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Paper des Monats
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Harmonized and interoperable national Quality Infrastructure (QI) systems are essential for fostering cooperation, promoting mutual trust, and facilitating trade. The true potential of the QI is realized when its elements and actors are seamlessly integrated into a cohesive digital QI ecosystem. Recent developments towards industrial international data spaces enable such an ecosystem but require the integration of QI principles. Recognizing the lack of such a platform, Quality-X aims at setting the stage for the implementation of a QI ecosystem in international data spaces (IDS), GAIA-X and related German and European projects dedicated to secure data sharing. Quality-X is not about the construction of a platform; it is the creation of an inclusive QI ecosystem with harmonized interfaces. Instead of imposing rigid data structures, it prioritizes interoperability. Through the utilization of Decentralized Identifiers (DIDs), Verifiable Credentials, and Identity Hubs, Quality-X seeks seamless interactions across diverse service provider systems.
This white paper introduces the concept and vision of Quality-X and discusses the general prerequisites for integrating QI processes within data spaces. Further on, we introduce existing testbeds, which will serve as an experimental proving ground for exploring various use cases related to the implementation of the vision of a QI-Digital.
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Harmonisierte und interoperable nationale Qualitätsinfrastrukturen (QI) sind für die Förderung der Zusammenarbeit, des gegenseitigen Vertrauens und der Erleichterung des Handels unerlässlich. Das wahre Potenzial der QI kommt zum Tragen, wenn ihre Elemente und Akteure nahtlos in ein kohärentes digitales QI-Ökosystem integriert werden. Die jüngsten Entwicklungen hin zu industriellen internationalen Datenräumen ermöglichen ein solches Ökosystem, erfordern jedoch die Integration von QI-Prinzipien. Angesichts des Fehlens einer solchen Plattform zielt Quality-X darauf ab, die Voraussetzungen für die Umsetzung eines QI-Ökosystems in internationalen Datenräumen (IDS), GAIA-X und verwandten deutschen und europäischen Projekten zum sicheren Datenaustausch zu schaffen. Bei Quality-X geht es nicht um den Aufbau einer Plattform, sondern um die Schaffung eines umfassenden QI-Ökosystems mit harmonisierten Schnittstellen. Anstatt starre Datenstrukturen aufzuerlegen, steht die Interoperabilität im Vordergrund. Durch die Verwendung von dezentralen Identifikatoren (DIDs), überprüfbaren Berechtigungsnachweisen und Identitäts-Hubs strebt Quality-X eine nahtlose Interaktion zwischen verschiedenen Systemen von Dienstleistern an.
Dieses Whitepaper stellt das Konzept und die Vision von Quality-X vor und erörtert die allgemeinen Voraussetzungen für die Integration von QI-Prozessen in Datenräumen. Darüber hinaus stellen wir bestehende Testbeds vor, die als experimentelles Versuchsfeld für die Erforschung verschiedener Anwendungsfälle im Zusammenhang mit der Umsetzung der Vision einer QI-Digital dienen sollen.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
A semi-automatic thermographic procedure for the assessment of the welded area of resistance projection welded joints has been developed. Currently, to assess the quality of RPW joints destructive tests are used and the more commonly used non-destructive technique is the ultrasonic one. The possibility for a quantitative evaluation of the welded area by thermographic technique has been proved by means of an innovative procedure applied on steel RPW joints with ‘as it’ surface conditions. Measurements obtained by thermography and ultrasound have been compared, to verify the developed procedure.
Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
(2024)
This study reports a strategy to use sophisticated, realistic X-ray Computed Tomography (CT) simulations to reduce Missing Wedge (MW) and Region-of-Interest (RoI) artifacts in FBP (Filtered Back-Projection) reconstructions. A 3D model of the object is used to simulate the projections that include the missing information inside the MW and outside the RoI. Such information augments the experimental projections, thereby drastically improving the reconstruction results. An X-ray CT dataset of a selected object is modified to mimic various degrees of RoI and MW problems. The results are evaluated in comparison to a standard FBP reconstruction of the complete dataset. In all cases, the reconstruction quality is significantly improved. Small inclusions present in the scanned object are better localized and quantified. The proposed method has the potential to improve the results of any CT reconstruction algorithm.
Grundmann, Jana ; Ermilova, Elena ; Hertwig, Andreas ; Klapetek, Petr ; Pereira, Silvania F. ; Rafighdoost, Jila ; Bodermann, Bernd
The different defect types on SiC samples are measured with various measurement methods including optical and tactile methods. The defect types investigated include particles, carrots and triangles and they are analyzed with imaging ellipsometry, coherent Fourier scatterometry and atomic force microscopy. Each of these methods measures different properties of the defects and they all together contribute to a complete analysis.
