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Paper des Monats
- ja (27)
The increasing amount and complexity of clinical data require an appropriate way of storing and analyzing those data. Traditional approaches use a tabular structure (relational databases) for storing data and thereby complicate storing and retrieving interlinked data from the clinical domain. Graph databases provide a great solution for this by storing data in a graph as nodes (vertices) that are connected by edges (links). The underlying graph structure can be used for the subsequent data analysis (graph learning). Graph learning consists of two parts: graph representation learning and graph analytics. Graph representation learning aims to reduce high-dimensional input graphs to low-dimensional representations. Then, graph analytics uses the obtained representations for analytical tasks like visualization, classification, link prediction and clustering which can be used to solve domain-specific problems. In this survey, we review current state-of-the-art graph database management systems, graph learning algorithms and a variety of graph applications in the clinical domain. Furthermore, we provide a comprehensive use case for a clearer understanding of complex graph learning algorithms.
In recent years, additive manufacturing technologies have gained in importance. Laser powder bed fusion can be used for complex functional components or the production of workpieces in small quantities. High safety requirements, e.g. in aerospace, demand comprehensive quality control. Therefore, non-destructive offline inspection methods such as computed tomography are used after production. Recently, online non-destructive testing methods such as optical tomography have been developed to improve profitability and practicality. In this presentation, the applicability of eddy current inspection using GMR sensors for online inspection of PBF-LB/M parts is demonstrated. Eddy current testing is performed for each layer during the production process at frequencies uo to 1.2 MHz. Despite the use of high-resolution arrays with 128 elements, the testing time is kept low by an adapted hardware. Thus, the measurement can be performed during the manufacturing process without significantly slowing down the production process. In addition to the approach, the results of an online eddy current test of a step-shaped test specimen made of Haynes282 are presented.
Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer.
The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements
In recent years, chromium (III) complexes have received a lot of attention as novel near-infrared (NIR) emitters. This interest was triggered by the report on the first molecular ruby Cr(ddpd)2(BF4)3 with a high photoluminescence quantum yield of 13.7% of its near infrared (NIR) emission band and a long luminescence lifetime of 1.122 ms at room temperature. Meanwhile, the influence of triplet oxygen, temperature, and pressure on the optical properties of different molecular rubies have been assessed. These features make these molecular rubies promising candidates for multi-analyte optical sensing applications and the generation of singlet oxygen for photocatalysis and photodynamic therapy. However, in an oxygen-containing environment, the photoluminescence quantum yields and luminescence lifetimes of these chromium(III) complexes show only very small values. This hampers their application as NIR luminescence labels. This application, that cannot be tackled by conventional deoxygenating approaches, requires suitable strategies to protect the luminescence of the chromium(III) complexes from oxygen quenching. Typical approaches to reduce the oxygen sensitivity of long-lived luminophores include the encapsulation into an oxygen-shielding matrix or less commonly employed, by tuning the bulkiness of the ligands for oxygen-sensitive coordination compounds. An elegant approach to reduce the undesired luminescence quenching by triplet oxygen explored by us presents the incorporation of these chromium(III) complexes into amorphous, non-porous silica nanoparticles, that can be simply surface functionalized, e.g., with targeting ligands and/or other sensor molecules. This can enable the use of such chromium(III) complexes as reporters for bioanalytical assays and bioimaging without the need to introduce reactive groups into the ligands and can pave the road to lifetime tuning.
In this work, as first proof-of-concept experiments, a set of chromium (III) complexes constituting of different ligands and counter anions, were embedded into the core of silica nanoparticles. As an alternative synthesis strategy, selected complexes were incorporated into a silica shell formed around the core of self-made silica nanoparticles. Subsequently, the optical properties of the resulting luminescent silica nanoparticles were spectroscopically assessed by steady state and time-resolved luminescence spectroscopy. First results of time-resolved luminescence measurements of the Cr(ddpd)2(PF6)3 complex incorporated into 25nm large silica nanoparticles dispersed in aerated water in comparison to the decay kinetics obtained for this complex in acetonitrile in air showed an increase in lifetime from 46 µs to 1147 µs. This confirming our design concept of nanoscale NIR emissive Cr(III) reporters.
New insights into pertinent Fe-complexes for the synthesis of iron via the instant polyol process
(2023)
Chemically synthesized iron is in demand for biomedical applications due to its large saturation magnetization compared to iron oxides. The polyol process, suitable for obtaining Co and Ni particles and their alloys, is laborious in synthesizing Fe. The reaction yields iron oxides, and the reaction pathway remains unexplored. This study shows that a vicinal polyol, such as 1,2-propanediol, is suitable for obtaining Fe rather than 1,3-propanediol owing to the formation of a reducible Fe intermediate complex. X-ray absorption spectroscopy analysis reveals the ferric octahedral geometry and tetrahedral geometry in the ferrous state of the reaction intermediates in 1,2-propanediol and 1,3-propanediol, respectively. The final product obtained using a vicinal polyol is Fe with a γ-Fe2O3 shell, while the terminal polyol is favourable for Fe3O4. The distinct Fe–Fe and Fe–O bond lengths suggest the presence of a carboxylate group and a terminal alkoxide ligand in the intermediate of 1,2-propanediol. A large Fe–Fe bond distance suggests diiron complexes with bidentate carboxylate bridges. Prominent high-spin and low-spin states indicate the possibility of transition, which favors the reduction of iron ions in the reaction using 1,2-propanediol.
At present, the field of research on nanostructures is actively developing, which is due to their unique physico-chemical properties compared to bulk materials. Many research activities are focused on obtaining nanocomposites, which combine various types of nanostructures with different properties and function. For example, the development of magneto-luminescent nanocomposites makes it possible to use their luminescence for optical imaging, and their magnetic properties for magnetic targeted delivery and as agents of hyperthermia and magnetic resonance imaging.
My master studies as part of the project Goszadanie 2019-1080 at ITMO were focused on the investigation of nanocomposites, consisting of semiconductor quantum dots (QDs) as luminescent component and superparamagnetic iron oxide nanoparticles (SPIONs) as magnetic one, in solution and during their incubation with HeLa cells. The spectrally resolved analysis of the QD photoluminescence (PL) kinetics of the free QDs and the QDs incorporated in these nanocomposites undergoing energy transfer processes allowed for (1) understanding the reasons for the quenching of QD luminescence in cells, (2) evaluating the average distance between the QDs and, based on this, concluding the degree of QD aggregation in cells, and (3) drawing conclusions about the QD-quencher composites integrity in cells. Overall, the analysis of the PL kinetics confirmed that QDs and SPIONs remain bound in the obtained nanocomposites during incubation with cells.
To ensure the successful advancement of nanomaterials in biomedicine and the transition from their laboratory preparation and studies to their use in different applications and in industry, it is crucial to develop reliable measurement methods and reference materials candidates for the characterization of functional nanomaterials and assessing the quality of the obtained nanostructures. My recently started project at BAM, which is part of the EU metrology project MeTrINo, will be devoted to this topic. There we will focus on the development of methodologies for the synthesis and characterization of iron oxide nanoparticles, already used in biomedicine, and multi-element lanthanide-based nanoparticles with attractive upconversion luminescence, as reference materials with high monodispersity and reproducibility. Also, these nanoparticles will be functionalized with organic dyes for optical imaging and, probably, the study of the energy transfer phenomena.
The ultrasonic echo technique is frequently used in non-destructive testing (NDT) of concrete structures for thickness measurements, geometry determinations as well as localization of built-in components. To improve ultrasonic imaging of complex structures in concrete, we transferred a geophysical imaging technique, the reverse time migration (RTM), to NDT in civil engineering. In contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, RTM is a wavefield continuation method in time and uses the full wave equation. Thus, RTM can handle complicated wave propagations in any direction without dip limitation. In this paper, we focused on the application and evaluation of a two-dimensional (2D) elastic RTM algorithm considering compressional waves, vertically polarized shear waves, and Rayleigh waves. We tested the elastic RTM routine on synthetic ultrasonic echo data generated with a 2D concrete model consisting of several steps and circular air inclusions. As these complex structures can often be found in real-world NDT use cases, their imaging is especially important. By using elastic RTM, we were able to clearly reproduce vertical reflectors and lower edges of circular air voids inside our numerical concrete model. Such structures cannot be imaged with conventional SAFT algorithms. Furthermore, the used elastic RTM approach also yielded a better reconstruction of a horizontal reflector and upper boundaries of circular air inclusions. Our encouraging results demonstrate that elastic RTM has the potential to significantly improve the imaging of complex concrete structures and, thus, is a step forward for detailed, high-quality ultrasonic NDT in civil engineering.
The Boltzmann plot method is widely used to determine the temperature of laser induced plasma. It involves the use of individual lines that are not easy to find in complex spectra and/or in the spectral range available. If the number of such lines is not enough to build a reliable Boltzmann plot, overlapping lines are often used, which are separated by software. However, line separation is a rather imprecise procedure, which, in addition, requires significant computational costs. This study proposes an extension of the Boltzmann plot method that allows a specific group of unresolved lines to be included in a Boltzmann plot without the need to separate them. This group of lines are multiplets, lines of the same element with similar upper and lower transition states. The multiplet lines along with the individual lines are included in the algorithm, which also includes a correction for self-absorption and is used to determine the plasma temperature. The algorithm is tested on synthetic spectra which are consistent with the model of a homogeneous isothermal plasma in local thermodynamic equilibrium and is shown to be superior to the standard Boltzmann plot method both in more accurate determination of the plasma temperature and in a significant reduction in the computational time. The advantages and disadvantages of the method are discussed in the context of its applications in laser induced breakdown spectroscopy.
Volatile organic compound (VOC) emissions from consumer products contribute to human inhalation exposure and may cause adverse health effects. Existing methods to determine long-term VOC emissions from e.g. building products need to be verified for their suitability to reliably detect initial VOC emissions from consumer products within the first hours and days of use, which would facilitate realistic inhalation exposure assessments. To investigate this issue, VOCs emitted from a test sample were determined in a large-scale emission test chamber and in two micro-chambers of different volumes, and the results were compared.
Ultrasonic coda wave interferometry can detect small changes in scattering materials like concrete. We embedded ultrasonic transducers in the Gänstorbrücke Ulm, a monitored road bridge in Germany, to test the methodology. Since fall 2020, we've been monitoring parts of the bridge and comparing the results to commercial monitoring systems. We calculate signal and volumetric velocity changes using coda waves, and long-term measurements show that the influence of temperature on strains and ultrasound velocity changes can be monitored. Velocity change maps indicate that different parts of the bridge react differently to environmental temperature changes, revealing local material property differences. A load experiment with trucks allows calibration to improve detectability of possibly damaging events. Our work focuses on measurement reliability, potential use of and distinction from temperature effects, combination with complementary sensing systems, and converting measured values to information for damage and life cycle assessment.
