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With the continuous release of anthropogenic pollutants into the environment, substantial risks for the human health arise. Concerning are especially persistent substances (e.g., PFAS) as they accumulate in food chains which inevitably result in the transgression of negative impact threshold levels. Environmental Analytical Chemsitry interfaces all disciplines of Risk Assessment. Therefore it is the important tool to identify, monitor, and remediate environmental pollutants. Based on the example of PFAS, a workflow to tackle environmental pollutants in a retro- and pro-spective way is shown. Within the project, the worldwide situation of environmental pollutants will be illustrated for the example of PFAS. As the major discipline to confront the problem, analytical chemistry will be shown as a key tool for contesting PFAS and creating safe-by-design materials in the future.
The combination of non-target analysis (NTA) based on HPLC-ESI-MS with elemental fluorine speciation analysis based on HPLC-PARCI-MS for the identification and quantification of (unknown) organofluorines in environmental samples is associated with several advantages e.g., reduced non-target data treatment workflow and quantification.
PFASs compromise persistent, bioaccumulative, and toxic properties and are hence, environmental contaminants of emerging concern. Thus, procedures for identifying potential sources of the entrance of these compounds into the environment, identification of new organofluorine species, and closing mass balances need urgent development. The intrinsic fluorine tag appears in a sizable fraction of these and other xenobiotics, making elemental speciation desirable for quantitative NTA in these areas. Current non-target approaches based on ESI-HRMS suffer from a lack of data mining algorithms for identification of PFASs with low fluorine mass percentages. Furthermore, low ionization efficiencies of the compounds hamper detection limits.
Hence, the proposed combination of simultaneous HPLC-ESI-MS and HPLC-PARCI-MS via split-stream coupling is a promising approach for environmental PFAS monitoring. Furthermore, it could serve as an important analytical procedure to set up limiting values in compliance with the desired PFAS ban of the European Union.
Digital Calibration Certificates: Transforming Efficiency and Safety in Hydrogen Refuelling Station
(2023)
Digital Certificates have emerged as a pivotal element in automation and digitalisation. This presentation highlights the added value of a digitalised metrology, its impact on the workflows on the calibration service providing and receiving side as well as their significance in enhancing the quality infrastructure. An overview of digital calibration certificates (DCC) for temperature sensors, including their structure and role in establishing trust in hydrogen refuelling stations (HRS), will be discussed. Additionally, it explores the impact of DCC on optimising efficiency in the hydrogen refuelling process.
Exploring the paradigm shift brought about by Industry 4.0, where machines possess the ability to autonomously interpret digital certificate data, leads to streamlined safety checks and reduced human intervention. We will discuss how automated verification of machine-readable certificates contributes to maintaining and elevating safety standards over human-readable certificates. Furthermore, we will take a deep dive into the application of DCCs in HRS, showcasing how they enhance operational efficiency, accuracy, and maintenance by enabling real-time monitoring and adjustment of process data.
By exploring the interdependent relationship between digital certificates, machine-readable environments, and HRS optimisation, this presentation will provide valuable insights into harnessing cutting-edge technologies to create a safer, more efficient, and technologically empowered hydrogen refuelling process.