This study investigates the sintering and crystallization behavior and kinetic of the bioactive glass (BG) 13–93 with nominal composition (in mol%): 54.6 SiO2 - 1.7 P2O3 - 22.1 CaO - 6.0 Na2O - 7.9 K2O - 7.7 MgO. Sintering and crystallization were investigated non-isothermally for various particle size fractions smaller than 315 μm as well as for bulk samples. Densification was not hindered by the presence of crystalline phases across all particle size fractions. Afterwards, wollastonite was found as the dominant crystal phase at higher temperature which resorb primary surface precipitation-like quartz crystallites. The growth direction shifts into volume when the sample surface is nearly covered. The crystal growth rate of wollastonite was calculated from the crystalline surface layer thickness measured during heating. The findings of this study are relevant for the high temperature processing of BG 13–93.
Until the 1980s radiography was used to inspect civil structures in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Meanwhile, non-destructive techniques such as ultrasound or
radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features when applied to reinforced or prestressed concrete inspection.
Muon tomography has received much attention recently. Muons are particles generated naturally by cosmic rays in the upper atmosphere and pose no risk to humans. Novel detectors and tomographic imaging algorithms have opened new fields of application, mainly in the nuclear sector, but also in spectacular cases such as the Egyptian pyramids.
As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results have been at least of similar quality compared to ultrasonic and radar imaging, potentially even better. Recently, the research was expanded to more realistic testing problems such as the detection of voids in certain structural elements. However, before practical implementation, more robust, mobile, and affordable detectors would be required as well as user-Friendly imaging and simulation software.
Ergot alkaloids form a toxicologically relevant group of mould toxins (mycotoxins) that are among the most common contaminants of foodstuff and animal feed worldwide. Reliable controls are essential to minimise health risks and economic damage. Due to their toxicological relevance, EU limit values for 12 priority ergot alkaloids have been introduced for the first time in 2022 and range from 500 μg/kg in rye milling products down to 20 ug/kg Processed cereal-based foods for infants and young children[1]. High-performance liquid chromatography - mass spectrometry is used to quantify low concentrations of ergots in food, however the European standard analytical procedure cannot be applied due to the lack of isotopically labelled reference standards.
The complex structure of the ergot alkaloids makes a total synthesis extremely challenging, expensive and time-consuming. Therefore, we are focusing on different semi-preparative methods (electrochemistry, organic synthesis, heterogeneous catalysis) to specifically N-demethylate the C8 carbon atom of the lysergic acid moiety. The norergot alkaloid formed is then isotopically labelled using an electrophilic methyl source, i.e. iodomethane or dimethyl sulphate to obtain the specific isotopic labelled ergot alkaloid. Initial experiments have shown that N-demethylation of the ergot alkaloid ergotamine is possible by both electrochemical and wet-chemical organic synthesis. The next step is to improve the previously determined reaction conditions to enable the synthesis of norergotamine on a mg scale for further reactions.
Ellipsometry is a very powerful tool used for accurate material investigation in a wide wavelength range. It is a non-destructive and fast method. Imaging ellipsometry as a combination of optical microscopy and ellipsometry enables spatially resolved measurements when determining the layer thickness and dielectric properties of thin layers. It is known for its high polarisation sensitivity and high contrast for the surface structures. In this contribution we show the application of the imaging ellipsometry for detection of defects in energy materials and quality validation of possible reference materials for nano-electronics.
Defects in wide bandgap semiconductors, in homoepitaxial SiC and heteroepitaxial GaN layers on transparent SiC substrates, can be successfully detected and classified by means of imaging ellipsometry. Correlation of imaging ellipsometry results with results from complementary techniques such as white light interference microscopy as well as atomic force microscopy contribute to understanding of surface topography and defect formation mechanisms. We discuss the potential of different methods for analysing ellipsometric map data for monitoring the defect densities.
Electric properties of materials at the nanoscale can be investigated by means of scanning probe microscopy methods such as scanning microwave microscopy and conductive atomic force microscopy. However, development of new robust and easy-to-use calibration methods and calibration standards is essential to increase the traceability of these methods and allow their broad application in industry. We show how imaging spectroscopic ellipsometry can be used for development and monitoring of processing quality of patterned reference samples based on indium tin oxide (ITO) layer with different thickness and conductivity.
The built infrastructure ages and requires regular inspection and, when in doubt, monitoring. To ensure that older concrete bridges showing signs of deterioration can be used safely, several innovative monitoring tools have been introduced, including but not limited to optical, fiber-optic, or acoustic emission techniques. However, there are gaps in the portfolio. A sensing technique that covers a wide range of damage scenarios and larger volumes, while still being sensitive and specific, would be beneficial.
For about 15 years, research has been conducted on ultrasonic monitoring of concrete structures that goes beyond the traditional ultrasonic pulse velocity test (PV test), mostly using a very sensitive data evaluation technique called coda wave interferometry. At BAM we have developed sensors and instrumentation specifically for this method.