Ultrasonic coda wave interferometry can detect small changes in scattering materials like concrete. We embedded ultrasonic transducers in the Gänstorbrücke Ulm, a monitored road bridge in Germany, to test the methodology. Since fall 2020, we've been monitoring parts of the bridge and comparing the results to commercial monitoring systems. We calculate signal and volumetric velocity changes using coda waves, and long-term measurements show that the influence of temperature on strains and ultrasound velocity changes can be monitored. Velocity change maps indicate that different parts of the bridge react differently to environmental temperature changes, revealing local material property differences. A load experiment with trucks allows calibration to improve detectability of possibly damaging events. Our work focuses on measurement reliability, potential use of and distinction from temperature effects, combination with complementary sensing systems, and converting measured values to information for damage and life cycle assessment.
Accurate and precise isotope ratio measurements of heavy elements are playing an increasinglyimportant role in modern analytical sciences and have numerous applications. Today, isotope ratio measurements are typically performed with two principal techniques: thermal ionization mass spectrometry (TIMS) and multiple collector-inductively coupled plasma mass spectrometry (MC-ICP-MS). To obtain accurate results by mass spectrometry, isotopic certified reference materials (iCRMs) are needed for mass bias correction and for the validation of the method used for analysis.Thus, it is of paramount importance to achieve measurement comparability of all data reported, and to assess measurement capability of each CRM producer/National Metrology Institute (NMI). Therefore, the international comparison (CCQM-P213) was performed to assess the analytical capabilities of NMIs for the accurate determination of copper isotope ratio delta values in high purity materials. The study was proposed by the coordinating laboratories, National Research Council Canada (NRC), National Institute of Standards and Technology (NIST), Bundesanstalt für Materialforschung und -prüfung (BAM) and Physikalisch-Technische Bundesanstalt (PTB), as an activity of the Isotope Ratio Working Group (IRWG) of the Consultative Committee for Amount of Substance - Metrology in Chemistry and Biology (CCQM). Participants included six NMIs and one designated institute (DI) from the six countries. Although no measurement method was prescribed by the coordinating laboratories, MC-ICP-MS with either standard-sample bracketing (SSB) or combined SSB with internal normalization (C-SSBIN) models for mass bias correction were recommended. Results obtained from the six NMIs and one DI were in good agreement.
This study describes an interlaboratory comparison (ILC) among nine (9) laboratories to evaluate and validate the standard operation procedure (SOP) for single-particle (sp) ICP-TOFMS developed within the context of the Horizon 2020 project ACEnano. The ILC was based on the characterization of two different Pt nanoparticle (NP) suspensions in terms of particle mass, particle number concentration, and isotopic composition. The two Pt NP suspensions were measured using icpTOF instruments (TOFWERK AG, Switzerland).
Two Pt NP samples were characterized and mass equivalent spherical sizes (MESSs) of 40.4 ± 7 nm and 58.8 ± 8 nm were obtained, respectively. MESSs showed <16% relative standard deviation (RSD) among all participating labs and <4% RSD after exclusion of the two outliers. A good agreement was achieved between the different participating laboratories regarding particle mass, but the particle number concentration results were more scattered, with <53% RSD among all laboratories, which is consistent with results from previous ILC studies conducted using ICP-MS instrumentation equipped with a sequential mass spectrometer. Additionally, the capabilities of sp-ICP-TOFMS to determine masses on a particle basis are discussed with respect to the potential for particle density determination. Finally, because quasi-simultaneous multi-isotope and multielement determinations are a strength of ICP-TOFMS instrumentation, the precision and trueness of isotope ratio determinations were assessed. The average of 1000 measured particles yielded a precision of below ±1% for intensity ratios of the most abundant Pt isotopes, i.e. 194Pt and 195Pt, while the accuracy of isotope ratios with the lower abundant isotopes was limited by counting statistics.
Per- and polyfuoroalkyl substances (PFAS) are emerging organic pollutants and can occur in surface and groundwater. To identify the degree of pollution in surface water with PFAS, often targeted HPLC–ESI–MS/MS has been employed in which commonly 30–40 compounds are analyzed. However, other PFAS and organofuorines remain undetected. We sampled surface water of the river Spree and the Teltow Canal in Berlin, Germany, which are afected by the efuent discharge of wastewater treatment plants. Here, we employed high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) for measuring extractable organofuorines (EOF) and compared in a mass balance approach the total fuorine to the identifed and quantifed PFAS from the targeted analysis. The analysis highlights that the EOF are in the range expected for an urban river system (Winchell et al. in Sci Total Environ 774, 2021). However, downstream of an efuent discharge, the EOF increased by one order of magnitude, e.g., 40.3 to 574 ng F L−1, along the Teltow Canal. From our target analytes, mostly short-chained perfuorinated carboxylic acids and sulfonates occur in the water, which however makes up less than 10% of the EOF. The increase in EOF in the Teltow Canal correlates well with the increase of perfuorohexanoic acid (PFHxA), indicating that PFHxA is characteristic for the discharged EOF but not responsible for the increase. Hence, it points to PFHxA precursor discharge. The study highlights that EOF screening using HR-CS-GFMAS is necessary to identify the full scale of pollution with regard to PFAS and other organofuorines such as pharmaceutical compounds from the efuent of WWTPs.
Wasserstoff als flexibel einsetzbarer und leicht transportierbarer Energieträger bildet eine Schlüsselkomponente auf dem Weg zu einer klimaneutralen Energiewende. Zur Speicherung von gasförmigem Wasserstoff kommen bei stationären und auch mobilen Anwendungen meist Druckbehälter aus Verbundwerkstoffen zum Einsatz. Dabei ist für den Betrieb der Behälter die Gewährleistung der Sicherheit von großer Relevanz. Structural Health Monitoring (SHM) bietet einen innovativen Ansatz, um sowohl die Sicherheit als auch die Zuverlässigkeit der Druckbehälter zu gewährleisten und kritische Versagensfälle zu vermeiden.
Zur kontinuierlichen Überwachung und Bewertung des Zustands eines Wasserstoffdruckbehälters wird in dem vorliegenden Beitrag eine aktive Methode präsentiert, die auf geführten Ultraschallwellen basiert. Dabei kommt das Pitch-Catch Verfahren zwischen Sender und Empfängern zur Überwachung der strukturellen Integrität zum Einsatz. Auf Grundlage des untersuchten Wellenausbreitungsverhaltens im Druckbehälter sowie der Geometrieeigenschaften wird ein Sensornetzwerk aus piezoelektrischen Flächenwandlern (PZT) zur Abdeckung des zu überwachenden Bereichs entworfen. Ziel ist es mit Hilfe eines Optimierungsalgorithmus eine größtmögliche Abdeckung bei gleichzeitiger Minimierung der Anzahl der Sensoren zu erreichen. Zudem soll eine gleichmäßige und platzsparende Verteilung im Vordergrund stehen, so dass zukünftig weitere Messmethoden auf dem Druckbehälter angewendet werden können (z. B. durch akustische oder faseroptische Sensoren).
Das für die Anwendung optimierte Sensornetzwerk wird anschließend hinsichtlich der Robustheit bei der Schadenserkennung und -lokalisierung durch Aufbringen von künstlichen Schäden evaluiert. Die Ergebnisse zeigen, dass die künstlichen Schäden am Wasserstoffdruckbehälter nachgewiesen werden können.
This presentation provides a short introduction to the Commission on Isotopic Abundances and Atomic Weights (CIAAW). It describes the role of the Commission and provides an insight into its work and the corresponding principal tasks. Finally, it provides the reader with the latest achievements and with the most recent publications.
Iron isotopes are used in a variety of fields from e.g., geologic question to medical applications. Measurements of iron isotopes are usually performed as delta measurements to an artificial based delta zero standard. In the case of Fe isotopes is that delta zero standard IRMM-014, a pure Fe metal. Unfortunately, that conventional delta zero reference material defining the 56/54Fe scale is out of stock and therefore unavailable. To overcome that situation and fulfill the need for laboratories that measure Fe isotope on a regular basis we will provide a set of solutions with IRMM-014 and a second anchor point for Fe isotope ratio measurements that is based on a pure Fe metal. This new second anchor point, a high purity Fe from BAM, will be calibrated against IRMM-014 and can be used as bracketing standard or as reference value for stable Fe isotope measurements.
We are in the good situation that BAM ordered a large stock of IRMM-014 several years ago. That stock of IRMM-014 Fe cubes and IRMM-014 Fe wires will be dissolved in 6M HCl in a large quantity. The new anchor point, the high purity Fe metal, that is commercially available at BAM, is a pure Fe metal with only trace amounts of impurities. The high purity BAM material will also be dissolved in 6M HCl in large quantity. Several aliquots of both solutions will be measured on the Neptune Plus MC-ICP-MS to define this second anchor point with a low uncertainty. Further will we send several aliquots of both solutions to different laboratories to also measure this second anchor point of high purity Fe on the 56/54Fe scale.
We will report the values of that study on BAM high purity Fe and will provide a guide for scale conversion to the IRMM-014 scale and for uncertainty calculation to use that new anchor point instead of the exhausted IRMM-014.
The variation of isotope ratios is increasingly used to unravel natural and technical questions. With new upcoming techniques and research topics in the last two decades, such as material provenance or food authenticity to animal and human migration studies, the number of published isotope data has strongly increased. Here, isotope reference materials are indispensable to enable a reliable method validation or even SI-traceability. The fast development and broad availability of inductively coupled plasma mass spectrometry instrumentation (ICP-MS) also lead to an expansion of the classical research areas and new elements are under investigation. Owing to this large expansion of the field, the production and certification of isotope reference materials for calibration and validation is lagging behind, even for classical applications such as conventional 87Sr/86Sr isotope ratio analysis. To improve this situation, BAM organized an interlaboratory comparison (ILC) comprising of thirteen international laboratories for the characterisation of 87Sr/86Sr isotope ratios in geochemical and industrial reference materials. Six reference materials (four cements and two rocks) were provided as powder requiring extensive sample preparation prior to isotopic measurement. Additional requirements included the use of the conventional method for obtaining 87Sr/86Sr isotope ratios, also known as radiogenic 87Sr/86Sr isotope ratios, and the assessment of the measurement uncertainty. The primary goal was to evaluate potential differences in the application of multicollector thermal ionization mass spectrometry (MC-TIMS) and multicollector inductively coupled plasma mass spectrometry (MC-ICP-MS) for conventional 87Sr/86Sr isotope ratio determination, with a secondary goal to provide reference values for the 87Sr/86Sr isotope ratios in these potential new reference materials. All reported results are accompanied by an uncertainty statement and are traceable to the conventional method, which will be described in detail within this presentation. Current state-of-the-art statistical models were used to ensure the proper evaluation of the reported results and their associated measurement uncertainties within the frame of this ILC. Combined with results from appropriate homogeneity assessment, reference values for 87Sr/86Sr isotope ratios will be assigned.
Round robin tests of odour and VOC emissions from building products – What have we learned so far?
