor air from construction products. Reliable, accurate and International System of Unit (SI)-traceable measurement results of the emissions are the key to consumer protection. Such measurement results can be obtained by using metrologically traceable reference materials. Gas-phase standards of volatile organic compounds (VOCs) in air can be prepared by a variety of dynamic methods according to the ISO 6145 series. However, these methods are not always applicable for semi-VOCs (SVOCs) due to their high boiling point and low vapour pressure. Therefore, a novel dynamic gas mixture generation system has been developed. With this system gas-phase standards with trace level VOCs and SVOCs in air can be prepared between 10 nmol mol−1 and 1000 nmol mol−1. The VOCs and SVOCs in this study have normal boiling points ranging from 146 °C to 343 °C. Metrologically traceable reference materials of the gas-phase standard were obtained by sampling of the VOC gas-phase standard into Tenax TA® sorbent material in SilcoNert® coated stainless steel tubes. Accurately known masses between 10 ng and 1000 ng per VOC were sampled. These reference materials were used to validate the dynamic system. Furthermore, the storage and stability periods of the VOCs in the reference materials were determined as these are crucial characteristics to obtain accurate and SI-traceable reference materials. In a round robin test (RRT), the reference materials were used with the aim of demonstrating the feasibility of providing SI-traceable standard reference values for SVOCs for interlaboratory comparison purposes. Based on the results from the validation, the storage and stability studies and the RRT, gas-phase standards and reference materials of VOCs and SVOCs with relative expanded uncertainties between 5% and 12% (k = 2) have been developed. These reference standards can be used as calibrants, reference materials or quality control materials for the analysis of VOC emissions.
In order to detect small and hidden material defects or micro-cracks, weak and localized magnetic stray fields need to be detected and characterized on the magnetic surface. Current flux leakage sensor elements are rigid and rely on air gaps to detect stray fields several hundred micrometers above the surface. Furthermore, the increasing complexity of critical components, enabled by novel fabrication technologies, primarily additive manufacturing, poses a significant challenge to the available flux leakage testing technologies.
The emergence of flexible magneto-electronics paves the way to a compliant form of magnetic sensors that, on one hand, are able to adapt to highly curved surfaces, allowing these measurements to be conducted on irregularly formed components, which are inaccessible for nowadays electromagnetic NDT equipment and, on the other hand, could enhance the detection limit for small magnetic stray fields, by allowing the magneto-sensitive elements to approximate the object’s surface until only a few µm, mediated by thin and flexible packaging.
In ultrasonic testing, the time of flight (ToF) of a signal can be used to infer material and structural properties of a test item. In dispersive media, extracting the bulk wave velocity from a received signal is challenging as the waveform changes along its path of propagation. When using signal features such as the first peak or the envelope maximum, the calculated velocity changes with the propagation distance. This does not occur when picking the signal onset. Borrowing from seismology, researchers used the Akaike information criterion (AIC) picker to automatically obtain onset times. In addition to being dependent on arbitrarily set parameters, the AIC picker assumes no prior knowledge of the spectral properties of the signal. This is unnecessary in ultrasonic through-transmission testing, where the signal spectrum is known to differ significantly from noise. In this contribution, a novel parameter-free onset picker is proposed, that is based on a spectral entropy criterion (SEC) to model the signal using the AIC framework. Synthetic and experimental data are used to compare the performance of SEC and AIC pickers, showing an improved accuracy for densely sampled data.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in North Macedonia. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
A certain group of mycotoxins, the ergot alkaloids, has caused countless deaths throughout human history. They are found in rye and other cereals and ingesting contaminated foods can cause serious health problems. To identify contaminated food exceeding the legal limits for ergot alkaloids, a portable and cost-effective test system is of great interest to the food industry. Rapid analysis can be achieved by screening for a marker compound, for which we chose ergometrine. We developed a magnetic bead-based immunoassay for ergometrine with amperometric detection in a flow injection system using a handheld potentiostat and a smartphone. With this assay a limit of detection of 3 nM (1 μg/L) was achieved. In spiked rye flour, ergometrine levels from 25 to 250 μg/kg could be quantified. All results could be verified by optical detection. The developed assay offers great promise to meet the demand for on-site ergometrine detection in the food industry.
Climate change and related energy policies, exacerbated by unforeseen geopolitical developments, pose new challenges for gas analytics, such as the use of hydrogen, hydrogen-containing alternative gaseous fuels (NH3, etc.), the use of alternative methane-based energy gases (LNG, LPG, etc.) or decarbonisation via CCSU. In all topics, the quality, i.e. the actual chemical composition of the gases, naturally plays a decisive role. BAM is meeting this strategic importance with the further development of hydrogen analytics and is continuing to develop the methods used in order to support the German economy and research landscape with traceability, reference materials and analytical procedures as quickly as possible.
Mass spectrometry plays an important role for trace analysis in hydrogen matrix. The presentation shows first experimental results from the application of PTR-TOF-MS (Proton Transfer Reaction Time-of-Flight Mass Spectrometry).
Mycotoxins (toxins formed by fungi) in food and have caused problems for mankind since the beginning of time. The group of ergot alkaloids plays a special role in human history. Several tens of thousands of deaths during the middle ages caused by to ergotism (the disease caused by continuous intake of ergot alkaloid contaminated food) underscore the importance of reliable analytical methods to ensure food safety.
More than 50 compounds belong to the group of ergot alkaloids. The 12 most found structures – the major ergot alkaloids – are typically measured, when it comes to ergot alkaloid quantification. High performance liquid chromatography (HPLC) with a fluorescence detector (FLD) is typically used to quantify the ergot alkaloid content. The main disadvantage of this method are the high costs for calibration standards (12 different calibration substances are required). But also the time and effort required for the analysis of 12 peaks and overlapping signals that occur in complex food samples such as bread. As all ergot alkaloids share the ergoline structure and just differ in the substituents attached to this backbone, measurement of all ergot alkaloids in one sum parameter presents a time and cost saving alternative. The most important step for the development of such a sum parameter method is the reaction used to transfer all ergot alkaloids to one uniform structure. In the talk two promising reactions, the acidic esterification to lysergic acid methyl ester and hydrazinolysis to lysergic acid hydrazide, are examined for possible use in a routine analysis method. In addition to yield and reaction rate, factor such as the handling of the reaction and the possibility of parallelization play a role. Next to the current status of the ongoing research project, in this talk, current approaches to ergot alkaloid quantitation will be discussed.
The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. The integration of data obtained from pulse echo immersion ultrasound testing and radiography holds immense potential to help improve the reliability of non-destructive evaluation. In this study, distinctive features obtained from single techniques, traditional ultrasonic pulse echo testing, and radiography, as well as fused images, were investigated and the suitability of these distinctive features and fusion techniques for improving the probability of defect detection was evaluated. For this purpose, aluminum single lap joints with brass inclusions were analyzed using ultrasound pulse echo and radiography techniques. The distinctive features were extracted from the data obtained, and images of features obtained by both techniques were fused together. Different combinations of features and fusion algorithms were investigated, considering the desire to automate data evaluation in the future.
Validation of novel ultrasonic phased array borehole probe by using simulation and measurement
(2022)
Low-frequency ultrasonic testing is a well-established non-destructive testing (NDT) method in civil engineering for material characterization and the localization of cracks, reinforcing bars and delamination. A novel ultrasonic borehole probe is developed for in situ quality assurance of sealing structures in radioactive waste repositories using existing research boreholes. The aim is to examine the sealing structures made of salt concrete for any possible cracks and delamination and to localize built-in components. A prototype has been developed using 12 individual horizontal dry point contact (DPC) shear wave transducers separated by equidistant transmitter/receiver arrays. The probe is equipped with a commercially available portable ultrasonic flaw detector used in the NDT civil engineering industry. To increase the sound pressure generated, the number of transducers in the novel probe is increased to 32 transducers. In addition, the timed excitation of each transducer directs a focused beam of sound to a specific angle and distance based on the previously calculated delay time. This narrows the sensitivity of test volume and improves the signal-to-noise ratio of the received signals. In this paper, the newly designed phased array borehole probe is validated by beam computation in the CIVA software and experimental investigations on a half-cylindrical test specimen to investigate the directional characteristics. In combination with geophysical reconstruction methods, it is expected that an optimised radiation pattern of the probe will improve the signal quality and thus increase the reliability of the imaging results. This is an important consideration for the construction of safe sealing structures for the safe disposal of radioactive or toxic waste.