We have instrumented a 70-year-old, severely damaged prestressed concrete bridge in Germany in addition to a commercial monitoring system. We have now collected data for almost 3 years. We can show that we can provide information about the stress distribution in the bridge. We have also been able to confirm that there has been no significant additional damage to the bridge since the installation.
X-rays without X-rays: Can muon tomography provide pictures from within concrete and other objects?
(2024)
Until the 1980s radiography was used to inspect civil structures in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Meanwhile, non-destructive techniques such as ultrasound or
radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features when applied to reinforced or prestressed concrete inspection.
Muon tomography has received much attention recently. Muons are particles generated naturally by cosmic rays in the upper atmosphere and pose no risk to humans. Novel detectors and tomographic imaging algorithms have opened new fields of application, mainly in the nuclear sector, but also in spectacular cases such as the Egyptian pyramids.
As a first step towards practical application in civil engineering and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results have been at least of similar quality compared to ultrasonic and radar imaging, potentially even better. Recently, the research was expanded to more realistic testing problems such as the detection of voids in certain structural elements. However, before practical implementation, more robust, mobile, and affordable detectors would be required as well as user-Friendly imaging and simulation software.
The talk also discusses other applications , such as volcanology, mining and geothermal exploration.
Bayerlein, Bernd ; Schilling, Markus ; Birkholz, Henk ; Jung, Matthias ; Waitelonis, Jörg ; Mädler, Lutz ; Sack, Harald
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 (consistent) and variant (context-specific) 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 paper, an approach how to maintain a comprehensive MSE-centric terminology composing a mid-level ontology–the Platform MaterialDigital Core Ontology (PMDco)–via MSE community-based curation procedures is presented. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics. Additionally, it demonstrates how the PMDco lowers development and integration thresholds. Moreover, the research highlights how to fuel it with real-world data sources ranging from manually conducted experiments and simulations with continuously automated industrial applications.
The usefulness of seven different Tin catalysts, Bismuth subsalicylate and Titan tetra(ethoxide) for the polycondensation of ethyl L-lactate (ELA) was examined at 150 °C/6 d. Dibutyltin bis(phenoxides) proved to be particularly effective. Despite the low reactivity of ELA, weight average molecular masses (Mw) up to 12 500 were found along with partial crystallization. Furthermore, polylactides (PLAs) of similar molecular masses were prepared via ELA-initiated ROPs of L-lactide by means of the four most effective polycondensation catalysts. The crystalline linear PLAs were annealed at 140 or 160 °C in the presence of these catalysts. The consequences of the transesterification reactions in the solid PLAs were studied by means of matrix-assisted laser desorption/ionization (MALDI TOF) mass spectrometry, gel permeation chromatography (GPC) and small-angle X-ray scattering (SAXS). The results indicate that polycondensation and formation of cycles proceed in the solid state via formation of loops on the surface of the crystallites. In summary, five different transesterification reactions are required to explain all results.
Tang, Lei ; Magdysyuk, Oxana V. ; Jiang, Fuqing ; Wang, Yiqiang ; Evans, Alexander ; Kabra, Saurabh ; Cai, Biao
Manufacturing austenitic stainless steels (ASSs) using additive manufacturing is of great interest for cryogenic applications. Here, the mechanical and microstructural responses of a 316L ASS built by laser powder bed fusion were revealed by performing in situ neutron diffraction tensile tests at the low-temperature range (from 373 to 10 K). The stacking fault energy almost linearly decreased from 29.2 ± 3.1 mJm⁻² at 373 K to 7.5 ± 1.7 mJm⁻² at 10 K, with a slope of 0.06 mJm⁻²K⁻¹, leading to the transition of the dominant deformation mechanism from strain-induced twinning to martensite formation. As a result, excellent combinations of strength and ductility were achieved at the low-temperature range.
Ergot alkaloids form a toxicologically relevant group of mould toxins (mycotoxins) that are among the most common contaminants of food and animal feed worldwide. Reliable controls are essential to minimise health risks and economic damage. Due to their toxicological relevance, EU limit values for 12 priority ergot alkaloids have been introduced for the first time in 2022 and range from 500 µg/kg in rye milling products down to 20 ug/kg Processed cereal-based foods for infants and young children[1]. High-performance liquid chromatography - mass spectrometry is used to quantify low concentrations of ergots in food, however the European standard analytical procedure cannot be applied due to the lack of isotopically labelled reference standards.