(2023)
Emission testing of volatile organic compounds (VOC) and odour from materials and products is commonly based on emission test chamber measurements. These measurements are often the basis of mandatory or voluntary labelling procedures. To ensure the comparability of results from different testing laboratories their performance must be verified. For this purpose, round robin tests (RRTs) are conducted. Bundesanstalt für Materialforschung und - prüfung (BAM) offers such a RRT every two years using well characterised test materials with defined VOC emissions. In addition to the VOC quantification, the evaluation of odour is also implemented in the round robin tests. At the beginning, only perceived intensity (PI) was tested but over the years also the acceptance evaluation was considered. In principle, the results of PI and acceptance evaluation are comparable. The advantage of PI is the lower number of panel members necessary for one evaluation.
An interlaboratory comparison (ILC)was organised to characterise 87Sr/86Sr isotope ratios in geological and industrial reference materials by applying the so-called conventional method for determining 87Sr/86Sr isotope ratios. Four cements (VDZ 100a,VDZ 200a, VDZ 300a, IAG OPC-1), one limestone (IAG CGL ML-3) and one slate (IAG OU-6) reference materials were selected, covering a wide range of naturally occurring Sr isotopic signatures. Thirteen laboratories received aliquots of these six reference materials together with a detailed technical protocol. The consensus values for the six reference materials and their associated measurement uncertainties were obtained by applying a Gaussian, linear mixed effects model fitted to all the measurement results. By combining the consensus values and their uncertainties with an uncertainty contribution for potential heterogeneity, reference values ranging from 0.708134 mol mol-1 to 0.729778 mol mol-1 were obtained with relative expanded uncertainties of ≤ 0.007 %. This study represents an ILC on conventional 87Sr/86Sr isotope ratios, within which metrological principles were considered and the compatibility of measurement results obtained by MC-ICP-MS and by MC-TIMS is demonstrated. The materials characterised in this study can be used as reference materials for validation and quality control purposes and to estimate measurement uncertainties in conventional 87Sr/86Sr isotope ratio measurement.
This study uses conventional 87Sr/86Sr and 143Nd/144Nd isotope and interelement ratios of Ca, Sr, K, Mn, Mg and Ti as fingerprints for provenancing ordinary Portland cements (OPC). Herein, the first database of Sr and Nd isotope ratios investigated in OPCs, stemming from 29 cement plants located worldwide, was created. The results show that the Sr isotope ratios of OPCs are higher than those of seawater from the observed geological period. The spread of 143Nd/144Nd in OPCs is not as large as the spread for 87Sr/86Sr isotope ratios. However, the combination of both Sr and Nd isotope ratios provides the potential for distinguishing between cements of different production sites. Most of the OPCs investigated have measurable differences in their 87Sr/86Sr and 143Nd/144Nd isotope ratios, which can be employed as a valuable analytical fingerprinting tool. In the case of equivocal results, divisive hierarchical clustering was employed to help overcome this issue. The construction of geochemical profiles allowed the computing of suitably defined distances between cements and clustering them according to their chemical similarity. By applying this methodology, successful fingerprinting was achieved in 27 out of the 29 ordinary Portland cements that were analysed.
Guided wave ultrasonic features in composite overwrapped pressure vessels towards digital twin
(2023)
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
Per- and polyfluoroalkyl substances (PFAS) are widely used for durable water-repellent finishing of different fabrics and textiles like outdoor clothing, carpets, medical textiles and more. Existing PFAS extraction techniques followed by target analysis are often insufficient in detecting widely used side-chain fluorinated polymers (SFPs) that are barely or non-extractable. SFPs are typically copolymers consisting of a non-fluorinated backbone with perfluoroalkyl side-chains to obtain desired properties. We compared the accessible analytical information and performance of complementary techniques based on oxidation (dTOP assay, PhotoTOP), hydrolysis (THP assay), standard extraction, extractable organic fluorine (EOF), and total fluorine (TF) with five functional textiles and characterized 7 further textiles only by PhotoTOP oxidation. The results show that when applied directly to textile samples, oxidation by dTOP and PhotoTOP and also hydrolysis by the THP are able to capture large fractions of the TF in form of perfluoroalkyl side-chains present in the textiles while methods relying on extracts (EOF, target and non-target analysis) were much lower (e.g., factor ~25-50 lower). The conversion of large fractions of the measured TF into PFCAs or FTOHs from fluorinated side chains is in contrast to previous studies. Concentrations ranged from <LOQ to over ~1000 mg F/kg after oxidation/hydrolysis and <LOQ to over 2000 mg F/kg for TF, while EOF and target PFAS in extracts were detected at much lower concentrations (up to ~ 60 mg F/kg) (amount of fluorine in the order: extraction << EOF << oxidation/hydrolysis ≤ TF). Perfluoroalkyl carboxylic acids (PFCAs) and fluorotelomer alcohols (FTOHs) from THP and PhotoTOP both represented the chain-length distribution in the textiles showing that long-chain SFPs are still used in current textiles. Further advantages and disadvantages of the applied methods are discussed.
Mistle: bringing spectral library predictions to metaproteomics with an efficient search index
(2023)
Motivation: Deep learning has moved to the forefront of tandem mass spectrometry-driven proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still, at this point spectral prediction is mainly used to validate database search results or for confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted to large search space problems that often occur in metaproteomics or proteogenomics.
Results: In this study, we showcase a workflow that uses Prosit for spectral library predictions on two common metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Hence, the workflow emulates a classic protein sequence database search with protein digestion but builds a searchable index from spectral predictions as an in-between step.
We compare Mistle to popular search engines, both on a spectral and database search level, and provide evidence that this approach is more accurate than a database search using MSFragger. Mistle outperforms other spectral library search engines in terms of run time and proves to be extremely memory efficient with a 4- to 22-fold decrease in RAM usage. This makes Mistle universally applicable to large search spaces, e.g. covering comprehensive sequence databases of diverse microbiomes.
Availability and implementation: Mistle is freely available on GitHub at https://github.com/BAMeScience/Mistle.
Human factors (HF) are little understood, and particularly in non-destructive testing (NDT) experimental data is rare, samples are often small, and statistical methods are rarely used to evaluate results. HF have been widely implicated in major occurrences of technical failure, for example at North Anna Power Plant and on United Airlines Flight 232. Understanding HF is vital for reliable detection and prevention of failures. Reliability assessments, though known to be affected by intrinsic capability, application factors, and HF, have thus far only concentrated to a sufficient degree on intrinsic capability. The addition of HF to that assessment has proven difficult due to the lack of a method of quantifying HF. This paper presents the first attempt from a psychological perspective to quantify HF from qualitative data.
HF data was derived from qualitative human-oriented Failure Modes and Effects Analysis (Human-FMEA) workshops for visual inspection of tunnels by laser scanning and for ultrasonic testing of welds. Data was collected on human failure modes, causes, consequences and preventive measures, as well as eliciting a risk priority number (RPN). Using this data, a system of quantitative weightings was created to allocate errors to inductively derived HF categories for further allocation to existing HF categorisation models.
This weighting model proved useful for creating quantitative summaries of HF, informing and validating qualitative FMEA results, and comparing existing HF categorisation models. Further potential lies within a planned interface to quantitative reliability assessment methods such as POD (Probability of Detection). While providing quantifications, the method retains a qualitative and holistic nature, can, thus, bridge the gap between psychological and engineering concerns of HF and reliability, contributing to future interdisciplinary work.
Capillary active interior insulation materials are an important approach to minimize energy losses of historical buildings. A key factor for their performance is a high liquid conductivity, which enables redistribution of liquid moisture within the material. We set up an experiment to investigate the development of moisture profiles within two different interior insulation materials, calcium-silicate (CaSi) and expanded perlite (EP), under constant boundary conditions. The moisture profiles were determined by two different methods: simple destructive sample slicing with subsequent thermogravimetric drying as well as non-destructive NMR measurements with high spatial resolution. The moisture profiles obtained from both methods show good agreement, when compared at the low spatial resolution of sample slicing, which demonstrates the reliability of this method. Moreover, the measured T2- relaxation-time distributions across the sample depth were measured, which may give further insight into the saturation degree of the different pore sizes. In order to explain differences in the moisture profiles between CaSi and EP, we determined their pore-size distribution with different methods: conversion of the NMR T2 relaxationtime distribution at full saturation, mercury intrusion porosimetry and indirect determination from pressure plate measurements. CaSi shows a unimodal distribution at small pore diameters, while in EP, a bi-modal or wider distribution was found. We assume that the smaller pore diameters of CaSi lead to a higher capillary conductivity, which causes a more distributed moisture profile in comparison with that of EP.
Capillary active interior insulation materials are an important approach to minimize energy losses of historical buildings. A key factor for their performance is a high liquid conductivity, which enables redistribution of liquid moisture within the material. We set up an experiment to investigate the development of moisture profiles within two different interior insulation materials, calcium-silicate (CaSi) and expanded perlite (EP), under constant boundary conditions. The moisture profiles were determined by two different methods: simple destructive sample slicing with subsequent thermogravimetric drying as well as non-destructive NMR measurements with high spatial resolution. The moisture profiles obtained from both methods show good agreement, when compared at the low spatial resolution of sample slicing, which demonstrates the reliability of this method. Moreover, the measured T2-relaxation-time distributions across the sample depth were measured, which may give further insight into the saturation degree of the different pore sizes. In order to explain differences in the moisture profiles between CaSi and EP, we determined their pore-size distribution with different methods: conversion of the NMR T2 relaxationtime distribution at full saturation, mercury intrusion porosimetry and indirect determination from pressure plate measurements. CaSi shows a unimodal distribution at small pore diameters, while in EP, a bi-modal or wider distribution was found. We assume that the smaller pore diameters of CaSi lead to a higher capillary conductivity, which causes a more distributed moisture profile in comparison with that of EP.
Regardless of the experimental care practiced in acquiring X-ray computed tomography (XCT) data, artifacts might still exist, such as noise and blur. This is typical for fast XCT data acquisitions (e.g., in-situ investigations), or low-dose XCT. Such artifacts can complicate subsequent analysis of the data. Digital filters can moderately cure extensive artifacts. The selection of filter type, intensity, and order of application is not always straight forward. To tackle these problems, a complete sequential multilevel, multi-scale framework: BAM SynthCOND, employing newly designed deep convolutional neural networks (DCNNs), was formulated. Although data conditioning with neural networks is not uncommon, the main complication is that completely artifact-free XCT data for training do not exist. Thus, training data were acquired from an in-house developed library (BAM SynthMAT) capable of generating synthetic XCT material microstructures. Some novel DCNN architectures were introduced (2D/3D ACEnet_Denoise, 2D/3D ACEnet_Deblur) along with the concept of Assertive Contrast Enhancement (ACE) training, which boosts the performance of neural networks trained with continuous loss functions. The proposed methodology accomplished very good generalization from low resemblance synthetic training data. Indeed, denoising, sharpening (deblurring), and even ring artifact removal performance were achieved on experimental post-CT scans of challenging multiphase Al-Si Metal Matrix Composite (MMC) microstructures. The conditioning efficiencies were: 92% for combined denoising/sharpening, 99% for standalone denoising, and 95% for standalone sharpening. The results proved to be independent of the artifact intensity. We believe that the novel concepts and methodology developed in this work can be directly applied on the CT projections prior to reconstruction, or easily be extended to other imaging techniques such as: Microscopy, Neutron Tomography, Ultrasonics, etc.
