TY - JOUR A1 - Zia, Ghezal Ahmad Jan A1 - Hanke, Thomas A1 - Skrotzki, Birgit A1 - Völker, Christoph A1 - Bayerlein, Bernd T1 - Enhancing Reproducibility in Precipitate Analysis: A FAIR Approach with Automated Dark-Field Transmission Electron Microscope Image Processing N2 - 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. KW - Industrial and Manufacturing Engineering KW - General Materials Science KW - Automated image analysis KW - FAIR research data management KW - Reproducibility KW - microstructural changes PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-593905 DO - https://doi.org/10.1007/s40192-023-00331-5 SN - 2193-9772 SP - 1 EP - 15 PB - Springer Science and Business Media LLC CY - Heidelberg AN - OPUS4-59390 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zaytsev, D. A1 - Funk, Alexander T1 - On the crack evolutional in human dentin under uniaxial compression imaged by high resolution tomography N2 - An observation of the fracture process in front of the crack tip inside a dentin sample by means of ex-situ X-ray computed tomography after uniaxial compression at different deformation values was carried out in this work. This ex-situ approach allowed the microstructure and fracturing process of human dentin to be observed during loading. No cracks are observed up to the middle part of the irreversible deformation in the samples at least visible at 0.4μm resolution. First cracks appeared before the mechanical stress reached the compression strength. The growth of the cracks is realized by connecting the main cracks with satellite cracks that lie ahead of the main crack tip and parallel its trajectory. When under the stress load the deformation in the sample exceeds the deformation at the compression strength of dentin, an appearance of micro-cracks in front of the main cracks is observed. The micro-cracks are inclined (~60°) to the trajectory of the main cracks. The further growth of the main cracks is not realized due to the junction with the micro-cracks; we assume that the micro-cracks dissipate the energy of the main crack and suppressed its growth. These micro-cracks serve as additional stress accommodations, therefore the samples do not break apart after the compression test, as it is usually observed under bending and tension tests. KW - Dentin KW - Crack evolution KW - Compression strength KW - Mechanical properties KW - Microstructure KW - Ex-situ X-ray computed tomography PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-594810 DO - https://doi.org/10.18149/MPM.5152023_5 SN - 1605-8119 VL - 51 IS - 5 SP - 38 EP - 51 PB - Advanced Study Center CY - St. Petersburg AN - OPUS4-59481 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Tobias A1 - Mensing, Friedrich A1 - Kruschwitz, Sabine T1 - Estimation of cement content in concrete by spatially resolved laser induced breakdown spectroscopy N2 - The cement content in concrete significantly influences critical properties such as durability, permeability, strength, and workability. Traditional methods for estimating the cement content face limitations. These include the need for comprehensive chemical and solubility knowledge, extensive sample preparation, and their time-consuming and destructive nature. This study investigates the application of laser-induced breakdown spectroscopy (LIBS) as an alternative method. It involves probing concrete samples with high spatial resolution and analyzing the resultant spectra. The methodology is first tested on mesoscale concrete models to assess limitations and inherent errors. Subsequently, the methodology is applied to actual concrete samples with varying cement content and aggregate size distributions. The results demonstrate a promising accuracy, with an average relative error of approximately 8%. This paper offers a comprehensive evaluation of the method's advantages, limitations, and factors influencing its practical applicability in field conditions. KW - LIBS KW - Spectroscopy KW - Cement content KW - Elemental mapping PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-620112 DO - https://doi.org/10.1016/j.cemconres.2024.107714 SN - 1873-3948 VL - 189 SP - 1 EP - 10 PB - Elsevier Ltd. AN - OPUS4-62011 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Tobias A1 - Blaschke, Jil A1 - Lierenfeld, Matthias A1 - Wilsch, Gerd A1 - Dalichow, Dirk A1 - Truffer, Philipp A1 - Kruschwitz, Sabine T1 - Aktuelle Anwendungsbeispiele der laserinduzierten Plasmaspektroskopie in der Bauwerksdiagnostik N2 - Die Zustandsbewertung und Instandhaltung von Betonbauwerken erfordert zuverlässige und effiziente Analysemethoden, um komplexe Schadensmechanismen frühzeitig erkennen und fundiert bewerten zu können. Klassische chemisch-analytische Verfahren in der Betonanalytik liefern zwar präzise Ergebnisse bezogen auf die Probenmasse, sind jedoch mit erheblichem Laboraufwand verbunden, in ihrer räumlichen Auflösung durch die Probenahme begrenzt und hinsichtlich der Ergebnisinterpretation mit Unsicherheiten behaftet. Die laserinduzierte Plasmaspektroskopie (LIBS) bietet hier ein hohes Potenzial als schnelle, bildgebende und weitgehend zerstörungsarme Alternative. In den vergangenen Jahren hat sich das Verfahren zunehmend in der Bauwerksdiagnostik etabliert und wird heute für ein breites Spektrum an Anwendungen eingesetzt. Der vorliegende Beitrag gibt einen Überblick über den aktuellen Stand der LIBS-Anwendungen und zeigt anhand ausgewählter Praxisbeispiele die Leistungsfähigkeit, den Mehrwert, die Grenzen und die zukünftigen Entwicklungsperspektiven des Verfahrens auf. KW - LIBS KW - Spektroskopie KW - Chemische Analyse KW - Infrastruktur KW - Bauwerksdiagnostik PY - 2026 DO - https://doi.org/10.1002/best.70078 SN - 1437-1006 SP - 1 EP - 13 AN - OPUS4-65445 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Moreno Torres, Benjami A1 - Zia, Ghezal Ahmad Jan A1 - Rug, Tehseen A1 - Firdous, Rafia A1 - Böhmer, Felix A1 - Stephan, Dietmar A1 - Kruschwitz, Sabine T1 - Presenting SLAMD – A Sequential Learning Based Software for the Inverse Design of Sustainable Cementitious Materials N2 - In recent decades, the number of components in concrete has grown, particularly in formulations aimed at reducing carbon footprints. Innovations include diverse binders, supplementary cementitious materials, activators, concrete admixtures, and recycled aggregates. These developments target not only the enhancement of material properties but also