The complex structure of the ergot alkaloids makes a total synthesis extremely challenging, expensive and time-consuming. Therefore, we are focusing on different semi-preparative methods (electrochemistry, organic synthesis, heterogeneous catalysis) to specifically N-demethylate the C8 carbon atom of the lysergic acid moiety. The norergot alkaloid formed is then isotopically labelled using an electrophilic methyl source, i.e. iodomethane or dimethyl sulphate to obtain the specific isotopic labelled ergot alkaloid. Initial experiments have shown that N-demethylation of the ergot alkaloid ergotamine is possible by both electrochemical and wet-chemical organic synthesis. The next step is to adapt the previously determined reaction conditions to enable the synthesis of norergotamine on a mg scale.
To evaluate the durability of new alternative cement compositions, it is important to examine the internal transport of moisture through these materials. For this purpose, mortars were prepared from different types of cement and capillary suction experiments were carried out. The moisture transport was studied with an NMR tomograph and compared with weight measurements. With the tomograph, the total moisture input could be determined, as well as the moisture content within the samples non-destructively and spatially resolved. This allows precise observation of the moisture fronts. The tomograph was also used to determine the capillary transport coefficient.
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). By fully utilizing these KETs, advanced and sustainable economies will be created. It is considered that Metrology is a key enabler for the advancement of these KETs. EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network for Advanced Manufacturing. The EMN is made up of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The EMN aims to provide a high-level coordination of European metrology activities for the Advanced Materials and Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing and Advanced Materials (Large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider metrology community (including TCs) to provide input for the preparation of a Strategic Research Agenda (SRA) for Metrology for Advanced Manufacturing.
This presentation will describe the progress in the development of the SRA by the EMN for Advanced Manufacturing. The metrology challenges identified across the various key industrial sectors, which utilise Advanced Materials and Advanced Manufacturing will be presented.
The EMN for Advanced Manufacturing is supported by the project JNP 19NET01 AdvManuNet.
O'Connor, Daniel ; Evans, Alexander ; Balsamo, Alessandro ; Favres, Georges ; Przyklenk, Anita ; Bosse, Harald ; Phillips, Dishi
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing.
This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
The contamination of drinking water with pharmaceuticals represents a severe health risk. In order to monitor the drinking water quality continuously and enable quick countermeasures in case of contamination, novel sensors are required. Here, immunoanalytical methods based on the binding of the analyte to highly selective antibodies can be helpful. In this work, magnetic bead-based immunoassays (MBBAs) have been developed for the detection of two relevant contaminants of drinking water: diclofenac (DCF) and amoxicillin (AMX). In case of the latter, not only the parent drug is of interest in the risk assessment but also its hydrolysis products (HPs). In a comprehensive study, the influence of external factors and intrinsic properties of the water on the rate of hydrolysis was investigated. As the hydrolysis of AMX further impacts the recognition by the antibody, a strategy to analyze samples with unknown hydrolysis degree of AMX was established employing the enzyme β-lactamase in sample preparation. For both analytes, the MBBAs enable the fast quantification with results obtained in less than one hour which represents a major improvement over conventional immunoassays like the enzyme-linked immunosorbent assay (ELISA). Compared to the respective ELISAs with the same antibodies, the MBBAs further exhibit improved analytical parameters such as a broader measurement range and lower limits of detection. Due to the magnetic properties of the beads that serve as a platform for the assays, they are suitable for the mobile and automated detection at the point-of-care. An integrated diagnostic system was designed in which electrochemical detection with chronoamperometry on a microfluidic chip allows for further miniaturization of the system to enable monitoring of the drinking water quality online in water supply pipes at waterworks.
Lisec, Jan ; Recknagel, Sebastian ; Prinz, Carsten ; Vogel, Kristin ; Koch, Matthias ; Becker, Roland
The statistical tool eCerto was developed for the evaluation of measurement data to assign property values and associated uncertainties of reference materials. The analysis is based on collaborative studies of expert laboratories and was implemented using the R software environment. Emphasis was put on comparability of eCerto with SoftCRM, a statistical tool based on the certification strategy of the former Community Bureau of Reference. Additionally, special attention was directed towards easy usability from data collection through processing, archiving, and reporting. While the effects of outlier removal can be flexibly explored, eCerto always retains the original data set and any manipulation such as outlier removal is (graphically and tabularly) documented adequately in the report. As a major reference materials producer, the Bundesanstalt für Materialforschung und -prüfung (BAM) developed and will maintain a tool to meet the needs of modern data processing, documentation requirements, and emerging fields of RM activity. The main features of eCerto are discussed using previously certified reference materials.
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing.
This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing.
Bertovic, Marija ; Given, Joseph ; Rentala, V K ; Wall, M ; Kanzler, D ; Lehleitner, Johannes ; Heckel, Thomas ; Tkachenko, Viktoriya
Human factors (HFs) are a frequently mentioned topic when talking about the reliability of non-destructive testing (NDT). However, probability of detection (POD), the commonly used measure of NDT reliability, only looks at the technical capability of an NDT system to detect a defect.