Per- and polyfluoroalkyl substances (PFAS) are chemicals which were developed to improve humanity’s quality of life. Due to their high chemical stability and resistance to degradation by heat or acids, PFAS were used in a variety of consumer products. The continuous use of PFAS in household products and the discharge of PFAS from industrial plants into the sewer system resulted in the contamination of effluents and sewage sludge from wastewater treatment plants (WWTPs) (Roesch et al. 2022). Since sewage sludge is often used as fertilizer, its application on agricultural soils has been observed as a significant entry path for PFAS into the environment, specifically in our food chain. In Germany the sewage sludge/biosolid application on agricultural land was banned with the amendment of the German Sewage Sludge Ordinance and by 2029 sewage sludge application will be totally prohibited. However, phosphorus (P) from sewage sludge should still be recycled in WWTPs of cities with a population larger than 50,000 residents. To produce high-quality P-fertilizers for a circular economy, PFAS and other pollutants (e.g. pesticides and pharmaceuticals) must be separated from sewage sludge. Due to the strong diversity of industrial PFAS usage it is not clear if a safe application of novel recycled P-fertilizers from WWTPs can be guaranteed. Therefore, we analyzed various sewage sludges and wastewater-based fertilizers. Sewage sludge (SL) samples from various WWTPs in Germany and Switzerland, six sewage sludge ashes (SSA) from Germany, six thermally treated SL and SSA samples with different additives (temperatures: 700-1050 °C), two pyrolyzed SL samples (temperature: 400 °C) and two struvite samples from Germany and Canada were analyzed. The goal was to quantify PFAS in sewage sludges and wastewater-based P-fertilizers with the sum parameter extractable organic fluorine (EOF) by combustion ion chromatography (CIC). The results were compared with data from classical LC-MS/MS target analysis as well as selected samples by HR-MS suspect screening. The EOF values of the SLs mainly range between 154 and 538 µg/kg except for one SL which showed an elevated EOF value of 7209 µg/kg due to high organofluorine contamination. For the SSA samples the EOF values were lower and values between LOQ (approx. 60 µg/kg) and 121 µg/kg could be detected. For the pyrolyzed SLs no EOF values above the LOQ were detected. Moreover, the two wastewater-based struvite fertilizers contain 96 and 112 µg/kg EOF, respectively. In contrast to the EOF values, the sum of PFAS target values were relatively low for all SLs. Additional applied PFAS HR-MS suspect screening aimed to tentatively identify PFAS that could contribute to the hitherto unknown part of the EOF value. The majority of the detected fluorinated compounds are legacy PFAS such as short- and long-chain perfluorocarboxylic acids (PFCA), perfluorosulfonic acids (PFSA), polyfluoroalkyl phosphate esters (PAPs) and perfluorophosphonic acids (PFPA). Moreover, fluorinated pesticides, pharmaceutical as well as aromatic compounds were also identified, which are all included in the EOF parameter. Our research revealed that the current PFAS limit of 100 µg/kg for the sum of PFOS + PFOA in the German Fertilizer Ordinance is no longer up to date. Since the number of known PFAS already exceeds 10,000, the ordinance limit should be updated accordingly. Recent regulations and restrictions on using long-chain PFAS (≥C8) have resulted in a significant shift in the industry towards (ultra-)short-chain alternatives, and other, partly unknown, emerging PFAS. Ultimately, also fluorinated pesticides and pharmaceuticals, which end up as ultrashort PFAS in the WWTPs, have to be considered as possible pollutants in fertilizers from wastewater, too.
When reassessing existing concrete bridges, the challenge is often to obtain missing or incomplete information on the internal structure. In particular, the number and position of the existing reinforcement as well as the geometric dimensions of the components are of interest. Non-destructive testing methods, like radar or ultrasound, which work on the basis of the pulse-echo method, have been established for this purpose, as they only require access to the component from one side. The measurement data recorded on the structure require pre-processing to be able to reproduce the internal structure geometrically accurately. Besides different steps of data processing, the geometrical reconstruction of the measured data based on the Synthetic Aperture Focusing Technique (SAFT) is state of the art today. In this paper, the technical possibilities of the ultrasonic echo method are presented based on measurements in the laboratory and on a real bridge structure. The precision of the reconstruction and its limitations are shown. In addition to the state of the art SAFT technique, open questions and the latest research approaches, such as imaging by reverse time migration (RTM) including initial results are discussed.
The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of different kind of materials in FB8.5 Micro-NDT BAM. For instance, the manufacturing defects and high RS are inherent of additively manufacturing techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads.
This presentation summarizes recent developments within the scope of the national pre-standardization project “ZfPStatik”, which aims to prepare a guideline about NDT-supported structural analyses. The focus is on the purposeful and explicit utilization of geometrical tendon and reinforcement bar positions measured on-site in reliability analysis — shown by means of a prestressed concrete bridge as case study.