For a long time, the rule of thumb for active thermography as a non-destructive testing method was that the resolution of internal defects/inhomogeneities is limited to a ratio of defect depth/defect size ≤ 1. This is due to the diffusive nature of thermal conduction in solids. So-called super resolution approaches have recently allowed this physical limit to be overcome many times over. This offers the attractive possibility of developing thermography from a purely near surface-sensitive testing method to one with improved depth range. How far this development can be pushed is the subject of current research.
We have already been able to show that this classical limitation for one- and two-dimensional defect geometries can be overcome by illuminating the test object sequentially in a structured manner with individual laser spots and thus subsequently calculating a defect map from the resulting measurement data by applying photothermal super resolution reconstruction, which allows significantly improved separation of individual closely spaced defects. As a result, this method benefits strongly from the combination of sequential spatially structured illumination and modern numerical optimization methods, which come at the expense of higher experimental complexity. This leads to long measurement times, large data sets, and tedious numerical analysis, in contrast to the application of established standard thermographic methods with homogeneous illumination.
In this work, we report on the application of full-area spatially structured two-dimensional illumination patterns, which, by applying state-of-the-art laser projector technology in conjunction with a high-power laser, makes it possible to achieve an efficient implementation of photothermal super-resolution reconstruction even for larger test areas in the first place.
Since its isolation, graphene has received growing attention from academia and industry due to its unique properties. However, the “what is my material” barrier hinders further commercialization. X-ray photoelectron spectroscopy (XPS) is considered as a method of choice for the determination of the elemental and chemical composition. In this work the influence of the morphology of graphene particles on the XPS results is studied and investigated as a function of X-ray energy, using conventional XPS with Al K𝜶 radiation and hard X-ray photoemission spectroscopy (HAXPES) using Cr K𝜶 radiation. Thereby, the information depth is varied between 10 and 30 nm. For this purpose, two commercial powders containing graphene nanoplatelets with lateral dimensions of either ≈100 nm or in the micrometer range are compared. These larger ones exist as stack of graphene layers which is inspected with scanning electron microscopy. Both kinds of particles are then functionalized with either oxygen or fluorine. The size of the graphene particles is found to influence the degree of functionalization. Only the combination of XPS and HAXPES allows to detect the functionalization at the outermost surface of the particles or even of the stacks and to provide new insights into the functionalization process.
International standards describing reliable protocols will facilitate the commercialization of graphene and related 2D materials. One physico-chemical key property next to flake size and thickness is the chemical composition of the material. Therefore, an ISO standard is under development with X-ray photoelectron spectroscopy having a prominent role. With its information depth of around 10 nm which is the similar length scale as the thickness as of particles of 2D materials consisting of a few monolayer XPS seems to be highly suitable for this purpose. Different sample preparation methods like pressing the powders onto adhesive tapes, into recesses, or into solid pellets result in inconsistencies in the quantification. For the validation of the quantification with XPS an interlaboratory comparison was initiated under the auspice of the “Versailles Project on Advanced Materials and Standards” (VAMAS). First results confirm that the sample preparation method (pellet vs. powder) influences the quantification results clearly.
The datasets from (Hard Energy) X-ray photoelectron spectroscopy, X-ray diffraction and Scanning Electron Microsopy are related to the publication
G. Chemello, X. Knigge, D. Ciornii, B.P. Reed, A.J. Pollard, C.A. Clifford, T. Howe, N. Vyas, V.-D. Hodoroaba, J. Radnik
"Influence of the morphology on the functionalization of graphene nanoplatelets analyzed by comparative photoelectron spectroscopy with soft and hard X-rays"
Advanced Materials Interfaces (2023), DOI: 10.1002/admi.202300116.
International standards describing reliable protocols will facilitate the commercialization of graphene and related 2D materials. One physico-chemical key property next to flake size and thickness is the chemical composition of the material. Therefore, an ISO standard is under development with X-ray photoelectron spectroscopy having a prominent role. With its information depth of around 10 nm which is the similar length scale as the thickness as of particles of 2D materials consisting of a few monolayer XPS seems to be highly suitable for this purpose. Different sample preparation methods like pressing the powders onto adhesive tapes, into recesses, or into solid pellets result in inconsistencies in the quantification. For the validation of the quantification with XPS an interlaboratory comparison was initiated under the auspice of the “Versailles Project on Advanced Materials and Standards” (VAMAS). First results confirm that the sample preparation method (pellet vs. powder) influences the quantification results clearly. Considering this effect, a good agreement of the results from the different participants were observed. Similar results were observed for raw, N- and F-functionalized graphene.
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.
Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.
Modular chemical production is a tangible implementation of the digital transformation of the specialty chemicals process industry. In particular, it enables acceleration of process development and thus faster time to market by flexibly interconnecting and orchestrating standardized physical modules and bringing them to life. For this purpose, specific (chemical) sensors of process analytics are needed, preferably without lengthy calibration or spectroscopic model development.
An excellent example of a "direct" analytical method is online nuclear magnetic resonance (NMR) spectroscopy. NMR spectroscopy meets the requirements of a direct analytical method because of the direct correlation between the signal area in the spectrum ("counting" the nuclear spins) and the analyte amount of substance concentrations. It is also extremely linear over the concentration range.
With the availability of compact benchtop NMR instruments, it is now possible to bring NMR spectroscopy directly into the field, in close proximity to specialized laboratory facilities, pilot plants, and even industrial-scale production facilities. The first systems are in TRL 8 (Qualified System with Proof of Functionality in the Field).
The presentation will discuss the many building blocks of online nuclear magnetic resonance spectroscopy, from flow cells to automated data analysis.
Although layer-based additive manufacturing methods such as laser powder bed fusion (PBF-LB) offer an immense geometrical freedom in design, they are typically subject to a build-up of internal stress (i.e. thermal stress) during manufacturing. As a consequence, significant residual stress (RS) is retained in the final part as a footprint of these internal stresses. Furthermore, localized melting and solidification inherently induce columnar-type grain growth accompanied by crystallographic texture. Although diffraction-based methods are commonly used to determine the RS distribution in PBF-LB parts, such features pose metrological challenges in their application. In theory, preferred grain orientation invalidates the hypothesis of isotropic material behavior underlying the common methods to determine RS. In this work, more refined methods are employed to determine RS in PBF-LB/M/IN718 prisms, based on crystallographic texture data. In fact, the employment of direction-dependent elastic constants (i.e. stress factors) for the calculation of RS results in insignificant differences from conventional approaches based on the hypothesis of isotropic mechanical properties. It can be concluded that this result is directly linked to the fact that the {311} lattice planes typically used for RS analysis in nickel-based alloys have high multiplicity and less strong texture intensities compared with other lattice planes. It is also found that the length of the laser scan vectors determines the surface RS distribution in prisms prior to their removal from the baseplate. On removal from the baseplate the surface RS considerably relaxes and/or redistributes; a combination of the geometry and the scanning strategy dictates the sub-surface RS distribution.
Quantitative Analysis and 2D/3D Elemental Imaging of Cocoa Beans Using X‑ray Fluorescence Techniques
(2023)
As an important raw material for the confectionery industry, the cocoa bean (Theobroma cacao L.) has to meet certain legal requirements in terms of food safety and maximum contaminant levels in order to enter the cocoa market. Understanding the enrichment and distribution of essential minerals but also toxic metals is of utmost importance for improving the nutritional quality of this economically important raw food material. We present three X-ray fluorescence (XRF) techniques for elemental bio-imaging of intact cocoa beans and one additional XRF technique for quantitative analysis of cocoa pellets. The interrelation of all the methods presented gives a detailed picture of the content and 3D-resolved distribution of elements in complete cocoa beans for the first time.
This dataset represents the electronic supplementary material (ESM) of the publication entitled "Characterisation of conventional 87Sr/86Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study", which is published in Geostandards and Geoanalytical Research under the DOI: 10.1111/GGR.12517. It consists of four files. 'ESM_Data.xlsx' contains all reported data of the participants, a description of the applied analytical procedures, basic calculations, the consensus values, and part of the uncertainty assessment. 'ESM_Figure-S1' displays a schematic on how measurements, sequences and replicates are treated for the uncertainty calculation carried out by PTB. 'ESM_Technical-protocol.pdf' is the technical protocol of the interlaboratory comparison, which has been provided to all participants together with the samples and which contains bedside others the definition of the measurand and guidelines for data assessment and calculations. 'ESM_Reporting-template.xlsx' is the Excel template which has been submitted to all participants for reporting their results within the interlaboratory comparison. Excel files with names of the the structure 'GeoReM_Material_Sr8786_Date.xlsx' represent the Rcon(87Sr/86Sr) data for a specific reference material downloaded from GeoReM at the specified date, e.g. 'GeoReM_IAPSO_Sr8786_20221115.xlsx' contains all Rcon(87Sr/86Sr) data for the IAPSO seawater standard listed in GeoReM until 15 November 2022.
The huge atomic heterogeneity of high-entropy materials along with a possibility to unravel the behavior of individual components at the atomic scale suggests a great promise in designing new compositionally complex systems with the desired multi-functionality. Herein, we apply multi-edge X-ray absorption spectroscopy (extended X-ray absorption fine structure (EXAFS), X-ray absorption near edge structure (XANES), and X-ray magnetic circular dichroism (XMCD)) to probe the structural, electronic, and magnetic properties of all individual constituents in the single-phase face-centered cubic (fcc)-structured nanocrystalline thin film of Cr20Mn26Fe18Co19Ni17 (at.%) high-entropy alloy on the local scale. The local crystallographic ordering and component-dependent lattice displacements were explored within the reverse Monte Carlo approach applied to EXAFS spectra collected at the K absorption edges of several constituents at room temperature. A homogeneous short-range fcc atomic environment around the absorbers of each type with very similar statistically averaged interatomic distances (2.54–2.55 Å) to their nearest-neighbors and enlarged structural relaxations of Cr atoms were revealed. XANES and XMCD spectra collected at the L2,3 absorption edges of all principal components at low temperature from the oxidized and in situ cleaned surfaces were used to probe the oxidation states, the changes in the electronic structure, and magnetic behavior of all constituents at the surface and in the sub-surface volume of the film. The spin and orbital magnetic moments of Fe, Co, and Ni components were quantitatively evaluated. The presence of magnetic phase transitions and the co-existence of different magnetic phases were uncovered by conventional magnetometry in a broad temperature range.