In this study, we explored the detection of weak bonds (WBs) due to contamination and faulty curing (FC) using linear ultrasound and machine learning. For this purpose, aluminium single-lap adhesive joints containing three variants of bonding quality were investigated: perfect bond, WB due to release agent (RA) contamination, and WB due to FC. The data, according to the deviation of the bonding protocol, were arranged in two groups, creating two datasets: distinct and complete. Each dataset included all bonding conditions (perfect, RA, and FC), although the distinct dataset contained only marginal cases, which were expected to be well separable, whereas the complete dataset included data with minor deviations from the bonding protocol. Pulse-echo C-scan images were acquired for all prepared samples in the immersion tank, and 45 features were initially extracted from the time traces representing each bonding group. The initial data were analysed via a t-test and pairwise correlation analysis to reveal statistically significant features. Then, we performed dimensionality reduction using tree-based, recursive, sequential, and linear discriminant analysis (LDA) feature selectors to explore feature importance and classification accuracy with different feature subsets. Finally, the important features identified with the different feature selectors were fed to support vector machine (SVM) classifiers, and the classification accuracies were compared amongst the different feature subsets. The classification accuracy using a distinct dataset in some cases demonstrated nearly 99% accuracy, indicating that significant bonding protocol deviations could be easily detected. It was demonstrated that classification accuracy increased with the number of features. However, even in the case of the 2D feature space obtained using linear discriminant analysis, the bonding quality classification accuracy remained higher than 84%. The feature subspace reduction with LDA demonstrated sufficient classification accuracy and an improvement of nearly 40% in training time compared with that for the initial feature set. Thus, the classical ultrasonic pulse-echo C-scan with an LDA feature transformation and SVM classifier could be used to identify the deviations in the bonding protocol in aluminium single-lap adhesive joints.
Mycotoxins (toxic compounds formed by fungi) in food and feed have caused problems for mankind since the beginning of time. The group of ergot alkaloids plays a special role in human history. Several tens of thousands of deaths during the middle ages caused by to ergotism (the disease caused by continuous intake of ergot alkaloid contaminated food) underscore the importance of reliable analytical methods to ensure food safety.
More than 50 compounds belong to the group of ergot alkaloids. The 12 most found structures – the major ergot alkaloids – are typically measured, when it comes to ergot alkaloid quantification. High performance liquid chromatography (HPLC) with a fluorescence detector (FLD) is typically used to quantify the ergot alkaloid content. The main disadvantage of this method are the high costs for calibration standards (12 different calibration substances are required). But also, the time and effort required for the analysis of 12 peaks and overlapping signals that occur in complex food samples such as bread. As all ergot alkaloids share the ergoline structure and just differ in the substituents attached to this backbone, measurement of all ergot alkaloids in one sum parameter presents a time and cost saving alternative. The most important step for the development of such a sum parameter method is the reaction used to transfer all ergot alkaloids to one uniform structure. Two promising reactions, the acidic esterification to lysergic acid methyl ester and hydrazinolysis to lysergic acid hydrazide, were examined for possible use in a routine analysis method. In addition to yield and reaction rate, factors such as handling of the reaction and the possibility of parallel sample workup play a role.
Investigation of degradation of the aluminum current collector in lithium-ion batteries by GD-OES
(2022)
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
In industrialised countries more than 80% of the time is spent indoors. Products, such as building materials and furniture, emit volatile organic compounds (VOCs), which are therefore ubiquitous in indoor air. VOC in combination may, under certain environmental and occupational conditions, result in reported sensory irritation and health complaints. Emission concentrations can become further elevated in new or refurbished buildings where the rate of air exchange with fresh ambient air may be limited due to improved energy saving aspects. A healthy indoor environment can be achieved by controlling the sources and by eliminating or limiting the release of harmful substances into the air. One way is to use (building) materials proved to be low emitting. Meanwhile, a worldwide network of professional commercial and non-commercial laboratories performing emission tests for the evaluation of products for interior use has been established. Therefore, comparability of test results must be ensured. A laboratory’s proficiency can be proven by internal and external validation measures that both include the application of suitable emission reference materials (ERM). For the emission test chamber procedure according to EN 16516, no artificial ERM is commercially available. The EU-funded EMPIR project MetrIAQ aims to fill this gap by developing new and improved ERMs. The goal is to obtain a material with a reproducible and temporally constant compound release (less than 10% variability over 14 days). Different approaches, such as the impregnation of porous materials, are being tested. The generation as well as results of the most promising materials will be presented.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Croatia. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in the United Kingdom. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
A recent upgrade of key equipment of the BAMline widens its imaging capabilities: shorter scan acquisition times are now possible, in situ and operando studies can now be routinely performed, and different energy spectra can easily be set up. In fact, the upgraded double-multilayer monochromator brings full flexibility by yielding different energy spectra to optimize flux and energy resolution as desired.
Deciphering microbiological influenced corrosion processes on steel with single cell-ICP-ToF-MS
(2022)
Microbiologically influenced corrosion (MIC) is a highly unpredictable process dictated by the environment, microorganisms, and the respective electron source. Interaction pathways between cells and the metal surface remain unclear. The development of this novel single cell-inductively coupled plasma-time of flight-mass spectrometry analytical method and a MIC-specific staining procedure facilitate the investigation of steel-MIC interactions. With this it is possible to analyze the multi-elemental fingerprint of individual cells. The detection method revealed elemental selectivity for the corrosive methanogenic archaeal strain Methanobacterium-affiliated IM1. The interface between material and environmental analysis thus receives special attention, e.g., when considering MIC on solid steel. Hence, the possible uptake of individual elements from different steel samples is investigated. Results showed the cells responded at a single-cell level to the different types of supplemented elements and displayed the abilities to interact with chromium, vanadium, titanium, cobalt, and molybdenum from solid metal surfaces. The information obtained will be used in the future to elucidate underlying mechanisms and develop possible material protection concepts, thus combining modern methods of analytical sciences with materials research.
References.
Geführte Ultraschallwellen sind für die Materialcharakterisierung hervorragend geeignet, da ihr Ausbreitungsverhalten abhängig von den Materialeigenschaften des untersuchten Werkstoffs ist.
Um aus dem messtechnisch ermittelten Ausbreitungsverhalten geführter Ultraschallwellen Rückschlüsse auf die Materialparameter zu ziehen, werden in der aktuellen Forschung verschiedene inverse Methoden diskutiert. Dispersionsabbildungen im Frequenz-Wellenzahl-Bereich repräsentieren das Ausbreitungsverhalten geführter Ultraschallwellen. Maschinelles Lernen und insbesondere Convolutional-Neural-Networks (CNNs) sind eine Möglichkeit der automatisierten inversen Bestimmung der Materialparameter aus den Dispersionsabbildungen.
In diesem Beitrag wird anhand synthetischer Daten gezeigt, wie das Ausbreitungsverhalten von geführten Ultraschallwellen unter Verwendung von CNNs und Dispersionsabbildungen genutzt werden kann, um die elastischen Konstanten einer isotropen plattenförmigen Struktur zu bestimmen. Anhand dieses Beispiels wird das generelle Vorgehen zur Anwendung maschineller neuronaler Lernverfahren aufgezeigt. Hierfür werden die verwendeten Daten analysiert, das Preprocessing erläutert und eine einfache CNN-Architektur gewählt. Im Rahmen der Auswertung wird insbesondere Wert auf die Erklärbarkeit und Zuverlässigkeit des verwendeten CNNs gelegt und so Grenzen und Möglichkeiten aufgezeigt.