After several decades of research on the influence of HFs on NDT reliability, there is still no commonly accepted approach to rendering HFs visible in reliability assessment. This paper provides an overview of possible quantitative and qualitative methods for integrating HFs into the reliability assessment. It is concluded that reliability assessment is best carried out using both quantifiable and non-quantifiable approaches to HFs.
Concrete is the most important human-made material because it serves as the basis of our built environment. Since the properties of concretes are dominated by their key compound, cement, devising a way to determine the cement’s origin, known as provenancing, is of great importance for answering different provenance-related questions. These questions range from liability issues when damage occurs to concrete-made structures, to forensic investigations where cement particles are found at crime scenes. This thesis showcases the use of isotope techniques to answer these provenance-related questions. Conventional 87Sr/86Sr and 143Nd/144Nd isotope and elemental ratios consisting of Ca, Sr, K, Mn, Mg, and Ti are used as fingerprints for ordinary Portland cement (OPC) provenancing. The first part of this thesis describes research previously conducted in fingerprinting cementitious materials, providing an overview of provenance studies of cement and the main approaches commonly used. In several studies, the origin of clinker for certain locations was determined via different approaches. However, clinker is an intermediate product, which is available only at the production site and therefore, the practical relevance is rather limited. Furthermore, the use of Sr and Nd isotope systems, together with elemental fingerprints are presented as state of the art in the field. Therein, the principal approach for the overall study is sketched. For the second part of the study, a sample preparation technique for Sr isotopes in Portland cement was developed. The aim was to find the most appropriate sample preparation procedure for cement provenancing and selection was realised by comparing the 87Sr/86Sr isotope ratios of differently treated OPCs with those of the corresponding clinkers. Based on these findings, the third part of the study focused on the measurements of Sr and Nd isotope ratios, together with elemental ratios, to establish a reliable technique for OPC provenancing. The outcomes of this final stage are then used to establish a procedure for fingerprinting cements. This becomes possible with the use of Sr and Nd isotope ratios and geochemical profiles. To perform isotope ratio measurements and obtain reliable data, it was necessary to establish a quality control procedure. Thus, an interlaboratory comparison (ILC) was organised to characterise 87Sr/86Sr isotope ratios in geological and industrial reference materials by applying the conventional method for 87Sr/86Sr isotope ratios. As reference material, four cements (VDZ 100a, VDZ 200a, VDZ 300a, IAG OPC-1), one limestone (IAG/CGL ML-3) and one slate (IAG OU-6) were selected, thus covering a wide range of Sr isotope signatures.
Sr isotope ratio analysis
(2023)
Pb isotope ratio analysis
(2023)
Detector deadtime
(2023)
Isotope Ratio Analysis
(2023)
Bartolac, M. ; Bien, J. ; Górski, M. ; Keßler, S. ; Küttenbaum, Stefan ; Kuzawa, M. ; Ley, J. ; Maack, Stefan ; Mendler, A. ; Ryjáček, P. ; Santos, L. ; Verstrynge, E.
The through-life management of our constantly ageing infrastructure is a basic requirement in order to ensure their structural safety and serviceability. Each structure experiences deterioration processes with time leading to a decrease of structural safety and serviceability. The design of new structures considers the expected deterioration for a defined period, the design service life. However, a frequent survey of structural safety controlling structural condition should be mandatory and a maintenance plan should be an integral part of the design. In addition, many structures have exceeded their design service life already or are very close to it leading to an increasing demand for condition assessment. On the one hand, assumptions made during design are not valid any more due to change of the loads, e.g., increasing traffic loads in terms of number and weights. On the other hand, design codes evolved over time in such a way that existing structures do not comply with today’s standards. In all these cases, the through-life management is an important tool to maintain the accessibility of existing structures with known reliability.
In line with the new Model Code for Concrete Structures, which includes guidance for both – design of new structures and assessment of existing structures, the Task Group 3.3 focused on the compilation of a state-of-the-art guideline for the through-life management of existing concrete structures, including:
Data acquisition by testing and monitoring techniques;
Condition assessment for the evaluation of existing structures;
Performance prediction using advanced methods;
Decision-making procedures to perform a complete assessment of existing structure.
The overall objective of the through-life management is the assessment of the current condition and the estimation of the remaining service life under consideration of all boundary conditions.