With increasing demand and environmental concerns, researchers are exploring new materials that can perform as well or better than traditional materials while reducing environmental impact. The BAMline, a real-life sample materials research beamline, provides unique insights into materials’ electronic and chemical structure at different time and length scales. The beamline specializes in x-ray absorption spectroscopy, x-ray fluorescence spectroscopy, and tomography experiments. This enables real-time optimization of material properties and performance for various applications, such as energy transfer, energy storage, catalysis, and corrosion resistance. This paper gives an overview of the analytical methods and sample environments of the BAMline, which cover non-destructive testing experiments in materials science, chemistry, biology, medicine, and cultural heritage. We also present our own synthesis methods, processes, and equipment developed specifically for the BAMline, and we give examples of synthesized materials and their potential applications. Finally, this article discusses the future perspectives of the BAMline and its potential for further advances in sustainable materials research.
In this study, we propose the use of nondestructive, depth-resolved, element-specific characterization using grazing exit X-ray absorption near-edge structure spectroscopy (GE-XANES) to investigate the corrosion process in compositionally complex alloys (CCAs). By combining grazing exit X-ray fluorescence spectroscopy (GE-XRF) geometry and a pnCCD detector, we provide a scanning-free, nondestructive, depth-resolved analysis in a sub-micrometer depth range, which is especially relevant for layered materials, such as corroded CCAs. Our setup allows for spatial and energy-resolved measurements and directly extracts the desired fluorescence line, free from scattering events and other overlapping lines. We demonstrate the potential of our approach on a compositionally complex CrCoNi alloy and a layered reference sample with known composition and specific layer thickness. Our findings indicate that this new GE-XANES approach has exciting opportunities for studying surface catalysis and corrosion processes in real-world materials.
Mesoporous glasses are a promising class of bioresorbable biomaterials characterized by high surface area and extended porosity in the range of 2 to 50 nm. These peculiar properties make them ideal materials for the controlled release of therapeutic ions and molecules. Whilst mesoporous silicate-based glasses (MSG) have been widely investigated, much less work has been done on mesoporous phosphate-based glasses (MPG). In the present study, MPG in the P2O5–CaO–Na2O system, undoped and doped with 1, 3, and 5 mol% of Cu ions were synthesized via a combination of the sol–gel method and supramolecular templating. The non-ionic triblock copolymer Pluronic P123 was used as a templating agent. The porous structure was studied via a combination of Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), and N2 adsorption–desorption analysis at 77 K. The structure of the phosphate network was investigated via solid state 31P Magic Angle Spinning Nuclear Magnetic Resonance (31P MAS-NMR) and Fourier Transform Infrared (FTIR) spectroscopy. Degradation studies, performed in water via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), showed that phosphates, Ca2+, Na+ and Cu ions are released in a controlled manner over a 7 days period. The controlled release of Cu, proportional to the copper loading, imbues antibacterial properties to MPG. A significant statistical reduction of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) bacterial viability was observed over a 3 days period. E. coli appeared to be more resistant than S. aureus to the antibacterial effect of copper. This study shows that copper doped MPG have great potential as bioresorbable materials for controlled delivery of antibacterial ions.
Synchrotron X-ray computed tomography (SXCT) at BAMline has been paired with in-situ tensile loading to monitor damage evolution in LPBF Metal Matrix Composite (MMC) 7017 Aluminium alloy + 3 wt% Zr + 0.5 wt% TiC. The processing of the material leads formation to different categories of Zr-rich inclusions, precipitates and defects. In-situ SXCT test disclosed the critical role of the pre-cracks in the reinforcement phases in the failure mechanisms of LPBF MMC. The damage was initiated from lack-of-fusion defects and cracks propagated through coalescence with other defects.
Moisture testing and mapping
(2023)
Luminescent Nanoparticles – From Photophysics to the Measurement of Photoluminescence Quantum Yields
(2023)
Inorganic nanocrystals with linear and nonlinear photoluminescence in the ultraviolet, visible, near infrared and short-wave infrared like spectrally shifting lanthanide-based nanoparticles (LnNCs) like NaYF4: Yb, Er and semiconductor quantum dots have meanwhile found applications in the life and material sciences ranging from optical reporters for bioimaging and sensing over security barcodes to solid state lighting and photovoltaics. The identification of optimum particle architectures for photonic applications requires quantitative spectroscopic studies, ideally flanked by single particle studies to assess spectroscopic inhomogeneities on a particle-to-particle level for typical preparation methods. In the following, photoluminescence studies of LnNCs are presented, addressing parameters such as particle size, surface coating, and dopant ion concentration as well as excitation power density mandatory for a profound mechanistic understanding of the nonradiative deactivation pathways in these nanocrystals. In addition, methods for the determination of particle brightness and photoluminescence quantum yield in different spectral windows are presented.
Ionizing radiation damage to DNA plays a fundamental role in cancer therapy. X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. The results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.
In this work, we report on our progress for investigating a new experimental approach for thermographic detection of internal defects by performing 2D photothermal super resolution reconstruction. We use modern high-power laser projector technology to repeatedly excite the sample surface photothermally with varying spatially structured 2D pixel patterns. In the subsequent (blind) numerical reconstruction, multiple measurements are combined by exploiting the joint-sparse nature of the defects within the specimen using nonlinear convex optimization methods. As a result, a 2D-sparse defect/inhomogeneity map can be obtained. Using such spatially structured heating combined with compressed sensing and computational imaging methods allows to significantly reduce the experimental complexity and to study larger test surfaces as compared to the one-dimensional approach reported earlier.
In this work, the limits of using spatially structured heating combined with subsequent photothermal super resolution reconstruction for the thermographic detection and resolution of internal defects are investigated. The approach is based on the application of modern high-power laser projector technology, which is used to repeatedly project varying spatially structured 2D pixel patterns to photothermally heat the object under test. After processing the generated thermographic data using nonlinear convex optimisation in conjunction with exploiting the joint-sparse nature of the defect signals within the individual measurements, a high-resolution 2D-sparse defect/inhomogeneity map is obtained. The main focus of the investigation is set on the influence of the number of individual measurements on the achievable reconstruction quality. Using numerical simulations based on an analytical representation of the forward solution to the underlying inverse problem, the convergence rate over performed measurements of the achievable reconstruction quality is determined. Finally, all findings are experimentally validated by reconstructing a set of internal defects in an additively manufactured sample. In this work, it is shown that for a variety of different defect separation distances, the projection of 50 different pixel patterns allows for a good trade-off between experimental complexity and reconstruction quality.
This talk introduces the expanded view that comes from wide-range X-ray scattering investigations.
Compared to X-ray diffraction studies alone, the additional angular range of this technique provides information on the larger structural dimensions present in your samples. This allows for the extraction of information on the size and size distribution of nanostructural components, such as nanoparticles, nanovoids, and any other structure exhibiting an electron density contrast.
The talk introduces the technique, the MOUSE instrument used for these investigations, and provides several real-world examples of its uses. The audience is invited to choose which examples captures their interest from a range of options, in the latter segment of the talk.
It can be difficult to efficiently model ultrasonic waves in 3D structures, especially when the computational model needs to account for complex geometries. This contribution presents a solution based on the Scaled Boundary Finite Element Method (SBFEM). It is a numerical tool suitable for elastodynamic problems. A space-tree discretisation, namely quad-trees, is used. This technique allows the decomposition of an image into quadrilaterals or quads, which are extruded to generate the 3D plate geometry. In particular, small quads resolve regions with discontinuities, allowing them to represent fine details in the structure. Moreover, this meshing technique allows for exploiting cell similarities, making the calculation procedure more efficient. The space-tree discretisations are generated from a high-resolution image containing all the information about damaged regions or boundary conditions. The resulting SBFEM polyhedral domains employ transition elements to ensure correct coupling between cells of different sizes. The analytical solution of a cylindrical scatterer serves as a reference to validate the proposed approach. Other examples also demonstrate the validity of the methodology and its flexibility.
Motivation: Inferring taxonomy in mass spectrometry-based shotgun proteomics is a complex task. In multi-species or viral samples of unknown taxonomic origin, the presence of proteins and corresponding taxa must be inferred from a list of identified peptides, which is often complicated by protein homology: many proteins do not only share peptides within a taxon but also between taxa. However, the correct taxonomic inference is crucial when identifying different viral strains with high-sequence homology—considering, e.g., the different epidemiological characteristics of the various strains of severe acute respiratory syndrome-related coronavirus-2. Additionally, many viruses mutate frequently, further complicating the correct identification of viral proteomic samples.
Results: We present PepGM, a probabilistic graphical model for the taxonomic assignment of virus proteomic samples with strain-level resolution and associated confidence scores. PepGM combines the results of a standard proteomic database search algorithm with belief propagation to calculate the marginal distributions, and thus confidence scores, for potential taxonomic assignments. We demonstrate the performance of PepGM using several publicly available virus proteomic datasets, showing its strain-level resolution performance. In two out of eight cases, the taxonomic assignments were only correct on the species level, which PepGM clearly indicates by lower confidence scores.
Availability and implementation: PepGM is written in Python and embedded into a Snakemake workflow. It is available at https://github.com/BAMeScience/PepGM.
The outbreak of SARS-CoV-2 in December of 2019, led to a worldwide still on-going pandemic. Since then, several so-called waves of SARS-CoV-2 infections, a time period with a high and fast rising number of new infections, have occurred all over the world. Classic surveillance approaches are hardly applicable, and further, non-detected cases cannot be covered by them. Wastewater-based Epidemiology (WBE) was proven to be a reliable tool for the prediction of new SARS-CoV-2 infection waves, due to the discharge of virus particles in fecal shedding of infectious people. Until now, for the monitoring of SARS-CoV-2 in wastewater, Polymerase Chain Reaction (PCR) is used as analytical tool. Even though PCR is a highly sensitive analytical tool, is presents several disadvantages, such as the need for trained personnel, specific technical equipment, as well as a difficult performance. An analytical tool, to which these disadvantaged do not apply, are immunoassays. In this work, a sandwich Enzyme-Linked Immunosorbent Assay (ELISA), with the immobilization of the capture antibodies on the surface of a Microtiter Plate (MTP), as well as a sandwich Magnetic Bead-Based Assay (MBBA), with immobilization of the capture antibodies on the surface of Magnetic Beads (MBs), targeting the SARS-CoV-2 N-protein, were developed and optimized. Both assay formats were performed with a colorimetric and chemiluminescent detection. The developed assay is composed of the two monoclonal antibodies (mAb) AH2 and DE6 - which was biotinylated in the course of the work - which bind to two different epitops of the antigen N-protein. As tracer, Neutravidin-HRP was used, which binds, through interaction of the Neutravidin with the biotin, to the mAb DE6-Biotin. The assay development and optimization procedure included the investigation of the surface saturation with the mAb AH2, the concentration and dilution of the mAb DE6-Biotin and Neutravidin-HRP, the ideal MBs, the ideal coating as well as dilution buffers, and the colorimetric and chemiluminescent substrates. For the developed and fully optimized colorimetric ELISA, a test midpoint x0 of 388 μg/L, for the chemiluminsecent ELISA of 371 μg/L, for the colorimetric MBBA of 251 μg/L and for the chemiluminescent MBBA of 243 μg/L was obtained. Validation of the colorimetric MBBA was done by measurement of three wastewater samples collected at the Wastewater Treatment Plant (WWTP) Potsdam. Whilst no N-protein could be detected in the samples, by spiking of the wastewater samples with certain concentrations of the N-protein, 10- to 18-times lower concentrations could be back-calculated, which can be attributed to matrix-effects of the wastewater sample. Next to the matrix-effects, also several other reason exist, why no N-protein could be determined in the samples. Because of that, further investigation of the handling, and the measurement of the wastewater samples, as well as the improvement of the assay sensitivity through further optimization steps or exchange of the antibodies, is still necessary.