In non-destructive testing and structural health monitoring with ultrasonic waves, the quantification of damage in components is one of the main tasks. In many shell-like structures, such as plates, pipes, or laminate components, ultrasonic waves propagate as guided waves. Although guided waves enable the testing of large areas, their multimodal and dispersive properties make it challenging to analyze signals. So, there is a need for more advanced algorithms to handle these properties, especially when reconstructing damage position and geometry.
The reconstruction can be formulated as an inverse problem where the measured signals are fitted with a simulative forward model. Due to the small wavelength of ultrasonic waves, classic forward models based on, e.g., the Finite Element Method are computationally intensive. In contrast, the authors use the semi-analytical Scaled Boundary Finite Element Method (SBFEM) to reduce the computational effort. The SBFEM approximates arbitrary long, undamaged parts of the structure with only a few degrees of freedom.
This contribution summarizes a general inverse procedure based on algorithmic differentiation in combination with the SBFEM. Results are presented for damaged 2D cross-sectional models of waveguides. These results include an analysis of the robustness of the proposed algorithms against noise.
This paper considers an indirect measurement approach to reconstruct a defect in a two-dimensional waveguide model for a non-destructive ultrasonic inspection via derivative-based optimization. The propagation of the mechanical waves is simulated by the scaled boundary finite element method that builds on a semi-analytical approach. The simulated data are then fitted to given data associated with the reflected waves from a defect which is to be reconstructed. For this purpose, we apply an iteratively regularized Gauss-Newton method in combination with algorithmic differentiation to provide the required derivative information accurately and efficiently. We present numerical results for three kinds of defects, namely, a crack, delamination, and corrosion. The objective function and the properties of the reconstruction method are investigated. The examples show that the parameterization of the defect can be reconstructed efficiently as well as robustly in the presence of noise.
In the interest of exploring their potential in the field of single particle analysis, a Microdroplet Generator (MDG) was coupled to an ICP-ToF-MS.
Isotopic Dilution Analysis was also incorporated for the size determination of three different Platinum Nanoparticles samples (50, 63 and 70 nm). The performance of the technique was validated by comparison to traditional size characterization techniques (sp-ICP-ToF-MS, TEM), while the robustness of the technique was proven by incorporating NaCl in the samples’ matrix, up to 100 mg/L.
LIBS is a complementary method to XRF and can detect all elements without the need for vacuum conditions. Automated systems are already commercially available capable of scanning surfaces with a resolution of up to 0.1 mm within a few minutes. In addition to possible applications in R&D, LIBS is also used for practical applications in building materials laboratories and even on-site.
In view of ageing infrastructure facilities, a reliable assessment of the condition of concrete structures is of increasing interest. For concrete structures, the ingress of potential harmful ions is affecting the serviceability and eventually structural performance. Pitting corrosion induced by penetrating chlorides is the dominant deterioration mechanism. Condition assessment based on frequently performed chloride profiling can be useful to identify the extent and evolution of chloride ingress. This could prove to be more economical than extensive repairs, especially for important infrastructure facilities.
Currently the most common procedure for determining the chloride content is wet chemical analysis with standard resolution of 10 mm. The heterogeneity is not considered. LIBS is an economical alternative for determining the chloride content at depth intervals of 1 mm or less. It provides 2D distributions of multiple elements and can locate spots with higher concentrations. The results are directly correlated to the mass of binder and can also be performed on-site with a mobile LIBS-System.
The application of a LIBS-system is presented. Calibration is required for quantitative analysis. Concrete cores were drilled, sliced and analyzed to determine the 2D-distribution of harmful elements. By comparing the chloride ingress and the carbonation, the interaction of both processes can be visualized in a measurement that takes less than 10 minutes for a 50 mm x 100 mm drill core.
A leaflet on the use of LIBS for the chloride ingress assessment has been completed.
In many scientific fields, isotopic analysis can offer valuable information, e.g., for tracing the origin of food products, environmental contaminants, forensic and archaeological samples (provenance determination), for age determination of minerals (geochronological dating) or for elucidating chemical processes. Up to date, typically bulk analysis is aimed at measuring the isotopic composition of the entire elemental content of the sample. However, the analyte element is usually present under the form of different elemental species. Thus, separating species of interest from one another and from matrix components prior to isotope ratio measurements can provide species-specific isotopic information, which could be used for tracing the origin of environmental pollutants and elucidation of (environmental) speciation. Using on-line hyphenations of separation techniques with multicollector-ICP-MS (MC-ICP-MS) can save time and effort and enables the analysis of different species during a single measurement.
In this work, we developed an on-line hyphenation of CE with multicollector-ICP-MS (CE/MC-ICP-MS) for isotopic analysis of sulfur species. With this method, the isotopic composition of sulfur in sulfate originating from river water could be analyzed without sample preparation. The results were compared with data from off-line analysis of the same samples to ensure accuracy. The precision of the results of the on-line measurements was high enough to distinguish the rivers from one another by the isotopic signature of the river water sulfate. Next to environmental applications, a current field is species-specific isotopic analysis of biomolecules, as sulfur is the only covalently bound constituent of proteins which can be analyzed by MC-ICP-MS. Data analysis of transient signals in terms of isotope ratio determination is further issue - we developed a small free accessible App allowing for fast data analysis taking relevant aspects (e.g., mass bias correction, peak picking, …) into account.
Due to the ageing of the infrastructure facilities, a reliable assessment of the condition of concrete structures is of great interest to plan timely and appropriate measures. In concrete structures, pittingcorrosion of the reinforcement is the predominant deterioration mechanism affecting serviceability and eventually structural performance. Determination of quantitative chloride ingress is not only necessary to obtain valuable information on the current condition of a structure, but the data obtained can also be used to predict future developments and the associated risks. An overview of the progress and the possibilities of the application of laser-induced breakdown spectroscopy for concrete analysis in daily civil engineering practice is given. High-resolution 2D measurements of drill cores to determine the penetration of harmful species into concrete is presented. Furthermore, the application of a mobile LIBS system in a parking garage is shown. The system consists of a diode-pumped low-energy laser (3 mJ, 1.5 ns, 100 Hz) and a compact NIR spectrometer. A scanner allows two-dimensional element mapping. Progress towards the establishment of LIBS in a leaflet for the analysis of chlorine ingress into concrete in civil engineering is presented.
The main application of LIBS in civil engineering is the detection of harmful ions in concrete, which can penetrate the component through the porous concrete structure. The advantages of LIBS over standard methods are the possibility of multi-element analysis, measurement speed, spatially resolved measurements, and minimal sample preparation. The spatially resolved measurements of LIBS allow the assessment of the heterogeneity of the concrete by measuring separately the chemical composition of the aggregates and the binder matrix. The latter is particularly relevant because the determined elemental distribution can be directly related to the binder matrix. This is not possible with standard methods, since the material is homogenized to powder during sample preparation stage and the determined concentration is thus related to the total mass. In addition to the use of LIBS for the specific analysis of individual harmful ions, LIBS can also be used to estimate the concrete composition and thus determine, for example, the type of cement used. Corresponding information are relevant for the estimation of the remaining service life and for the preparation of a maintenance concept. In recent years, LIBS has been increasingly used in civil engineering. Currently, however, it is primarily used in research institutions and only occasionally in building materials laboratories. Special commercial devices have also been developed, which greatly simplify the application due to the high degree of automation. Mobile LIBS systems allow on-site application. A central point, which limits the use of LIBS in the commercial sector, is the lack of norms and standards. Therefore, within the framework of a project funded by the German government, work has been carried out on the preparation of a leaflet on quantitative chlorine determination in concrete, which will be published this year. In interlaboratory comparisons the robustness and accuracy for the practical application was demonstrated. LIBS also has great potential in the recycling of construction waste in conjunction with hyperspectral sensors. This issue is currently being addressed in a national project. During the presentation, the state of the art of LIBS in civil engineering will be presented, next steps will be discussed, and future challenges will be outlined.