Karafiludis, Stephanos ; Kochovski, Z. ; Scoppola, E. ; Retzmann, Anika ; Hodoroaba, Vasile-Dan ; ten Elshof, J. E. ; Emmerling, Franziska ; Stawski, Tomasz Maciej
Here, we elucidate nonclassical multistep crystallization pathways of transition metal phosphates from aqueous solutions. We followed precipitation processes of M-struvites, NH4MPO4·6H2O, and M-phosphate octahydrates, M3(PO4)2·8H2O, where M = Ni, Co, or NixCo1–x, by using in situ scattering and spectroscopy-based techniques, supported by elemental mass spectrometry analyses and advanced electron microscopy. Ni and Co phosphates crystallize via intermediate colloidal amorphous nanophases, which change their complex structures while agglomerating, condensing, and densifying throughout the extended reaction times. We reconstructed the three-dimensional morphology of these precursors by employing cryo-electron tomography (cryo-ET). We found that the complex interplay between metastable amorphous colloids and protocrystalline units determines the reaction pathways. Ultimately, the same crystalline structure, such as struvite, is formed. However, the multistep process stages vary in complexity and can last from a few minutes to several hours depending on the selected transition metal(s), their concentration, and the Ni/Co ratio.
Surface functionalized silica nanoparticles (SiO2-NP) gained great interest in the life and material sciences, as they can be used e.g. as drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. They are highly stable, are easily produced and modified on a large scale at low cost and can be labeled or stained with a multitude of sensor dyes. These dye modified particle conjugates have several advantages as compared to conventional molecular probes like enhanced brightness, ease of designing ratiometric systems by combining analyte-sensitive and inert reference dyes, and increased photostability. Moreover, stained nanoparticles can enable the use of hydrophobic dyes in aqueous environments.
Here we present our work on multicolored sensors for the measurement of pH, oxygen and saccharides utilizing amorphous SiO2 NPs.
In recent years, chromium (III) complexes have received a lot of attention as novel near-infrared (NIR) emitters 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.[1] 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. An elegant approach to reduce the undesired luminescence quenching by triplet oxygen explored by us presents the incorporation of these chromium(III) complexes into different types of amorphous, non-porous silica nanoparticles, that can be simply surface functionalized, e.g., with targeting ligands and/or other sensor molecules. 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. 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 confirm our design concept of nanoscale NIR emissive Cr(III) complex-based reporters
Engineered nanoparticles (NPs) with various chemical compositions and surface functionalities are routinely fabricated for industrial applications such as medical diagnostics, drug delivery, sensing, catalysis, energy conversion and storage, opto-electronics, and information storage which improve the quality of life and European prosperity. NP function, performance, interaction with biological species, and environmental fate are largely determined by their surface functionalities. Standardized repeatable surface characterization methods are therefore vital for quality control of NPs, and to meet increasing concerns regarding their safety. Therefore, industry, regulatory agencies, and policymakers need validated traceable measurement methods and reference materials. This calls for fit-for-purpose, validated, and standardized methods, and reference data and materials on the surface chemistry of engineered NPs. Here, we present a concept for the development of such standardized measurement protocols utilizing method cross-validation and interlaboratory comparisons (ILCs) with emphasis on both advanced measurement methods such as quantitative Nuclear Magnetic Resonance (qNMR), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) and cost-efficient, non-surface specific methods like optical assays and electrochemical titration methods.
Engineered and tailored nanomaterials (NM) are of great interest in the life and material sciences, as they can be used, e.g., as drug carriers, barcodes, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. Their performance and safety depend not only on their particle size, size distribution, and morphology, but also on their surface chemistry, i.e., the total number of surface functional groups (FG) and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. It also underlines the importance of validated analytical methods that provide accurate information on these application-relevant physicochemical properties with a known uncertainty. In the case of FG quantification, this calls for robust, fast, inexpensive, and reliable methods which allow for the characterization of a broad variety of NM differing in size, chemical composition, and optical properties.
Methods
Aiming at the development of simple, versatile, and multimodal tools for the quantification of bioanalytically relevant FG such as amine, carboxy, thiol, and aldehyde functionalities, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance (NMR), mass spectrometry (MS), and thermal analysis methods.
Results
Here, we will present examples for different types of NMs and FGs including results from a currently running interlaboratory comparison (ILC) with the National Research Council of Canada (NRC) to pave the road for method standardization.
Innovative aspects
• Surface analysis
• Performance and safety of nanomaterials
• Standardization
Engineered nanomaterials (NM) with their large surface-to-volume ratios and their for some materials observed size-dependent functional properties are of increasing relevance for current and future developments in various fields such as medical and pharmaceutical industry, computing and electronics or food and consumer products. The performance and safety of NM are determined by the sum of their intrinsic physicochemical properties. Especially, the particle surface chemistry, which is largely controlled by the chemical nature and density of functional groups (FG) and ligands, is an important key driver for NM performance, stability, and processibility as well as the interaction of NM with the environment. Thus, methods for FG quantification can foster the sustainable development of functional and safe(r) NM.
Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made polymeric and silica particles of varying FG, used as optical pH sensors. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.