Utilizing Aspergillus niger Fumonisin Amine Oxidase for the Electrochemical Detection of Fumonisin
(2023)
Fumonisins are a class of toxic secondary metabolites produced by various Fusarium species. The two most important producers of fumonisins are F. verticillioides and F. proliferatum but also Aspergillus niger is known to produce fumonisins. Most frequently they occur on maize, but also other grains can be contaminated with this group of mycotoxins. Exposure to fumonisins by dietary intake can have serious health effects on farm animals and also within humans. Thus, the European Commission sets legal limits for fumonisins in feed and foodstuffs. The detection of fumonisins is frequently performed in laboratories by chromatographic methods, which are costly and require trained personnel. Simplifying the analysis is therefore a major goal using portable detection systems. Electrochemical enzymatic biosensors offer great promise to meet this demand. Here we report for the first time an enzymatic fumonisin sensing approach with amperometric detection. For this purpose, an Aspergillus niger fumonisin amine oxidase (AnFAO) catalyzing the oxidative deamination of fumonisins, producing hydrogen peroxide, was recombinantly produced in E. coli. It was found that the specific activity of AnFAO using 20 μM Fumonisin B1 as substrate is higher than for 20 μM Fumonisin B2 with 0.122 U mg-1 and 0.058 U mg-1, respectively. It was possible to show a dependence of enzyme activity with enzyme – and substrate-concentration. For fumonisin B1 detection, the enzyme was coupled covalently to magnetic particles and the enzymatically produced H2O2 was detected amperometrically in a flow injection system using Prussian blue carbon electrodes. The developed method allows to quantify fumonisin B1 concentrations down to 1.5 µM and demonstrates that the recombinantly produced AnFAO was able to deaminate different concentrations of fumonisin even in immobilized form. Thus, this enzyme is well suited to develop an enzyme based electrochemical biosensor for fumonisin contaminated food and feed.
Per- and polyfluoroalkyl substances (PFASs) are a group of anthropogenic contaminates associated with persistent, bioaccumulative and toxic properties. Mostly, target-based approaches (e.g., LC-MS/MS) are utilized for the analysis of PFASs in the environment. Target approaches are limited to a few selected PFASs and therefore underestimate the total PFAS burden. Analytical approaches based on total fluorine for PFAS sum parameter analysis become increasingly important to indicate realistic PFAS pollution levels.
Recently high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) turned out to be 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 in the low µg F/L range. HR-CS-GFMAS analysis can be combined with the extractable organically bound fluorine (EOF) approach whereas PFASs are extracted from liquid or solid samples using organic solvents and/or solid phase extraction (SPE).
In this presentation the applicability of HR-CS-GFMAS for organic fluorine analysis in various environmental sample including (1) water samples, (2) soil samples and (3) plant samples is demonstrated.
(1) We investigated EOF concentrations in water bodies in Berlin, Germany and used additional PFAS target analysis for a PFAS mass balance approach. EOF concentrations were in the expected range for an urban river system. However, downstream of an effluent discharge, the EOF increased by one order of magnitude from 40 to 574 ng F/L. Target analysis determined mostly short-chained perfluorinated carboxylic acids and sulfonic acids, which however only made up less than 10% of the EOF. This study highlights that EOF screening using HR-CS-GFMAS is useful and advantageous compared to target analysis to identify pollution sites in urban water systems.
(2) For soil samples, we optimized a fast and simple PFAS extraction method for EOF determination. The developed extraction method consists of a liquid-solid extraction without any additional SPE for fluoride removal. We investigated different soil samples using the optimized method with and without an additional SPE clean-up step and revealed a drastic underestimation of EOF mass fractions using SPE. The optimized method is a valuable screening tool for fast PFAS monitoring.
(3) For plant samples, we conducted a study on the uptake and fate of PFASs in bean plants. For PFAS mass balancing HR-CS-GFMAS analysis was combined with LC-MS/MS analysis. PFASs were spiked as mixtures of known and unknown composition. Short-chained PFASs were determined with high mass fractions mainly in the fruits of the investigated plants while long-chained PFASs were mainly determined in roots. Overall, both methods indicate comparable results with target analysis being more reliable for known PFAS contamination and EOF/HR-CS-GFMAS analysis being more valuable to identify PFAS exposure of unknown composition.
Comparative study of the co-assembly behaviour of 3-chloro-4-hydroxy-phenylazo dyes with DTAB
(2023)
The co-assembly of three one-fold negatively charged 3-chloro-4-hydroxy-phenylazo dyes (Yellow, Blue and Red) with the cationic surfactant dodecyltrimethylammoniumbromide (DTAB) was studied to probe dye–DTAB binding stoichiometry and assembly morphology. For each dye, phase separation was observed above a given dye : DTAB ratio with the ratio depending on the dye. While Yellow and DTAB showed liquid/liquid phase separation above Yellow : DTAB = 1 : 1.67, crystalline dye–DTAB complexes were observed for Blue–DTAB and Red–DTAB above Blue : DTAB = 1 : 2.56 and Red : DTAB = 1 : 2.94 respecively. In homogeneous solution, UV/vis spectroscopic investigations suggest stochiometries of Yellow : DTAB = 1 : 2, Blue : DTAB = 1 : 3 and Red : DTAB = 1 : 4. It was concluded, that Yellow exhibits the highest dye : DTAB binding stoichiometry in both, dye–surfactant complexes in the 2-phase region and in solution, whereas the lowest dye : DTAB binding stoichiometry was observed for Red–DTAB in both cases. The observed stoichiometries are inversely correlated to the impact dye addition has on the morphology of DTAB micelles. Generally, addition of dye to DTAB micelles leads to a reduction in spontaneous curvature of these micelles and to the formation of triaxial ellipsoidal or cylindrical micelles from oblate ellipsoidal DTAB micelles. At a DTAB concentration of 30 mM and a dye concentration of 5 mM, this effect was most pronounced for Red and least pronounced for Yellow, whilst Blue showed an intermediate effect.
X-ray photoelectron spectroscopy (XPS) is widely used for characterising the chemistry of graphene-related two-dimensional materials (GR2M), however the careful preparation of the sample for analysis is important in obtaining representative quantifications. We report an investigation by three laboratories showing that the preparation method for oxygen-functionalised graphene nanoplatelet (GNP) powders has a significant effect on the homogeneous-equivalent elemental composition measured in XPS. We show that pressing GNP powders onto adhesive tapes, into recesses, or into solid pellets results in inconsistencies in the XPS quantification. The measured oxygen-to-carbon atomic ratio from GNP pellets depends upon the die pressure used to form them and the morphology of the GNPs themselves. We recommend that powder samples of GR2Ms are pelletised prior to XPS analysis to improve repeatability and reproducibility of measurements.
Functionally graded porous scaffolds (FGPS) constructed with pores of different size arranged as spatially continuous structure based on sheet-based gyroid with three different scaling factors of 0.05, 0.1 and 0.2 were produced by electron beam powder bed fusion. The pore dimensions of the obtained scaffolds satisfy the values required for optimal bone tissue ingrowth. Agglomerates of residual powder were found inside all structures, which required post-manufacturing treatment. Using X-ray Computed Tomography powder agglomerations were visualized and average wall thickness, wall-to-wall distances, micro- and macro-porosities were evaluated. The initial cleaning by powder recovery system (PRS) was insufficient for complete powder removal. Additional treatment by dry ultrasonic vibration (USV) was applied and was found successful for gyroids with the scaling factors of 0.05 and 0.1. Mechanical properties of the samples, including quasi-elastic gradients and first maximum compressive strengths of the structures before and after USV were evaluated to prove that additional treatment does not produce structural damage. The estimated quasi-elastic gradients for gyroids with different scaling factors lie in a range between 2.5 and 2.9 GPa, while the first maximum compressive strength vary from 52.5 for to 59.8 MPa, compressive offset stress vary from 46.2 for to 53.2 MPa.
This paper reports the results of an international interlaboratory study sponsored by the Versailles Project on Advanced Materials and Standards (VAMAS) and led by the National Institute of Standards and Technology (NIST) on the measurement of water vapor sorption isotherms at 25 °C on a pelletized nanoporous carbon (BAM-P109, a certified reference material). Thirteen laboratories participated in the study and contributed nine pure water vapor isotherms and four relative humidity isotherms, using nitrogen as the carrier gas. From these data, reference isotherms, along with the 95% uncertainty interval (Uk=2), were determined and are reported in a tabular format.
Since its isolation, graphene has received growing attention from academia and industry due to its unique properties. Promising opportunities for applications are discussed in different field like electronics and optoelectronics, detection, and sensing devices, biosystems or chemical and environmental corrosion inhibition. Here, functionalization with elements like oxygen, nitrogen or fluorine can broaden the application, for example in composite materials. However, lack of generally accepted operation procedures hinders the commercialization, the so-called “what is my material” barrier. Therefore, first efforts were done to develop common, reliable, and reproducible ways to characterize the morphological and chemical properties of the industrially produced material.
In this contribution, our efforts in the development of reliable chemical characterizations protocols for functionalized graphene are presented. An ISO standard for the chemical characterization of graphene-related (GRM) is under development with X-ray photoelectron spectroscopy (XPS) having a prominent role. With its information depth of around 10 nm, which is the similar length scale as the thickness of particles of 2D materials consisting of a few monolayers, XPS seems to be highly suitable for the quantitative analysis of (functionalized) GRM. Thereby, different sample preparation methods like pressing the powders onto adhesive tapes, into recesses, or into solid pellets result in inconsistencies in the quantification. Furthermore, different morphologies like stacks of graphene layers (left figure) or irregular particles (right figure) lead to different analysis results for the chemical composition.
For the validation of the quantification with XPS and the further development of standards an international interlaboratory comparison was initiated under the head of the “Versailles Project on Advanced Materials and Standards” (VAMAS). First results are reported showing the suitability of the protocols. Finally, the XPS results are compared with the elemental composition results obtained after quantification with energy-dispersive X-ray spectroscopy (EDS) as a fast analytical method which is usually combined with electron microscopy.
Ionizing radiation damage to DNA plays a fundamental role in cancer therapy. X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. The results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.
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.
Asymmetrical Flow Field-Flow Fractionation (AF4), as a cleaning technique, was combined on-line with the multielemental analytical capabilities of an Inductively Coupled Plasma-Time of Flight-Mass Spectrometer (ICP-ToF-MS). In that manner, the heavy ionic matrix effect of untreated cells' samples can be significantly reduced. As a proof of concept, commercial baker's yeast cells were analysed.