The metrological analysis uses an unbroken chain of comparative measurements to trace results back to the national or international standard. This enables comparable, absolute quantification between laboratories. In 2020/2021, a pilot study for the quantification of SARS-CoV-2 antibodies was initiated with the involvement of BAM. Despite the consistent use of ID-MS, a large discrepancy in the results of the participating laboratories was found. This was the motivation for a project to systematically investigate and optimize traceable methods of protein quantification using mass spectrometric nontarget analysis (NTA) and recombinant antibody panels.
The composition of acoustically levitated droplets was probed by a novel combination of mid-IR laser evaporation and subsequent postionization via secondary electrospray ionization. The combination of microliter samples and subnanoliter sampling provided time-resolved interrogation of droplets and allowed for a kinetic investigation of the laser-induced release of the analyte, which was found to strongly depend on the analytes. The observed substancespecific delayed release of the analytes permitted baseline-separated discrimination of the analytes, ideal for the study of complex samples.
The additionally applied postionization scheme was found to enable efficient detection of small volatile compounds as well as peptides. The detection of small molecules and peptides occurred under very different sampling geometries, pointing to two distinct underlying ionization mechanisms. Overall, our results suggest that the experimental setup presented in this study can serve as a widely applicable platform to study chemical reactions in acoustically levitated droplets as model reactors.
Living organisms constantly interact with their environment, including through the exchange of gases. Respiration and the release and uptake of volatile organic compounds (VOCs) create dynamic microenvironments in biological systems. Studying the kinetics of volatiles in biological systems requires expensive instruments, and data analysis is challenging. Therefore, we aimed to design a minimal analytical device for measuring the composition of gaseous mixtures in realtime.
We built the ‘Modular Biological Mass Spectrometer’ (MoBiMS) from 3D-printed parts and custom sensors to fit a wide array of experimental set-ups. We tested the chemical detection range and temporal resolution of the MoBiMS employing pure compounds and complex biological samples.
Compounds with a higher than 0.4 mmHg vapor pressure and a molecular weight up to 154 g/mol were reliably sensed within seconds. The generated electron impact (EI) spectra were directly comparable with standard databases like the NIST EI library. Under a direct analysis approach, the MoBiMS identified the characteristic odor of banana (Musa sp.), that is, isoamyl acetate; tracked the dynamics of CO2 release while the Alka-Seltzer® reaction occurred showed the kinetics of the transient production and consumption of carbon dioxide during photosynthesis. MoBiMS also discriminated between volatile compounds ions coming from tobacco (Nicotiana benthamiana) leaves and the surrounding air through untargeted analysis. The small footprint of the MoBiMS and its relatively low energy consumption facilitate in situ analyses, as an additional gas supply is not necessary with EI ionization. The MoBiMS is easy to assemble, and its construction and operation are very cost-efficient compared to commercial devices. The analytical performance of the MoBiMS is suitable for real-time studies of biological systems, environmental monitoring, and medical diagnostics.
Unintended Rate Enhancement in Mechanochemical Kinetics by Using Poly(methyl methacrylate) Jars
(2022)
Time-resolved in situ (TRIS) X-ray diffraction has changed how mechanochemical transformations are studied but requires the use of X-ray transparent jars often made from poly(methyl methacrylate) (PMMA). However, using PMMA jars can alter the apparent kinetics of mechanochemical polymorphism by an order of magnitude, questioning the interpretability of established TRIS methods. Our results suggest that rate enhancement in PMMA jars may not be dominated by chemical effects of the polymer, but rather a result of different equilibrium temperatures within the jar. These features must be better understood before control over mechanochemical reactions can be achieved.
Small-angle scattering is an increasingly common method for characterizing particle ensembles in a wide variety of sample types and for diverse areas of application. SASfit has been one of the most comprehensive and flexible curve-fitting programs for decades, with many specialized tools for various fields. Here, a selection of enhancements and additions to the SASfit program are presented that may be of great benefit to interested and advanced users alike: (a) further development of the technical basis of the program, such as new numerical algorithms currently in use, a continuous integration practice for automated building and packaging of the software, and upgrades on the plug-in system for easier adoption by third-party developers; (b) a selection of new form factors for anisotropic scattering patterns and updates to existing form factors to account for multiple scattering effects; (c) a new type of a very flexible distribution called metalog [Keelin (2016). Decis. Anal. 13, 243–277], and regularization techniques such as the expectation-maximization method [Dempster et al. (1977). J. R. Stat. Soc. Ser. B (Methodological), 39, 1–22; Richardson (1972) J. Opt. Soc. Am. 62, 55; Lucy (1974). Astron. J. 79, 745; Lucy (1994). Astron. Astrophys. 289, 983–994], which is compared with fits of analytical size distributions via the non-linear least-squares method; and (d) new structure factors, especially for ordered nano- and meso-scaled material systems, as well as the Ornstein–Zernike solver for numerical determination of particle interactions and the resulting structure factor when no analytical solution is available, with the aim of incorporating its effects into the small-angle scattering intensity model used for fitting with SASfit.
Der Bunsen-Kirchhoff-Preis 2022 wurde am 23.06.2022 anlässlich der analytica conference in München an Dr. Carlos Abad verliehen - in Anerkennung seiner exzellenten Entwicklungen im Bereich der continuum source atomic absorption spectrometry (CS-AAS).
Dr. Carlos Abad ist ein herausragender Experte auf dem Gebiet der Atom- und molekularen Absorptionsspektrometrie. insbesondere trug er maßgeblich zur substanziellen Weiterentwicklung von Echelle-Spektrometern für die CS-AAS bei. So gelang es, einen quantitativen Zugang zu Elementen wie Bor, Chlor, Fluor und Schwefel, mittels AAS zu erreichen. Erstmals demonstriert Dr. Carlos Abad am Beispiel eines Zr-Modifier, dass durch die Zeitauflösung der eingesetzten Echelle-Systeme mechanistische Untersuchungen zur Wirkung des Modifiers im Graphitrohrofen möglich sind.
Besonders hervorzuheben sind seine Arbeiten zum Einsatz der CS-AAS für die Analyse von Isotopen, die eine Genauigkeit aufweist, welche an die der Multikollektor-induktiv gekoppelten Plasma-Massenspektrometrie (MC-ICP-MS) heranreicht. Damit ergeben sich völlig neue Einsatzmöglichkeiten für technologisch hochrelevante Applikationen, wie z.B. die Untersuchung der Alterung von Lithium-Batterien oder die Lithium-Analyse in Blutserum.
Calcium isotope analysis can be an important tool for paleoclimate studies of the carbon cycle, as well in carbon capture technology, but its utility is limited by challenges using conventional mass spectrometry. We propose a new fast, precise, and high-throughput technology based on multiple complementary high-resolution spectroscopies analyzed by machine-learning.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.
Glow discharge optical emission spectroscopy (GD-OES) is a technique for the analysis of solids such as metals, semiconductors, and ceramics. A low-pressure glow discharge plasma is applied in this system, which ‘sputters’ and promotes the sample atoms to a higher energy state. When the atoms return to their ground state, they emit light with characteristic wavelengths, which a spectrometer can detect. Thus, GD-OES combines the advantages of ICP-OES with solid sampling techniques, which enables it to determine the bulk elemental composition and depth profiles. However, direct solid sampling methods such as glow-discharge spectroscopy require reference materials for calibration due to the strong matrix effect.