Experimentally informed multiscale creep modelling of additive manufactured Ni-based superalloys
(2023)
Excellent creep resistance at elevated temperatures, i.e. T / T_m> 0.5, due to γ-γ’ microstructure is one of the main properties of nickel-based superalloys. Due to its great importance for industrial applications, a remarkable amount of research has been devoted to understanding the underlying deformation mechanism in a wide spectrum of temperature and loading conditions. Additive manufactured (AM) nickel-based superalloys while being governed by similar γ-γ’ microstructure, exhibit AM-process specific microstructural characteristics, such as columnar grains, strong crystallographic texture (typically <001> fiber texture parallel to build direction) and compositional inhomogeneity, which in turn leads to anisotropic creep response in both stationary and tertiary phases.
Despite the deep insights achieved recently on the correlation between process parameters and the resulting microstructure, the anisotropic creep behavior and corresponding deformation mechanism of these materials are insufficiently understood so far. One reason for this is the lack of capable material models that can link the microstructure to the mechanical behavior. To overcome this challenge, a multiscale microstructure-based approach has been applied by coupling crystal plasticity (CP) and polycrystal model which enables the inclusion of different deformation mechanisms and microstructural characteristics such as crystallographic texture and grain morphology. The method has been applied to experimental data for AM-manufactured INCONEL-738LC (IN738). The effect of different slip systems, texture, and morphology on creep anisotropy at 850°C has been investigated. Results suggest a strong correlation between superlattice extrinsic stacking fault (SESF) and microtwinning and observed creep anisotropy.
HR-CS-GFMAS a new screening tool for per- and polyfluoroalkyl substances (PFAS) in the environment
(2023)
Per- and polyfluorinated alkyl substances (PFASs) are a large group of anthropogenic contaminates. Concerning are especially their persistent, bioaccumulative and toxic properties. Mostly, target-based approaches (e.g., LC-MS/MS) are utilized for the analysis of PFASs in the environment. But these approaches are limited to the availability of analytical grade standards and therefore drastically 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.
PFAS sum parameters display the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. Besides combustion ion chromatography (CIC), high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification in the low µg F L-1 range.
Here, we present a comparison of total fluorine analysis methods – AOF vs. EOF and HR-CS-GFMAS vs. CIC. Therefore, surface water samples from the Spree River in Berlin, Germany were analyzed at 10 locations for total fluorine (TF), AOF and EOF. The AOF made up 0.14–0.81% of TF and the EOF 0.04–0.28% of TF while AOF concentrations were systematically higher. For the instrumental comparison, HR-CS-GFMAS was the more sensitive and precise method for fluorine analysis compared to CIC.
Glimpses of the Future ✨: Advancing X-ray Scattering in an Automated Materials Research Laboratory
(2023)
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology1 let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators. Combined with automated data correction pipelines, and our analysis and simulation software, this led to more than 40 papers2 in the last 5 years with just over 2 full-time staff members.
This year, our new, modular synthesis platform has made more than 1000 additional samples for us to analyse and catalogue. By virtue of the automation, the synthesis of these samples is automatically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases. Having developed these proof-of-concepts, we find that materials research itself is changed dramatically by automating dull tasks in a laboratory.
This talk is intended to spark ideas and invite collaborations by providing an overview of: 1) the current improvements in our wide-range X-ray scattering laboratory methodology, 2) Introduce some of our open-source analysis and simulation software, touching on scattering, diffraction and PDF, and 3) introducing our open, modular robotic platform for systematic sample preparation. Finally, the remaining bottlenecks and points of attention across all three are highlighted.
The second talk for the Swiss Society for Crystallography (SSCr) workshop on SAXS will highlight the data processing challenges, holistic experimental workflow developments, and the pitfalls. In particular, the following items will be addressed:
- The importance of data processing and estimating uncertainty
- A universal correction pipeline – away with the headaches, at least for this step!
- Experiment planning part 2, some tips and advice to improve your corrected data.
- Sample preparation, background selection, some tips and advice to improve your corrected data.
- Automate for your mental well-being; electronic logbooks, measurement catalogs and workflow management software
- Life on the edge: several pitfalls to avoid…
This talk for the Swiss Society for Crystallography (SSCr) workshop on SAXS will introduce scattering from various angles, focusing in particular on:
- Information content of X-ray scattering experiments, three entry points…
- An introduction to Fourier Transforms
- Sample criteria, compatibility, and selection
- Key indicators of a measurement – where is the information?