In recent years, the use of functionalized micro- and nanomaterials has increased rapidly for a wide range of applications in the life and material sciences, due to their unique properties in combination with their high surface-to-volume ratio and stability. For instance, functionalized micro- and nanomaterials, that are labeled or stained with a multitude of sensor dyes can be used for monitoring, and quantification of neutral and ionic analytes. These materials have several advantages as compared to conventional molecular probes like enhanced brightness, ease of designing ratiometric systems by combining analyte-sensitive and inert reference dyes, and increased photostability. Moreover, stained nanoparticles can enable the use of hydrophobic dyes in aqueous environments.
Versatile templates and carriers for the fabrication of nanosensors by staining and/or labeling with different fluorophores and sensor molecules are biocompatible silica and polymeric particles, because they can be synthesized in large scales at low costs with different surface chemistries.
Here we present our work on multicolored sensors for the measurement of pH, oxygen and saccharides utilizing commercially available or in-house synthesized silica and polymeric particles.
Nowadays amorphous silica nanoparticles (SiO2-NP) are one of the most abundant engineered nanomaterials, that are highly stable and can be easily produced on a large scale at low cost. Surface functionalized SiO2-NP are of great interest in the life and material sciences, as they can be used e.g. as
drug carriers, fluorescent sensors, and multimodal labels in bioanalytical assays and imaging applications. Their performance in such applications depends not only on particle size, size distribution, and morphology, but also on surface chemistry, i.e. the total number of surface functional groups (FG)
and the number of FG accessible for subsequent functionalization with ligands or biomolecules, which in turn determines surface charge, colloidal stability, biocompatibility, and toxicity. Aiming at the development of simple, versatile, and multimodal tools for the quantification of many bioanalytically relevant FG and ligands, we investigated and compared various analytical methods commonly used for FG quantification. This includes electrochemical titration methods, dye-based optical assays, and other instrumental analytical techniques such as nuclear magnetic resonance and thermal analysis methods.
The potential of our multimodal approach for FG quantification was demonstrated for commercial and custom-made silica particles of varying FG, showing not only an influence of the synthesis methods on the number of FG but also on the performance. In the future, our strategy can contribute to establish multi-method characterization strategies to provide a more detailed picture of the structure-properties relationship.
In the focus of division Biophotonics are the design, preparation, analytical and spectroscopic characterization, and application of molecular and nanoscale
functional materials, particularly materials with a photoluminescence in the visible, near infrared (NIR) and short-wave infrared (SWIR). This includes optical reporters for bioimaging and sensing, security and authentication barcodes, and materials for solid state lighting, energy conversion, and photovoltaics. For the identification of optimum particle structures quantitative spectroscopic studies are performed under application-relevant conditions, focusing on the key performance parameter photoluminescence quantum yield. In addition, simple, cost-efficient, and standardizable strategies for quantifying functional groups on the surface of nano- and microparticles are developed, here with a focus on optical assays and electrochemical titration methods, cross-validated by more advanced methods such as quantitative NMR. In addition, reference materials and reference products are developed for optical methods, particularly luminescence techniques, and for analytical methods utilized for the characterization of nanomaterials.
For fluorescence microscopy, there is an increasing need for suitable calibration tools and reference materials for microscope calibration, the determination of performance parameters, and the regular control and validation of instrument performance. This is addressed in the BmWk-financed project FluMikal (WIPANO program) by two research groups from academia and two companies, that is coordinated by BAM. Here we present different approaches to liquid and solid fluorescence standards for the determination of the wavelength-dependent spectral sensitivity of fluorescence microscopes and ideas concerning the choice of suitable fluorescence lifetime standard for increasingly utilized fluorescence lifetime imaging (FLIM).
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.
The application of composite overwrapped pressure vessels (COPV) to store hydrogen and other compressed gases, especially when operating at high pressures, imposed the need for an innovative and reliable approach to ensure the safe operation of the system. Continuous structural health monitoring (SHM) based on ultrasonic guided waves (GWs) is a promising approach due to the ability of the wave to propagate for long distances and go around complex structures, moreover the high sensitivity to various failure modes such as delamination, matrix cracking and debonding. In this study, we scrutinize the behavior of (GWs) within the COPV using a network of PZT elements that are used for excitation and sensing. A laser doppler vibrometer (LDV) was also used to scan the surface of the vessel in various directions. L(0,1) and L(0,2) were observed in the captured signal. The L(0, 2) appeared to be a dominant mode in the COPV and was capable of propagating along the entire length and maintaining a good signal-to-noise ratio. The L(0,2) mode maintained the same phase velocity when it is captured at various excitation angles (0, 45, and 90 degrees). The reduced effect of the orthotropy of the materials on the propagating waves is an important result as it will reduce the complexity in data processing when performing damage identification.
In the event of moisture deterioration, rapid detection and localization is particularly important to prevent further deterioration and costs. For building floors, the layered structure poses a challenging obstacle for most moisture measurement methods. But especially here, layer-specific information on the depth of the water is crucial for efficient and effective repairs. Ground Penetrating Radar (GPR) shows the potential to generate such depth information. Therefore, the present work investigates the suitability of GPR in combination with machine learning methods for the automated classification of the typical deterioration cases (i) dry, (ii) wet insulation, and (iii) wet screed.