Reference materials are essential when the accuracy and reliability of measurement results need to be guaranteed to generate confidence in the analysis. These materials are frequently used to determine measurement uncertainty, validate methods, suitability testing, and quality assurance. In addition, they guarantee that measurement results can be compared to recognized reference values. Unfortunately, the availability of certified reference materials suited to calibrate all elements in different matrix materials is limited. Therefore various calibration strategies and the preparation of traceable matrix-matched calibration standards will be discussed.
Machine learning is an essential component of the growing field of data science. Through statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. Therefore, it was tried in our work to combine GD-OES with machine learning strategies to establish a new and robust calibration model, which can be used to identify the elemental composition and concentration of metals from a single spectrum. For this purpose, copper reference materials from different manufacturers, which contain various impurity elements, were investigated using GD-OES. The obtained spectra information are evaluated with different algorithms (e.g., gradient boosting and artificial neural networks), and the results are compared and discussed in detail.
Isotope analysis is a tool for material research. For example, it may provide information about the provenance of a sample or changes in dynamic systems. Here is presented optical spectroscopy as an analytical alternative to mass spectrometry for isotope quantification based on the isotopic shift of atoms and diatomic molecules.
Mechanochemistry offers a unique opportunity to modify or synthesize new crystal forms. Although the method is very promising, little is known about the mechanochemical means to control the synthesis of a solid form. Using an polymorphic organic cocrystal system, we show here that mechanochemistry can be used to obtain a polymorph transformation under the apparently conventional (thermal) transition point.
Mechanochemistry offers a unique opportunity to modify and manipulate crystal forms, often providing new products as compared with conventional solution methods. While promising, there is little known about how to control the solid form through mechanochemical means, demanding dedicated investigations. Using a model organic cocrystal system (isonicotinamide:glutaric acid), we here demonstrate that with mechanochemistry, polymorphism can be induced in molecular solids under conditions seemingly different to their conventional thermodynamic (thermal) transition point. Whereas Form II converts to Form I upon heating to 363 K, the same transition can be initiated under ball milling conditions at markedly lower temperatures (348 K). Our results indicate that mechanochemical techniques can help to reduce the energy barriers to solid form transitions, offering new insights into controlling polymorphic forms. Moreover, our results suggest that the nature of mechanochemical transformations could make it difficult to interpret mechanochemical solid form landscapes using conventional equilibrium-based tools.
In X-ray computed tomography (XCT), an X-ray beam of intensity I0 is transmitted through an object and its attenuated intensity I is measured when it exits the object. The attenuation of the beam depends on the attenuation coefficients along its path. The attenuation coefficients provide information about the structure and composition of the object and can be determined through mathematical operations that are referred to as reconstruction. The standard reconstruction algorithms are based on the filtered backprojection (FBP) of the measured data. While these algorithms are fast and relatively simple, they do not always succeed in computing a precise reconstruction, especially from under-sampled data. Alternatively, an image or volume can be reconstructed by solving a system of linear equations. Typically, the system of equations is too large to be solved but its solution can be approximated by iterative methods, such as the Simultaneous Iterative Reconstruction Technique (SIRT) and the Conjugate Gradient Least Squares (CGLS). This dissertation focuses on the development of a novel iterative algorithm, the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT). After its reconstruction principle is explained, its performance is assessed for real parallel- and cone-beam CT (including under-sampled) data and compared to that of other established algorithms. Finally, it is demonstrated how the shape of the measured object can be modelled into DIRECTT to achieve even better reconstruction results.
Gold films coated with a graphene sheet are being widely used as sensors for the detection of label-free binding interactions using surface plasmon resonance (SPR). During the preparation of such sensors, it is often essential to subject the sensor chips to a high-temperature treatment in order to ensure a clean graphene surface. However, sensor chips used currently, which often use chromium as an adhesion promoter, cannot be subjected to temperatures above 250 °C, because under such conditions, chromium is found to reorganize and diffuse to the surface, where it is easily oxidized, impairing the quality of SPR spectra. Here we present an optimized preparation strategy involving a three-cycle tempering coupled with chromium (oxide) etching, which allows the graphene-coated SPR chips to be annealed up to 500 °C with little deterioration of the surface morphology. In addition, the treatment delivers a surface that shows a clear enhancement in spectral response together with a good refractive index sensitivity. We demonstrate the applicability of our sensors by studying the kinetics of avidin–biotin binding at different pH repeatedly on the same chip. The possibility to anneal can be exploited to recover the original surface after sensing trials, which allowed us to reuse the sensor for at least six cycles of biomolecule adsorption.
Vertebrate bones are made of a nanocomposite consisting of water, mineral and organics. Water helps bone material withstand mechanical stress and participates in sensation of external loads. Water diffusion across vertebrae of medaka (bone material lacking osteocytes) and zebrafish (bone material containing osteocytes) was compared using neutron tomography. Samples were measured both wet and following immersion in deuterated-water (D2O). By quantifying H+ exchange and mutual alignment with X-ray lCT scans, the amount of water expelled from complete vertebra was determined. The findings revealed that anosteocytic bone material is almost twice as amenable to D2O diffusion and H2O exchange, and that unexpectedly, far more water is retained in osteocytic zebrafish bone. Diffusion in osteocytic bones (only 33 % – 39 % water expelled) is therefore restricted as compared to anosteocytic bone (~ 60 % of water expelled), presumably because water flow is confined to the lacunar-canalicular network (LCN) open-pore system. Histology and Raman spectroscopy showed that anosteocytic bone contains less proteoglycans than osteocytic bone. These findings identify a previously unknown functional difference between the two bone materials. Therefore, this study proposes that osteocytic bone retains water, aided by non-collagenous proteins, which contribute to its poroelastic mechano-transduction of water flow confined inside the LCN porosity.
Quantitative 1H Nuclear Magnetic Resonance (qNMR) of Aromatic Amino Acids for Protein Quantification
(2022)
qNMR is a valuable technique for metrological studies due to the uniformity of its signal response for all chemical species of an isotope of interest, which enables compound-independent calibration. However, protein quantification remained challenging as large molecules produce wide, low-intensity signals that reduce the already low sensitivity. Combining qNMR with the hydrolysis of protein samples into amino acids circumvents many of these issues and facilitates the use of NMR spectroscopy for absolute protein and peptide quantification.In this work, different conditions have been tested for quantifying aromatic amino acids and proteins. First, we examined the pH-based signal shifts in the aromatic region. The preferable pH depends on the selection of the amino acids for quantification and which internal standard substance should be used to avoid peak overlap. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, have been applied as internal standards. The quantification of amino acids from an amino acid standard, as well as from a certified reference material (bovine serum albumin), was performed. Using the first two suggested internal standards, recovery was ~ 97 % for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98 ± 2 and 88 ± 4 %, respectively, at a protein concentration of 16 g/L or 250 µM.
Hydration is the exothermic reaction between anhydrous cement and water, which forms the solid cement matrix of concrete. Being able to evaluate the hydration is of high interest for the use of both conventional and more climate-friendly building materials. The experimental monitoring is based on temperature or moisture measurements. The first needs adiabatic conditions, which can only be achieved in laboratory. The latter is often measured comparing the weight of the material sample before and after oven drying, which is time-consuming. This study investigates the moisture content of two cement-based and two calcium sulphate based mixtures for the first 90 days by using the calcium carbide method and oven drying at 40 °C and 105 °C (Darr method). Thereby, the amount of chemically bound water is determined to derive the degree of hydration. The calcium carbide measurements highly coincide with oven drying at 40 °C. The calcium carbide method is therefore evaluated as a suitable alternative to the time-consuming Darr drying. The prompt results are seen as a remarkable advantage and can be obtained easily in laboratory as well as in the field.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
New Reference Materials for Quantification and Standardization of Fluorescence-based Measurements
(2022)
Luminescence techniques are amongst the most commonly used analytical methods in the life and material sciences due to their high sensitivity and non-destructive and multiparametric character. Photoluminescence signals are, however, affected by wavelength-, polarization-, and time-dependent instrument specific effects and the compound-specific photoluminescence quantum yield. The former hamper the comparability of fluorescence measurements, while the relative determination of the latter requires suitable quantum yield standards with well-known photoluminescence quantum yields. For the simple correction of instrument specific effects in the wavelength region of 300 nm to 950 nm, the set of the five certified spectral fluorescence standards (CRM) BAM-F001 – BAM-F005, has been extended to the NIR range by including two new fluorescence standards currently under certification.