- Key indicators of measurement quality
- Experiment planning, the basics
In our (dramatically understaffed) X-ray scattering laboratory, developing a systematic, holistic methodology let us provide scattering and diffraction information for more than 2100 samples for 200+ projects led by 120+ collaborators. Combined with automated data correction pipelines, and our analysis and simulation software, this led to more than 40 papers in the last 5 years with just over 2 full-time staff members.
This year, our new, modular synthesis platform has made more than 1000 additional samples for us to analyse and catalogue. By virtue of the automation, the synthesis of these samples is automatically documented in excruciating detail, preparing them for upload and exploitation in large-scale materials databases.
This talk is intended to spark ideas and invite collaborations by providing an overview of: 1) the current improvements in our wide-range X-ray scattering laboratory methodology, and 2) introducing our open, modular robotic platform for systematic sample preparation.
Introduction: The influence of copper, iron and zinc concentrations on the formation of ß-amyloid plaques and neurofibrillary tangles in Alzheimer’s disease (AD) is widely discussed in the community. The results from human and animal studies so far are mixed with some studies showing a correlation and others not. From a number of studies, it is known that disease state and isotopic composition of essential elements can be coupled.
Aim: The aim of the study was to identify changes in element content and isotopic composition in two transgenic mouse models used in AD research compared to their genetic WT relatives and to establish whether element content and isotopic signature between different laboratories is comparable.
Methods: ß-amyloid (5xFAD) and tau overexpressing (L66) mice together with their matching wild-types were bred at dedicated facilities in accordance with the European Communities Council Directive (63/2010/EU). Serum and brain were sampled after sacrifice and the samples distributed among the participants of the study. The tissues were acid digested for total element determination and high-precision isotope ratio determination. Element content was determined by either sector-field or quadrupole-based inductively coupled plasma mass spectrometry (ICPMS). For the determination of isotope ratios multi-collector ICPMS was used.
Results: Total copper content was significantly higher for L66 and their matched WT compared to 5xFAD and WT. Brains of L66 mice contained more Fe in brain than their WT, Zn and Cu were not significantly different between L66 and WT. Whereas 5xFAD mice had a slightly lower Cu and slightly higher Zn concentration in brain compared to WT. The isotopic signature in brain of L66 mice for Fe was different from their controls, whereas Zn isotope ratios were influenced in 5xFAD mice compared to their WT . The Cu isotopic ratio did not seem to be influenced in either strain. In serum, the shifts were less pronounced.
Conclusion: Even though neither Tau-protein nor amyloid precursor protein are known to be metal-dependent / -containing proteins, the overexpression of both influences the Fe, Cu and Zn metabolism in brain and to some extent also in serum as can be seen not only using total element determination but probably more clearly studying the isotopic signature of Fe, Cu and Zn.
Many metallic materials gain better mechanical properties through controlled heat treatments. For example, in age-hardenable aluminium alloys, the strengthening mechanism is based on the controlled formation of nanometre-sized precipitates, which represent obstacles to dislocation movement and consequently increase the strength. Precise tuning of the material microstructure is thus crucial for optimal mechanical behaviour under service condition of a component. Therefore, analysis of the microstructure, especially the precipitates, is essential to determine the optimum parameters for the interplay of material and heat treatment. Transmission electron microscopy (TEM) is utilized to identify precipitate types and orientations in the first step. Dark-field imaging (DF-TEM) is often used to image the precipitates and thereafter quantify their relevant dimensions. Often, these evaluations are still performed by manual image analysis, which is very time-consuming and to some extent also poses reproducibility problems.
Our work aims at a semantic representation of an automatable digital approach for this material specific characterization method under adaption of FAIR data practices. Based on DF-TEM images of different precipitation states of a wrought aluminium alloy, the modularizable, digital workflow of quantitative analysis of precipitate dimensions is described. The integration of this workflow into a data pipeline concept will also be discussed. Using ontologies, the raw image data, their respective contextual information, and the resulting output data of the quantitative image analysis can be linked in a triplestore. Publishing the digital workflow and the ontologies will ensure data reproducibility. In addition, the semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability.