First, a literature review was conducted to identify the most common methods for detecting moisture in building materials using GPR. Here, it especially became clear that all publications only investigated individual time-, amplitude- or frequency features separately, without combining them. This was seen as a potential aspect for innovation, as the multivariate application of several signal features can help to overcome individual weaknesses and limitations.
Preliminary investigations carried out on drying screed samples confirmed the profitable use of multivariate evaluations. In addition to the general suitability and dependencies of various features, first limitations due to possible interference between the direct wave and the reflection wave could be identified. This is particularly evident with thin or dry materials, for which the two-way travel times of the reflected radar signals become shorter.
An extensive laboratory experiment was carried out, for which a modular test specimen was designed to enable the variation of the material type and thickness of screed and insulation, as well as the simulation of moisture deteriorations. The data collected revealed clear differences between dry and deteriored structures within measured B-scans. These deviations were to be detected with the newly introduced B-scan features, which evaluate the statistical deviation of A-scan features within a survey line. In this way, deteriorations to unknown floor structures are recognized, regardless of the material parameters present. In a subsequent training and cross-validation process of different classifiers, accuracies of over 88 \% of the 504 recorded measurements (252 different experimental setups) were achieved. For that, the combination of amplitude and frequency features, which covered all relevant reflections of the radar signals, was particularly beneficial. Furthermore, the data set showed only small differences between dry floors and deteriored screeds for the B-scan features, which could be attributed to a homogeneous distribution of the added water in the screeds. The successfully separation of these similar feature distributions raised the suspicion of overfitting, which was examined in more detail by means of a validation with on-site data.
For this purpose, investigations were carried out at five different locations in Germany, using the identical measurement method like in the laboratory. By extracting drilling cores, it was possible to determine the deterioration case for each measurement point and thus generate a corresponding reference. However, numerous data had to be sorted out before classification, since disturbances due to underfloor heating, screed reinforcements, steel beams or missing insulation prevented comparability with the laboratory experiments. Validation of the remaining data (72 B-scans) achieved only low accuracy with 53 \% correctly classified deterioration cases. Here, the previously suspected overfitting of the small decision boundary between dry setups and deteriored screeds within the laboratory proved to be a problem. The generally larger deviations within (also dry) on-site B-scans were thus frequently misclassified as screed deterioration. In addition, there were sometimes strongly varying layer thicknesses or changing cases of deterioration within a survey line, which caused additional errors due to the local limitation of the drilling core reference. Nevertheless, individual on-site examples also showed the promising potential of the applied signal features and the GPR method in general, which partly allowed a profound interpretation of the measurements. However, this interpretation still requires the experience of trained personnel and could not be automated using machine learning with the available database. Nevertheless, such experience and knowledge can be enriched by the findings of this work, which provide the basis for further research.
Future work should aim at building an open GPR data base of on-site moisture measurements on floors to provide a meaningful basis for applying machine learning. Here, referencing is a crucial point, whose limitations with respect to the moisture present and its distribution can easily reduce the potential of such efforts. The combination of several reference methods might help to overcome such limitations. Similarly, a focus on monitoring approaches can also help to reduce numerous unknown variables in moisture measurements and increase confidence in the detection of different deterioration cases.
These data sets serve as models for calculating the specific surface area (BET method) using gas sorption in accordance with ISO 9277.
The present measurements were carried out with nitrogen at 77 Kelvin and argon at 87 Kelvin.
It is recommended to use the following requirements for the molecular cross-sectional area:
Nitrogen: 0.1620 nm²
Argon: 0.1420 nm²
Titanium dioxides certified with nitrogen sorption and additionally measured with argon for research purposes were used as sample material.
The resulting data sets are intended to serve as comparative data for own measurements and show the differences in sorption behaviour and evaluations between nitrogen and argon.
These data are stored in the universal AIF format (adsorption information file), which allows flexible use of the data.
We employ in-house generated synthetic Al-Si matrix composite XCT data for training deep convolutional neural networks for XCT data conditioning and automatic segmentation. We propose an in-house multilevel deep conditioning framework capable of rectifying noise and blur in corrupted XCT data sequentially. Furthermore, for automatic segmentation, we utilize a special in-house network coupled with a novel iterative segmentation algorithm capable of generalized learning from synthetic data. We report a consistent SSIM efficiency of 92%, 99%, and 95% for the combined denoising/deblurring, standalone denoising, and standalone deblurring, respectively. The overall segmentation precision was over 85% according to the Dice coefficient. We used experimental XCT data from various scans of Al-Si matrix composites reinforced with ceramic particles and fibers.