XPS of GR2M
(2022)
High-resolution absorption isotopic spectrometry as a tool for aging studies of Li-ion batteries
(2022)
Lithium (Li) is the key element in the manufacturing of batteries. Isotopic study of Li may help to identify the causes of battery aging due to isotopic fractionation during charge/discharge cycles.
Isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←22S electronic transition around 670.788 nm. In this work, we propose improvements to our previous work [1] by using a higher-resolution double echelle modular spectrometer (HR-DEMON II) coupled to a continuum source graphite furnace atomic absorption spectrometer (HR-CS-GF-AAS) for the isotopic analysis of Li.
The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm (XGBoost). A set of samples with 6Li isotope amount fractions ranging from 0.0004 to 0.99 mol mol-1 was used for the algorithm's training. Subsequently, the procedure was validated by a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material, a cathode material (NMC111). Finally, the ML model was applied to determine the isotope ratio of geological samples, including anorthosite, granite, soil, rhyolite, nepheline syenite, and basalt and battery samples. These samples were measured as digested without any further purification step.
Improvements in the optical resolution resolve the lithium isotopic components of the atomic spectra. In the studied geological samples, were found δ7Li values between -0.5 and 4.5 ‰ with a precision range of 1 to 2 ‰. In addition, the proposed method was validated with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), and these results are comparable and compatible.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in New Zealand. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
In this study, the concept of a zero mass flow liner is evaluated. The concept enables impedance control by theinduction of, acoustically actuated, periodic bias flowthrough the facing sheet of the liner. Bymeans of the periodic bias flow, the impedance of the liner is adapted to different grazing flowconditions.The equivalent fluid impedancemodel for perforated plates is modified to account for the effects of periodic bias and grazing flow. A generally applicable optimization routine, using the impedance of the lined surface as a boundary condition in a numeric calculation, is implemented. Based on the results of the optimization, a zero mass flow liner is manufactured and evaluated experimentally. The damping characteristics are assessed in the form of dissipated energy along the lined surface.
Prediction and measurements show reasonable agreement. The zero mass flow liner delivers broadband dissipation of high peak value over a range of grazing flow Mach numbers. Under grazing flow, the effect of periodic bias flow is reduced. For a ratio of grazing to bias flow velocities larger than five, no appreciable effect is found. This poses considerable energy requirements on the actuation source for the application in high-Mach-number flow regimes.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in West Africa. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Mexico. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Peru. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2022. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
Per- and polyfluorinated alkyl substances (PFASs) are a group of several thousand individual compounds. Many PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their various chemical and physical properties as well as the high number of compounds. Target-based approaches (e.g., LC-MS/MS) are limited to the availability of analytical grade standards and are not suitable for the analysis of new/unknown PFASs and transformation products. Therefore, PFAS sum parameter methods become increasingly important to indicate realistic PFAS pollution levels.
PFAS sum parameters display the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. High resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification of c(F) 2.7 µg/L.
In the present work a HR-CS-GFMAS method for EOF analysis was utilized for suspended particulate matter (SPM) analysis in German rivers in time lines from 2005–2020. Therefore, time and spatial resolved trends were investigated. In addition, SPM samples were analyzed for the Σ41PFAS using target analysis based on UHPLC-HRMS. Overall, target analysis drastically underestimated the total PFAS burden in SPM of German rivers compared to the EOF HR-CS-GFMAS analysis. Using a fluorine mass balance approach, only 0.2% to 38.6% of the EOF was explainable using the Σ41PFAS determined with target analysis. Our study highlights the need to integrate PFAS sum parameters (e.g., EOF with HR-CS-GFMAS) in PFAS risk assessment strategies.
This presentation summarizes major findings from an international study in 16 countries and regions on digital transformation in conformity assessment bodies such as testing and calibration laboratories or certification and inspection bodies. It draws from survey data of 1.476 participants and specifically highlights findings on the digital maturity of the organizations, providing an international comparison.
The isotopic analysis of lithium is also relevant to the study of geological phenomena.1 In this work we propose improvements to the method for the isotopic analysis of lithium using a high-resolution continuum source atomic absorption spectrometer (HR-CS-AAS) coupled to a double echelle modular spectrometer (DEMON). 2 This tool for isotopic ratio determination is based on monitoring the isotopic components of lithium by their spin-orbit coupling and its isotopic shift of about 15 pm for the 22P←2 2S electronic transition around 670.788 nm. The data analysis was carried out by using a decision-tree-based ensemble machine learning (ML) algorithm. For the training of the algorithm (XGBoost), a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol-1 was used. Subsequently, the procedure was validated of a set of stock chemicals (Li2CO3, LiNO3, LiCl and LiOH) and a BAM candidate reference material, the cathode material LiNi1/3Mn1/3Co1/3O2 (NMC111). Finally, the ML model was applied to the set of geological samples, previously digested, for the determination of their isotope ratio. The optical resolution was improved from 140,000 to 790,000 to better deconvolution the lithium isotopic components in the atomic spectrum. And the method was compared with multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). The results are metrologically comparable.
Estrogens are endocrine disrupting chemicals and of high concerns due to demonstrated harmful effects on the environment and low effect levels. For monitoring and risk assessment, several estrogens were included in the "watch list" of the EU Water Framework Directive which sets very low environmental quality standard (EQS) levels for Estrone (E1) and 17β-Estradiol (E2) of 0.4 ng L−1 and for 17α-Ethinylestradiol (EE2) of 0.035 ng L−1 requiring sensitive detection methods, as well as extensive sample preparation. A sensitive, derivatization-free, isotope dilution calibration HPLC-MS/MS method for a panel of 5 selected estrogens (including the 3 estrogens of the EU WFD watchlist), and a procedure for the reproducible preparation of a representative whole water matrix including mineral water, humic acids and solid particulate matter are presented. These are used in a diligent comparison of classical solid phase extraction (SPE) on hydrophilic-lipophilic balanced (HLB) phase to SPE on an estrogen-specific molecularly imprinted polymer phase (MISPE) for ultra-trace levels of the analytes (1–10 ng L−1). Additionally, a two-step procedure combining HLB SPE disks followed by MISPE is evaluated. The tow-step procedure provides superior enrichment, matrix removal and sample throughput while maintaining comparable recovery rates to simple cartridge SPE. Estimated method quantification limits (MQLs) range from 0.109–0.184 ng L−1 and thus meet EQS-levels for E1 and E2, but not EE2. The representative whole water matrix provides a reproducible comparison of sample preparation methods and lays the foundation for a certified reference material for estrogen analysis. The presented method will serve as the basis for an extended validation study to assess its use for estrogen monitoring in the environment.
X-ray fluorescence imaging is a well-established tool in materials characterization. In this work, we present the adaption of coded aperture imaging to full-field X-ray fluorescence imaging at the synchrotron. Coded aperture imaging has its origins in astrophysics, and has several advantages: Coded apertures are relatively easy to fabricate, achromatic, allow a high photon throughput, and high angular acceptance. Coded aperture imaging is a two-step-process, consisting of the measurement process and a reconstruction step. Different programs have been written, for the raytracing/forward projection and the reconstruction. Experiments with coded aperture in combination with a Color X-ray Camera and an energy-dispersive area detector, have been conducted at the BAMline. Measured samples were successfully reconstructed, and gave a 9.1-fold increase in count rate compared to a polycapillary optic.