McSAS3 is a refactored software package for fitting large batches of (X-ray or Neutron) scattering data. It uses a Monte-Carlo acceptance-rejection algorithm to optimize model parameters - ideal for analysis of size-disperse scatterers.
The refactored code can exploit multiprocessing, traceably stores (multiple) results in the output file, and allows for re-histogramming of previous optimizations. Besides analysis of large batches, it can also be integrated in automated data processing pipelines.
The live demonstration will show how to use the software, what its limitations are, and what outcomes can look like for batches of results.
We investigated the performance of nitrogen microwave inductively coupled atmospheric-pressure plasma mass spectrometry (MICAP-MS) under matrix effects and its applicability to trace element analysis in steels. Influences of different gas flows and ion optics on the matrix tolerance are studied, indicating that nebulizer gas flow has the most significant impact. Optimization of ion optics improves matrix tolerance for light elements due to the reduction of the inelastic collisional scattering effect. With optimized operating conditions, MICAP-MS achieves an internal standard intensity recovery of over 90% at an Fe concentration of 500 mg L−1. Even at an Fe concentration of 1 g L−1, the recovery remains above 80%. Three certified reference materials – non-alloy, low-alloy and high-alloy steel – were analyzed using MICAP-MS. The determined mass concentrations of the trace and minor components show metrological compatibility to the reference values. No significant differences are observed between the results obtained with aqueous and matrix-matched calibration, demonstrating the strong matrix tolerance of MICAP-MS, and its promising applicability to steel analysis.
Cardiac troponin I (cTnI) is a crucial biomarker for diagnosing cardiac vascular diseases, including acute myocardial infarction (AMI). This study presents a proof-of-concept chemiluminescence-based immunosensor for rapid and accurate measurement of cTnI, with the potential for online monitoring. The immunosensor incorporates a flow cell design and a sensitive complementary metal-oxide-semiconductor (CMOS) camera for optical readout. A microfluidic setup was established to enable selective and quasi-online determination of cTnI within ten minutes. The sensor was tested with recombinant cTnI in phosphate buffer, demonstrating measurements in the concentration range of 2–25 µg/L, with a limit of detection (LoD) of 0.6 µg/L (23 pmol/L) achieved using the optimized system. The immunosensor exhibited high selectivity, as no cross-reactivity was observed with other recombinant proteins such as cTnT and cTnC at a concentration of 16 µg/L. Measurements with diluted blood plasma and serum yielded an LoD of 60 µg/L (2.4 nmol/L) and 70 µg/L (2.9 nmol/L), respectively. This biosensor offers a promising approach for the rapid and sensitive detection of cTnI, contributing to the diagnosis and management of acute myocardial infarction and other cardiac vascular diseases.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
Creep-resistant steels such as the 13CrMoV9-10, used in the construction of thick-walled pressure vessels, are most commonly submerged arc welded (SAW). These steels can develop stress relief cracks (SRC) if the mandatory post weld heat treatment (PWHT) is performed improperly. Current PWHT parameters, such as heating rate and holding time at a specific holding temperature, are based on both empirical experience and conventional free shrinking welding experiments to characterize the SRC-susceptibility of the weld. These cannot adequately depict the higher residual stresses caused by the structurally induced stiffness of the surrounding construction. This study discusses the development of a repeatable, precise, and time-efficient methodology to study the effects of different stress levels and heating rates on the SRC susceptibility of the coarse grain heat-affected zone (CGHAZ). For that purpose, samples were thermically treated to simulate a coarse grain heat-affected zone (CGHAZ) and subsequently exposed to representative levels of stress during the heating phase of a PWHT. The recorded stress and heating rate–dependent strains were mathematically analyzed via curve tracing/calculus to identify interdependent effects. This procedure facilitates the measurement of material characteristics such as carbide growth on grain boundaries at the µm-scale via an integrated value over the entire sample volume. The first and second derivatives show a slight, precipitate-dependent, increase in hardness of the sample, depending on the heating rate and applied stress. This new methodology generates an improved assessment of the SRC susceptibility of SAW microstructures of creep-resistant CrMoV steels.
The complex nature of liquid water saturation of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs) greatly affects the device performance. To investigate this problem, we present a method to quantify the presence of liquid water in a PEFC CL using small-angle X-ray scattering (SAXS). This method leverages the differences in electron densities between the solid catalyst matrix and the liquid water filled pores of the CL under both dry and wet conditions. This approach is validated using ex situ wetting experiments, which aid the study of the transient saturation of a CL in a flow cell configuration in situ. The azimuthally integrated scattering data are fitted using 3D morphology models of the CL under dry conditions. Different wetting scenarios are realized in silico, and the corresponding SAXS data are numerically simulated by a direct 3D Fourier transformation. The simulated SAXS profiles of the different wetting scenarios are used to interpret the measured SAXS data which allows the derivation of the most probable wetting mechanism within a flow cell electrode.
While the synthesis of Metal-Organic Framework (MOF) particles can be as easy as adding two solutions together, reproducibly obtaining the same particles, time and time again, is a lot harder. As laboratory-independent reproducibility is a cornerstone of the scientific method, we must put effort into finding and controlling all necessary parameters to achieve this.
An open-source Python/EPICS-controlled robotic platform (see picture) was adapted to systematically explore this for a 20 ml MOF synthesis of the Zeolitic Imidazole Framework-8 (ZIF-8) chemistry in methanol. Parameters that were explored included: 1) addition sequence, 2) addition speeds, 3) reaction times, 4) source chemicals, 5) stirring speeds, 6) stirring bar choice, 7) starting concentrations, and 8) workup methodologies. It was found that, by controlling these parameters, highly reproducible syntheses are obtained. Secondly, the variation of these parameters alone led to a dramatic difference in volume-weighted particle size means, which exceeds an order of magnitude as investigated by our in-house X-ray scattering instrument [1].
The syntheses are thoroughly documented in an automated fashion, and the synthesis libraries as well as analyses libraries will become available in batches soon. With this library, it will be possible to extract previously unknown correlations, and other laboratories can produce specific particles by following the exact procedures of the particles of their choice.
Robot-assisted laser thermography for surface breaking crack detection on complex shaped components
(2023)
Laser thermography using a focused (spot or line) beam has proved to be effective for detection of surface breaking cracks on planar samples. In this work, we use the same principle, but applied to complex shaped components, like a rail cross-section, a gear, and a gas turbine blade. We use a six-axis robot to move the sample in-front of our thermographic setup. Several scanning-path and thermographic parameters are explored: scanning speed, density of points in each scanning slice, laser power, camera framerate. Additionally, we explore semi-automatic evaluation algorithms for crack detection, as well as 2D-to-3D registration of the found indications.
The use of benchtop-NMR instruments is constantly increasing during the recent years. Advantages of being affordable, portable and easy-to-operate without the need for trained staff make them especially interesting for industrial applications in quality control. However, applications of NMR spectroscopy as an online PAT tool are still very rare but offer a huge potential for process optimization and control. A key task to exploit this potential is hardware field integration of the lab-instruments in a rough environment of a chemical plant. Additionally, developments in automation and data evaluation are mandatory to ensure a robust unattended operation with low maintenance requirements. Here, we show an approach of a fully automated analyzer enclosure considering explosion safety, field communication, as well as environmental conditions in the field.
Temperature sensitivity is still a limitation of benchtop-NMR instruments in flow applications. Recent developments of manufacturers allow for limited operation at static temperature levels, however, a dynamic system for continuous operation is still not available. Using a prototype system offering a larger bore, active temperature shielding studies with thermostated air were performed evaluating the performance.
Automated data evaluation of NMR spectra using a modular indirect hard modeling (IHM) approach showed good results and flexibility. A second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously, offering new ways to simultaneously evaluating large numbers of different models.
Immobilized metal affinity chromatography (IMAC) is a widely used technique for purifying polyhistidine-tagged recombinant proteins. However, it often has practical limitations that require complex optimizations and additional steps for purification. In this study, we introduce functionalized corundum particles as a novel, efficient, and economical method for purifying recombinant proteins in a column-free format. The corundum surface is modified with amino silane APTES, followed by EDTA dianhydride, and then loaded with nickel ions. We used the Kaiser test to monitor the modification process and ICP-MS to quantify the metal-binding capacity. To evaluate the system, we used His-tagged protein A/G (PAG) mixed with bovine serum albumin (BSA). The corundum particles exhibited a binding capacity of approximately 3 mg of protein per gram of corundum or 2.4 mg per 1 mL of corundum suspension. We also examined cytoplasm obtained from different E. coli strains as an example of a complex matrix. Varying the imidazole concentration in the loading and washing buffers showed that higher concentrations during loading improved purity. Even with sample volumes as large as one liter, we successfully isolated recombinant proteins down to a concentration of 1 µg/mL. We found higher purity levels with corundum when comparing the corundum material to standard Ni–NTA agarose beads. We successfully purified His6-MBP-mSA2, a fusion protein comprising monomeric streptavidin and maltose-binding protein, from E. coli cytoplasm, demonstrating the method's applicability. We also purified SARS-CoV-2-S-RBD-His8 expressed in human Expi293F cells, confirming its suitability for mammalian cell culture supernatants. The material cost of the nickel-loaded corundum material (without regeneration) is estimated to be less than 30 cents per gram of functionalized support or 10 cents per milligram of isolated protein. Another advantage of this system is the exceptional physical and chemical stability of corundum particles. Overall, we have demonstrated that this novel material offers an efficient, robust, and cost-effective purification platform for His-tagged proteins, even in challenging, complex matrices and large sample volumes with low product concentrations. This method has potential applications in both small laboratories and large-scale industrial settings.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
This paper reports a systematic study into the effect of nitrogen on iron-catalyzed graphitization of biomass. Chitin, chitosan, N-acetylglucosamine, gelatin and glycine were selected to represent nitrogen-rich saccharides and amino-acid/polypeptide biomass precursors. The materials were pyrolyzed with an iron catalyst to produce carbons with a wide range of chemical and structural features such as mesoporosity and nitrogen-doping. Many authors have reported the synthesis of nitrogen-doped carbons by pyrolysis and these have diverse applications. However, this is the first systematic study of how nitrogen affects pyrolysis of biomass and importantly the catalytic graphitization step. Our data demonstrates that nitrogen inhibits graphitization but that some nitrogen survives the catalytic graphitization process to become incorporated into various chemical environments in the carbon product.