We report about a joint project aiming at the digitalization of a lab course in materials testing. The undergraduate students were asked to prepare samples of a precipitation hardened aluminum alloy and characterize them using hardness and tensile tests. In a first step, we developed the frames for the digital labor notebook using eLabFTW. The primary data and the relevant metadata of each run were saved in a central database and made available for analysis and report issues. The whole set of results produced in a course was made available in the database. This database can be improved and serve as an open repository for data on this specific alloy.
The logical frame for the joint project was provided by the PMD Core Ontology (PMDco), a mid-level ontology that enables the representation and description of processes and process chains in an MSE-specific manner, ensuring full traceability of generated data. For the digitalization of this lab course, the tensile test ontology (TTO) was applied which is designed as a module of the PMDco using strongly related semantic concepts.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
In this presentation, an approach how to maintain a comprehensive and intuitive MSE-centric terminology composing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures is shown.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
The present work is part of the AIFRI project (Artificial Intelligence For Rail Inspection), where we and our project partners train a neural network for defect detection and classification. Our goal at BAM is to generate artificial ultrasound and eddy current training data for the A.I. This paper has an exploratory nature, where we focus on the simulation of eddy current signals for head check cracks, one of the most important rail surface defects. The goal of this paper is twofold. On the one hand, we present our general simulation setup. This includes geometric models for head check cracks with features like branching and direction change, a model for the HC10 rail testing probe, and the configuration of the Faraday simulation software.
On the other hand, we use the Faraday software to simulate eddy current testing signals with a strong focus on the influence of the damage depth on the signal, while differentiating between different crack geometries. Here, we observe an early saturation effect of the test signal at a damage depth of 2 mm (at a crack angle of 25◦ to the surface). That is about 2 mm earlier than we would expect from measurements at a crack angle of 90◦. This behavior will be investigated further in a future paper. Finally, we interpolate the simulated signals in a two-step curve fitting process. With these interpolations we may generate eddy current test signals for any damage depth within the simulated range.
Additive manufacturing of concrete structures is a novel and emerging technology. Free contouring in civil engineering, which allows for entirely new designs, is a significant advantage. In the future, lower construction costs are expected with increased construction speeds and decreasing required materials and workers. However, architects and civil engineers rely on a certain quality of execution to fulfil construction standards. Although several techniques and approaches demonstrate the advantages, quality control during printing is highly challenging and rarely applied. Due to the continuous mixing process commonly used in 3D concrete printing, it is impossible to exclude variations in the dry mixture or water content, and a test sample cannot be taken as a representative sample for the whole structure. Although mortar properties vary only locally, a defect in one layer during printing could affect the entire integrity of the whole structure . Therefore, real-time process monitoring is required to record and document the printing process. At the Bundesanstalt für Materialforschung und -prüfung (BAM) a new test rig for the additive manufacturing of concrete is built. The primary purpose is measuring and monitoring the properties of a mortar during the printing process. The following study investigates an approach for calculating yield stress and plastic viscosity based on experimentally recorded pressure data. The calculations assume that fresh mortar behaves as a Bingham fluid and that the Buckingham-Reiner-equation is applicable. A test setup consisting of rigid pipes with integrated pressure sensors at different positions is utilized. Monitoring the printing process with different sensors is crucial for the quality control of an ongoing process.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a non-destructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. The results of the defect detection using infrared cameras are presented for a custom research PBF-LB/M machine. Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
The presentation provides an overview and introduction to the need and drivers for the digital transformation of the quality infrastructure (QI). It illustrates the tools and processes that are the fundation of a digital QI and how the initiatve QI-Digital aims at developing accordant solutions. Special emphasis is given to the pilot projects at BAM.
Current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. A second option is the utilization of a “pump and treat” process, cycling polluted soils through a washing plant leading to the concentration of the pollutants in the fine fraction. Only a subsequent, high-energy consuming pyrolysis process guarantees the total destruction of all fluorinated organic contaminants. These approaches are cost-intensive and not intended for the direct decomposition of all PFAS contaminants. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination with gas chromatography mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS), respectively, as well as the fluoride mineralization by ion chromatography (IC) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of additively manufactured (AM) materials in BAM (Berlin, Germany). The manufacturing defects and high RS are inherent of AM techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.