A tool for merging and/or rebinning single or multiple datasets to achieve a lower point density with best possible statistics. highly scriptable, CLI, no GUI
Version 0.1: works but could do with a cleanup. Weighting by uncertainty currently always on, but should be optional for use as an azimuthal or radial averager
IsoCor
(2022)
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.
The formation of irregularities such as keyhole porosity pose a major challenge to the manufacturing of metal parts by laser powder bed fusion (PBF-LB/M). In-situ thermography as a process monitoring technique shows promising potential in this manner since it is able to extract the thermal history of the part which is closely related to the formation of irregularities. In this study, we investigate the utilization of machine learning algorithms to detect keyhole porosity on the base of thermographic features. Here, as a referential technique, x-ray micro computed tomography is utilized to determine the part's porosity. An enhanced preprocessing workflow inspired by the physics of the keyhole irregularity formation is presented in combination with a customized model architecture. Furthermore, experiments were performed to clarify the role of important parameters of the preprocessing workflow for the task of defect detection . Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
The appearance of irregularities such as keyhole porosity is a major challenge for the production of metal parts by laser powder bed fusion (PBF-LB/M). The utilization of thermographic in-situ monitoring is a promising approach to extract the thermal history which is closely related to the formation of irregularities. In this study, we investigate the utilization of convolutional neural networks to predict keyhole porosity based on thermographic features. Here, the porosity information calculated from an x-ray micro computed tomography scan is used as reference. Feature engineering is performed to enable the model to learn the complex physical characteristics of the porosity formation. The model is examined with regard to the choice of hyperparameters, the significance of thermal features and characteristics of the data acquisition. Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
Attenuation of ultrasonic signals in concrete has the potential to carry much information about the microstructure of the material. In this work a series of concrete specimens of varying porosities and pore size distributions were internally imaged with x-ray computed tomography (CT), and then subsequently examined with throughtransmission ultrasound. The CT images were used to quantify both capillary porosity of cement paste as well as internal interfaces that are likely to produce elastic wave scattering. Ultrasound signals were represented as a diffusion process such that absorption and scattering attenuation could be isolated. As implemented, the diffusion model was a poor predictor of capillary porosity, while diffusivity was a reasonable predictor of scattering interfaces. Diffusivity was found to scale extremely well with small scale porosity, which made it a good predictor of compressive strength.
The retroreflective corner echo is used, for example, in ultrasonic non-destructive testing of metals to find fatigue cracks in tubes or shafts. If the much weaker crack tip signal is additionally detected, the crack length can also be determined. A corner reflection occurs in cases of surface breaking cracks with predominantly perpendicular orientation to the surface. The intensity of the corner reflection depends on the angle of incidence and on the ultrasonic wave mode used. For the reliable detection of vertical surface breaking cracks in metals, transversal waves are commonly used, which propagate at an angle of 37° to 53° to the inspection surface. As shown in this contribution, the wide spread low frequency ultrasonic arrays with dry point contact sources available for ultrasonic testing of concrete also allow to receive corner echoes. These devices generate transversal waves in concrete structures with a large divergence of the sound field. A series of experiments was carried out with such dry point contact arrays on concrete specimens with artificial test defects and controlled induced cracks of different depths. The ultrasonic time-of-flight signals were recorded, exported and reconstructed utilising the SAFT (Synthetic Aperture Focusing Technique) algorithm. The SAFT reconstruction parameters were adjusted to visualize the corner echo indication. As will be shown, with this targeted processing, the reproducible detection of surface breaking cracks in concrete is possible. The retroreflective corner echo can thus be exploited in civil engineering for non-destructive inspection of concrete.
Muon tomography applied to assessment of concrete structures: First experiments and simulations.
(2022)
Non-destructive techniques for reinforced or prestressed concrete inspection such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened new fields of application. As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. In a second step, we have performed simulations to assess the potential for a set of important testing problems such as grouting defects in tendon ducts. The next steps include the development of mobile detectors and optimizing acquisition and imaging parameters.
This contribution summarizes actual developments and draft fundamental teaching topics in the field of nondestructive testing in civil engineering (NDT-CE). It is based on the first memorandum on teaching and research in the field of NDT-CE at German speaking universities and provides an overview of the academic education and highlights possible focuses, especially in teaching but also takes into account noteworthy developments and topics in research in the field of NDT-CE.
Suggestions are given for the development and advancement of the teaching curricula in regards to a comprehensive and sound professional education of students in civil engineering and adjacent disciplines.
Muon tomography applied to assessment of concrete structures: First experiments and simulations.
(2022)
Non-destructive techniques for reinforced or prestressed concrete inspection such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and
accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques.
However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened new fields of application. As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. In a second step, we have performed simulations to assess the potential for a set of important testing problems such as grouting defects in tendon ducts. The next steps include the development of mobile detectors and optimizing acquisition and imaging parameters.
To complement the information provided by deterministic seismic imaging at length scales above a certain resolution limit we present the first application of adjoint envelope tomography (AET) to experimental data. AET uses the full envelopes of seismic records including scattered coda waves to obtain information about the distribution of absorption and small-scale heterogeneity which provide complementary information about the investigated medium. Being below the resolution limit this small-scale structure cannot be resolved by conventional tomography but still affects wave propagation by attenuating ballistic waves and generating scattered waves. Using ultrasound data from embedded sensors in a meter-sized concrete specimen we image the distribution of absorption and heterogeneity expressed by the intrinsic quality factor Q−1 and the fluctuation strength ɛ that characterizes the strength of the heterogeneity. The forward problem is solved by modeling the 2-D multiple nonisotropic scattering in an acoustic medium with spatially variable heterogeneity and attenuation using the Monte-Carlo method. Gradients for the model updates are obtained by convolution with the back-propagated envelope misfit using the adjoint formalism in analogy to full waveform inversion.
We use a late coda time window to invert for absorption and an earlier time window to infer the distribution of heterogeneity. The results successfully locate an area of salt oncrete with increased scattering and concentric anomalies of intrinsic attenuation. The resolution test shows that the recovered anomalies constitute reasonable representations of internal structure of the specimen.
Screening against ADAMTS4 reveals a specific peptide, which was turned into an MRI probe. The aneurysm in a mouse modal was visualized via MRI. A differentiation between stable and unstable aneurysm in an early state was performed. Using the probe as tool for an easy and non-invasive rupture assessment is possible.
ABID
(2022)
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.
Our aim is to develop a simple and inexpensive method for full field X-ray fluorescence imaging.We combine an energydispersive array detector with a coded aperture to obtain high resolut ion images. To obtain the information from the recorded image a reconstruction step is necessary. The reconstruction methods we have developed, were tested on simulated data and then applied to experimental data. The first tests were carried out at the BAMline @BESSY II. This method enables the simultaneous detection of multiple elements,which is important e.g. in the field of catalysis.
With the development of hybridoma technology, monoclonal antibodies are increasingly important in therapeutic and analytical applications. For recombinant expression in mammalian cells, knowledge of the variable regions of both, heavy (VH) and light (VL) chain, is a necessary prerequisite for generating expression plasmids. Furthermore, cloning antibody sequences including constant regions CH1 to CH3 and CL reduces impact of hybridoma cell loss and associated full natural antibody sequence leakage. Here, we show a cost-effective workflow for amplification of IgG antibody variable regions in combination with advanced methods for full-length cloning of monoclonal antibodies.