The dataset contains raw data gathered with the ultrasonic pulse-echo method on concrete specimens. The surfaces of the measuring objects were automatically scanned point by point. Pulse-echo measurements were performed at each of these measuring points. The test specimens represent two typical testing tasks in construction industry: the detection of objects and the determination of dimensions to describe the geometry of components. By automating the measurement process, the different test scenarios are examined with a high repeatability, precision and measuring point density. Longitu- dinal and transversal waves were used and the geometrical aperture of the testing system was varied. The low-frequency probes operate in a range of up to approximately 150 kHz. In addition to the specification of the geometrical dimensions of the individual probes, the directivity pattern and the sound field characteristics are provided. The raw data are stored in a universally readable format. The length of each time signal (A-scan) is two milliseconds and the sampling rate is two mega-samples per second. The provided data can be used for comparative studies in signal analysis, imag- ing and interpretation as well as for evaluation pur- poses in different, practically relevant testing scenarios.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
This data set contains three different data types obtained from concrete specimens. For each specimen, the rebound numbers, ultrasonic data (ultrasonic velocity, time of flight), and destructive concrete strength are given. Two kind of specimen geometries were tested: cubes and drilled cores. The files are labeled according to the specimen geometry as "cube" or "core" and the type of measurement data as "compressive_strength", "rn_R" and "rn_Q" for rebound numbers as well as "us" for ultrasonic data. The ultrasonic data were generated by six independent laboratories, the rebound numbers by five independent laboratories and the destructive tests by one laboratory. The designation of each specimen establishes the relationship between the different data types.
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
The corner echo is a well-known effect in ultrasonic testing, which allows detection of surface breaking cracks with predominantly perpendicular orientation to the surface as, for example, corrosion cracks in metal pipes or shafts. This echo is formed by two planes, the surface of the crack and the surface which the crack breaks. It can also be classified as a half-skip method, since a reflection of the pulse occurs on the backwall before the reflection at the defect takes place. In combination with the diffraction from the crack tip, the corner echo also allows crack sizing. As shown in this paper, the corner reflection can be used in civil engineering for nondestructive inspection of concrete. Commercially available low frequency ultrasonic arrays with dry point contact sources generate SH transversal waves with sufficient divergence of the sound field in order to detect corner reflections. Ultrasonic line-scans and area-scans were acquired with a linear array on flat concrete specimens, and the data were reconstructed by the Synthetic aperture focusing technique. If the angles and the area of reconstruction are chosen accordingly, the corner echo reflection can be distinguished from other ultrasonic information. The corner echo can thus be used as a method for deciding whether a crack is a partial-depth crack or a full-depth crack and thus for obtaining a statement about crack depth. This paper presents corresponding experimental results obtained on concrete specimens with artificial test defects and cracks induced under controlled conditions.
Two test series were examined using nondestructive measuring methods by six independent laboratories before determining their compressive strength. The nondestructive test methods used were the rebound hammer and ultrasonic pulse velocity measurement. Two types of geometries were investigated: drilled cores and cubes. The measurement procedure for each of these datasets is conditioned to the geometry and is therefore different.
The first series consists of 20 drilled cores (approximately diameter/height = 10 cm/20 cm) from the 55-year-old Lahntal Viaduct near Limburg, Germany. After preparation in the first laboratory, the lateral surface of the drilled cores was tested with the rebound hammer using a given pattern. Every laboratory tested every drilled core at different locations.
Ultrasonic measurements in transmission were performed repeatedly at predefined points on the flat surfaces of the specimen.
The second series consisted of 25 newly manufactured concrete cubes of a mix with a target concrete strength class of C30/37. The edge length was 15 cm. Each laboratory received five specimens of this test series. Thus, contrary to the first series, each specimen was tested by only one laboratory. Two side faces of each cube were tested with the rebound hammer. In addition, ultrasonic measurements were performed by one laboratory. The time of flight was measured between the tested side faces of the rebound hammer at different positions.
For both series, rebound hammers were used to determine the R-value as well as the Q-value. The rebound hammer models within the laboratories were always the same, while they differed between the laboratories. The ultrasonic measurements took place with different measurement systems and couplants. Finally, both specimen series were tested destructively for compressive strength.
The dataset contains the raw data summarized in tabular form. In addition, relevant calculated data are included in some cases. For the ultrasonic measurements, the time of flight has already been converted into the ultrasonic velocity. Besides, in addition to the raw data of the compressive strength test (force, weight, and geometry values), the calculated compressive strengths and densities are also provided.
The glass transition behavior of thin films of poly(bisphenol A carbonate) (PBAC) was studied employing ellipsometry. The glass transition temperature increases with the reduction of the film thickness. This result is attributed to the formation of an adsorbed layer with a reduced mobility compared to bulk PBAC. Therefore, for the first time, the growth kinetics of the adsorbed layer of PBAC was investigated, prepared by leaching samples from a 200 nm thin film which were annealed for several times at three different temperatures. The thickness of each prepared adsorbed layer was measured by multiple scans using atomic force microscopy (AFM). Additionally, an unannealed sample was measured. Comparison of the measurements of the unannealed and the annealed samples provides proof of a pre-growth regime for all annealing temperatures which was not observed for other polymers. For the lowest annealing temperature after the pre-growth stage only a growth regime with a linear time dependence is observed. For higher annealing temperatures the growth kinetics changes from a linear to a logarithmic growth regime at a critical time. At the longest annealing times the films showed signs of dewetting where segments of the adsorbed film were removed from the substrate (dewetting by desorption). The dependence of the surface roughness of the PBAC surface on annealing time also confirmed that the films annealed at highest temperatures for the longest times desorbed from the substrate.
The microstructure of an apatite-wollastonite (code name AP40) glass-ceramic is analyzed in this study by combining 2D microscopy, phase analysis, X-ray absorption and synchrotron X-ray refraction computed tomography (XCT and SXRCT, respectively). It is shown that this combination provides a useful toolbox to characterize the global microstructure in a wide scale range, from sub-micrometer to millimeter. The material displays a complex microstructure comprising a glassy matrix with embedded fluorapatite and wollastonite small crystals. In this matrix, large (up to 200 μm) spike-shaped structures are distributed. Such microstructural features are oriented around a central sphere, thereby forming a structure resembling a sea urchin. A unique feature of SXRCT, in contrast to XCT, is that internal interfaces are visualized; this allows one to show the 3D distribution of these urchins with exceptionally good contrast. Furthermore, it is revealed that the spike-shaped structures are not single crystals, but rather composed of sub-micrometric crystals, which are identified as fluorapatite and diopside phases by SEM-EDX analysis.
In this study, we compare analytical methods for PFAS determination–target analysis, non-target screening (NTS), direct total oxidizable precursor assay (dTOPA) and extractable organically bound fluorine (EOF). Therefore, suspended particulate matter (SPM) samples from German rivers at different locations in time series from2005 to 2020 were analyzed to investigate temporal and spatially resolved trends. In this study 3 PFAS mass balances approaches were utilized: (i) PFAA target vs. PFAS dTOPA, (ii) PFAS target vs. EOF and (iii) PFAS target vs. PFAS dTOPA vs. organofluorines NTS vs. EOF. Mass balance approach (i) revealed high proportions of precursor substances in SPM samples. For the time resolved analysis an increase from 94% (2005) to 97% in 2019 was observable. Also for the spatial resolved analysis precursor proportions were high with >84% at all sampling sites. Mass balance approach (ii) showed that the unidentified EOF (uEOF) fraction increased over time from82% (2005) to 99% (2019). Furthermore, along the river courses the uEOF increased. In the combined mass balance approach (iii) using 4 different analytical approaches EOF fractions were further unraveled. The EOF pattern was fully explainable at the sampling sites at Saar and Elbe rivers. For the time resolved analysis, an increased proportion of the EOF was now explainable. However, still 27% of the EOF for the time resolved analysis and 25% of the EOF for the spatial resolved analysis remained unknown. Therefore, in a complementary approach, both the EOF and dTOPA reveal unknown gaps in the PFAS mass balance and are valuable contributions to PFAS risk assessment. Further research is needed to identify organofluorines summarized in the EOF parameter.
Introduction to microplastics, definition, relevance, analytical approaches & challenges. TED-GC/MS working principle, features & performance. Optimisation in TED-GC/MS methodology, new validation data. Replacement of Internal Standard, outlook towards upcoming publication and application within EU´s revised drinking water directive.
Critical defects, also known as device killers, in wide bandgap semiconductors significantly affect the performance of power electronic devices. We used the methods imaging ellipsometry (IE) and white light interference microscopy (WLIM) in a hybrid optical metrology study for fast and non-destructive detection, classification, and characterisation of defects in 4H–SiC homoepitaxial layers on 4H–SiC substrates. Ellipsometry measurement results are confirmed by WLIM. They can be successfully applied for wafer characterisation already during production of SiC epilayers and for subsequent industrial quality control.
Small-angle X-ray scattering (SAXS) can be used for structural de- termination of biological macromolecules and polymers in their na- tive states. To improve the reliability of such experiments, the re- duction of radiation damage occurring from exposure to X-rays is needed.One method, is the use of scavenger molecules that protect macromolecules against radicals produced by radiation exposure.In this study we investigate the feasibility to apply the compatible solute, osmolyte and radiation protector Ectoine (THP(B)) as a scavenger throughout SAXS measurements of single-stranded DNA-binding protein Gene-V Protein (G5P/GVP). Therefore we monitor the radiation induced changes of G5P during bio-SAXS. The resulting microscopic energy-damage relation was determined by particle scattering simu- lations with TOPAS/Geant4. The results are interpreted in terms of radical scavenging as well as post-irradiation effects, related to preferential-exclusion from the protein surface. Thus, Ectoine provides an non-disturbing way to improve structure-determination of proteins via bio-SAXS in future studies.
Introduction
Per- and polyfluorinated alkyl substances (PFASs) are a group of over 4730 individual compounds. Several 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.
Methods
For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. In our study we used high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) which 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.
Results
Here, we present an improved method for the determination of PFASs using HR-CS-GFMAS via GaF detection. The optimized method includes a modifier pretreatment step using a mixture of Mg, Pd and Zr and a correction measurement using perfluorooctanoic acid. The combination of both resulted in increased accuracy and precision as well as overall lower detection limits. Furthermore, during optimization the influence of species-specific responses during HR-CS-GFMAS analysis was reduced resulting in a more accurate determination of PFAS sum parameters. To test the applicability of the improved method, we analysed soil samples from a former fire-fighting training area combining the improved method for detection with our previously optimized extraction method for extractable organically bound fluorine (EOF) determination in soils.
Innovative aspects
• Highly sensitive and selective method for fluorine/PFASs analysis based on HR-CS-GFMAS
• Increased accuracy for the determination of EOF
• Reduction of PFAS species-specific responses by optimized modifier conditions
X-ray photoelectron-spectroscopy (XPS) allows simultaneous irradiation and damage monitoring. Although water radiolysis is essential for radiation damage, all previous XPS studies were performed in vacuum. Here we present near-ambient-pressure XPS experiments to directly measure DNA damage under water atmosphere. They permit in-situ monitoring of the effects of radicals on fully hydrated double-stranded DNA. Our results allow us to distinguish direct damage, by photons and secondary low-energy electrons (LEE), from damage by hydroxyl radicals or hydration induced modifications of damage pathways. The exposure of dry DNA to x-rays leads to strand-breaks at the sugar-phosphate backbone, while deoxyribose and nucleobases are less affected. In contrast, a strong increase of DNA damage is observed in water, where OH-radicals are produced. In consequence, base damage and base release become predominant, even though the number of strand-breaks increases further.