Compositionally complex alloys (CCAs) are a new class of alloys containing at least 5 elements with concentrations between 5 and 35 atomic percent. Due to their adjustable composition, which enables modifications of mechanical properties (such as hardness, strength and ductility etc) and their stability at high temperatures, CCAs have been the focus of various studies [1,2]. Especially the corrosion behavior of CCAs has been a wide research interest.
However, there are only few studies that deals with the degradation process on such materials, which is highly relevant for the safety aspect for future component design. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Since the grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect notable information regarding the high temperature oxidation, we consider it as a useful method to investigate how CCAs behave in corrosive environments.
The main idea of grazing geometry is to enhance the fluorescence signal of the surface. This enables highly sensitive surface analyses of thin protective film on surface in sub-micrometer scale [3]. When compared to a conventional CCD-based camera, the advantage and most important feature of the detector system (Color X-Ray Camera (CXC)) is that each pixel is an energy sensitive detector. The position and area sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
In this contribution, we address the feasibility of our setup and new optimization procedure (Bayesian Optimization and Gaussian Regression). The results of a conceptual study regarding layer properties of the reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer) and CrCoNi (Cr-Oxide (>1µm) layer on CrCoNi substrate) medium entropy alloy.
The components that are used in structural and in high temperature applications generally face significant challenges with respect to oxidation behaviours and metalworking processes. In most of the cases, harsh environmental conditions lead materials to degrade due to corrosion. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect this information in sub-micrometre depth range.
In order to obtain structural information, such as regarding oxidation states or atomic/molecular geometric arrangement, the GEXRF approach can also be combined with the X-ray absorption spectroscopy (XAS) method. The position and energy sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
We address the feasibility of our setup and provide a new optimization procedure (Bayesian Optimization and Gaussian Regression) to decrease measuring time. The results settle on a conceptual study on a reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer).
Time is the most valuable parameter in synchrotron experiments. This is costly and some of the experiments suffer from low efficiency due to low counting statistics. With today's high processing power long experiments are run in a shorter time and increase efficiency. With optimization algorithms time in "counting-hungry" experiments reduced by factor of 10. Our project is to develop a new method to analyze the chemical properties of complex materials non-destructively and efficiently, such as high entropy materials subjected to corrosion processes. A better understanding of the corrosion process will help to develop corrosion-resistant materials and reduce the cost of corrosion damage, which averages around 2.5 trillion USD annually.
The components that are used in structural and in high temperature applications generally face significant challenges with respect to oxidation behaviours and metalworking processes. In most of the cases, harsh environmental conditions lead materials to degrade due to corrosion. To thoroughly investigate the corrosion processes and to determine oxidation states of metal components within the reaction products, we need special analytical tools. Grazing exit X-ray fluorescence (GEXRF) offers a non-destructive way to collect this information in sub-micrometre depth range.
In order to obtain structural information, such as regarding oxidation states or atomic/molecular geometric arrangement, the GEXRF approach can also be combined with the X-ray absorption spectroscopy (XAS) method. The position and energy sensitive detector, with 264x264 pixel detector area, provides information regarding the signal emitted from the sample as a function of the emission angle and thus allows depth-sensitive analysis. Furthermore, the data collected from samples of an incidence energy which can be controlled with a resolution of 0.5 eV provides XANES data to determine oxidation states.
We address the feasibility of our setup and provide a new optimization procedure (Bayesian Optimization and Gaussian Regression) to decrease measuring time. The results settle on a conceptual study on a reference sample (Cr-Oxide layer (300nm) on Cr layer (500nm) on Si wafer).
Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline
(2022)
For more than 20 years, BAM is operating the BAMline at the synchrotron BESSY II in Berlin Adlershof. During this time, the complexity of the setup and the amount of data generated have multiplied. To increase the effectiveness and in preparation for BESSY III, algorithms from the field of machine learning are increasingly used.
After a short introduction to BO and GP, the first example is the automatic alignment of our double multilayer monochromator (DMM).
The second example is the optimization of measurement time in XRF scanning.
News from the BAMline
(2022)
Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS)
(2021)
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Time resolved in situ monitoring of mechanochemical transformations by X-ray spectroscopy (XAS)
(2021)
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline
(2022)
For more than 20 years, BAM is operating the BAMline at the synchrotron BESSY II in Berlin Adlershof. During this time, the complexity of the setup and the amount of data generated have multiplied. To increase the effectiveness and in preparation for BESSY III, algorithms from the field of machine learning are increasingly used.
In this paper, several examples in the areas of beamline alignment and measurement time optimization based on Bayesian optimization (BO) with Gaussian processes (GP) are presented. BO is a method for finding the global optimum of a function using a probabilistic model represented by a GP. The advantage of this method is that it can handle high-dimensional problems, does not depend on the initial estimate, and also provides uncertainty estimates.
After a short introduction to BO and GP, the first example is the automatic alignment of our double multilayer monochromator (DMM). To achieve optimal performance, up to three linear and two angular motor positions have to be optimized. To achieve this with a grid scan, at least 100^5 measurement points would be required. Assuming that all positions can be aligned independently, 100*5 points are still necessary. We show that with BO and GP less than 100 points are sufficient to achieve equal or better results.
The second example is the optimization of measurement time in XRF scanning. Here we will show the advantage of the BO GP approach over point-by-point scanning. As can be seen in Fig. 1, the number of points required and thus the measurement time can be reduced by a factor of 50, while the loss in image quality is acceptable. The advantages and limitations of this approach will be discussed.
Mechanochemical reactions promise a new direction for environmentally benign preparation of materials, and has been dubbed by IUPAC as one of the 10 chemical innovations that will change our world. Despite this significant promise, very little is known about the mechanisms that drive mechanochemical transformations, posing significant barriers to realizing their full potential. To this end, there is growing need to follow mechanochemical reactions in situ and in real time. We here describe advances in the development and application of XAS methods to monitor material synthesis in real time under mechanochemical conditions. We demonstrate the generality of our approaches by describing mechanochemical syntheses of materials by both vibratory ball milling and by Resonant Acoustic Mixing (RAM), where a time resolution of 1 second is for a whole XAS spectrum was achieved. Moreover, we describe how spectroscopic methods can be coupled to diffraction-based approaches, thereby providing new dimensions in understanding mechanochemical synthesis.
In this talk an overview about artificial intelligence/machine learning applications @BAMline is given. In the first part, the use of neural networks for the quantification of XRF measurements and the decoding of coded-aperture measurements are shown. Then it is shown how Gaussian processes and Bayesian statistics can be used to achieve an optimal alignment of the set-up and in general for optimization of measurements.
Gold is one of the seven metals already known in antiquity and was used from time immemorial as a medium of exchange and for the production of jewelry because of its luster and rarity. In addition, it is easy to work and largely resistant to chemical influences. Investigations of gold using synchrotron radiation excited X-ray fluorescence analysis are non-destructive and provide information about the chemical elements present in the sample under investigation. The investigations presented here at BAMline focus on questions such as the origin, manufacturing process, and association of gold findings. The different questions are explained by a number of examples ranging from the Viking treasure from Hiddensee to the Nebra Sky Disk and finds from Egypt. The find from Bernstorf is discussed in detail. A Bayesian treatment of the authenticity is shown.
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
Aging Mechanisms of Lithium Batteries: How can we make batteries more durable and more sustainable in the future?
Lithium batteries are particularly susceptible to ageing processes. During each charging and discharging process in an electric battery, lithium ions are deposited in the electrodes of the cell like in the pores of a sponge. Over time, however, fractures and cracks occur in the filigree structures. The result: more and more lithium ions no longer fit into the hollow spaces of the „sponge“, instead they accumulate in heaps around the electrodes and hinder the movement of other ions. The performance of the battery decreases.
We present our new project, in which we are developing a fast and cost-effective method with which companies that produce lithium batteries can already assess the ageing behaviour of their batteries in the laboratory.