the mitigation of the ecological and economic impacts of concrete — the most extensively used material by humankind. However, these advancements also introduce a greater variability in the composition of raw materials. The material’s behavior is significantly influenced by its nanoscale properties, which can pose challenges in accurate characterization. Consequently, there’s an increasing need for experimental tuning of formulations. This is accompanied by a more inconsistent composition of raw materials, which makes an experimental tuning of formulations more and more necessary. However, the increased complexity in composition presents a challenge in finding the ideal formulation through trial and error. Inverse design (ID) techniques offer a solution to this challenge by allowing for a comprehensive search of the entire design space to create new and improved concrete formulations. In this publication, we introduce the concept of ID and demonstrate how our open-source app “SLAMD” provides all necessary steps of the workflow to adapt it in the laboratory, lowering the application barriers. The intelligent screening process, guided by a predictive model, leads to a more efficient and effective data-driven material design process resulting in reduced carbon footprint and improved material quality while considering socio-economic factors in the materials design. KW - Sustainable concrete KW - Machine learning optimization KW - Inverse design techniques KW - Scientific software KW - Data-driven material design PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-589993 DO - https://doi.org/10.17756/nwj.2023-s2-032 VL - 9 SP - 180 EP - 187 AN - OPUS4-58999 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Moreno Torres, Benjami A1 - Rug, Tehseen A1 - Firdous, Rafia A1 - Zia, Ghezal Ahmad Jan A1 - Lüders, Stefan A1 - Lisdero Scaffino, Horacio A1 - Höpler, Michael A1 - Böhmer, Felix A1 - Pfaff, Matthias A1 - Stephan, Dietmar A1 - Kruschwitz, Sabine T1 - Data driven design of alkali-activated concrete using sequential learning N2 - This paper presents a novel approach for developing sustainable building materials through Sequential Learning. Data sets with a total of 1367 formulations of different types of alkali-activated building materials, including fly ash and blast furnace slag-based concrete and their respective compressive strength and CO2-footprint, were compiled from the literature to develop and evaluate this approach. Utilizing this data, a comprehensive computational study was undertaken to evaluate the efficacy of the proposed material design methodologies, simulating laboratory conditions reflective of real-world scenarios. The results indicate a significant reduction in development time and lower research costs enabled through predictions with machine learning. This work challenges common practices in data-driven materials development for building materials. Our results show, training data required for data-driven design may be much less than commonly suggested. Further, it is more important to establish a practical design framework than to choose more accurate models. This approach can be immediately implemented into practical applications and can be translated into significant advances in sustainable building materials development. KW - Sustainable building materials KW - Sequential learning KW - Data-driven materials design KW - Alkali-activated building materials PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-584376 UR - https://www.sciencedirect.com/science/article/pii/S095965262302379X DO - https://doi.org/10.1016/j.jclepro.2023.138221 SN - 0959-6526 SN - 1879-1786 VL - 418 SP - 1 EP - 13 PB - Elsevier CY - Amsterdam AN - OPUS4-58437 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Firdous, R. A1 - Kruschwitz, Sabine A1 - Stephan, D. T1 - Sequential learning to accelerate discovery of alkali-activated binders N2 - Alkali-activated binders (AAB) can provide a clean alternative to conventional cement in terms of CO2 emissions. However, as yet there are no sufficiently accurate material models to effectively predict the AAB properties, thus making optimal mix design highly costly and reducing the attractiveness of such binders. This work adopts sequential learning (SL) in high-dimensional material spaces (consisting of composition and processing data) to find AABs that exhibit desired properties. The SL approach combines machine learning models and feedback from real experiments. For this purpose, 131 data points were collected from different publications. The data sources are described in detail, and the differences between the binders are discussed. The sought-after target property is the compressive strength of the binders after 28 days. The success is benchmarked in terms of the number of experiments required to find materials with the desired strength. The influence of some constraints was systematically analyzed, e.g., the possibility to parallelize the experiments, the influence of the chosen algorithm and the size of the training data set. The results show the advantage of SL, i.e., the amount of data required can potentially be reduced by at least one order of magnitude compared to traditional machine learning models, while at the same time exploiting highly complex information. This brings applications in laboratory practice within reach. KW - Alkali-activated binders KW - Machine learning KW - Sequential learning KW - Materials by design KW - Materials informatics PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-531376 DO - https://doi.org/10.1007/s10853-021-06324-z SN - 0022-2461 SN - 1573-4803 VL - 56 SP - 15859 EP - 15881 PB - Springer CY - Dordrecht AN - OPUS4-53137 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Valdestilhas, Andre A1 - Bayerlein, Bernd A1 - Moreno Torres, Benjami A1 - Zia, Ghezal Ahmad Jan A1 - Muth, Thilo T1 - The Intersection Between Semantic Web and Materials Science N2 - The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE. KW - Linked open data KW - Materials science KW - Ontology KW - Semantic web PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-575506 DO - https://doi.org/10.1002/aisy.202300051 PB - Wiley-VCH GmbH CY - Weinheim AN - OPUS4-57550 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ulbricht, Alexander A1 - Gollwitzer, Christian A1 - Kupsch, Andreas A1 - Léonard, Fabien A1 - Müller, Bernd R. A1 - Oesch, Tyler A1 - Onel, Yener A1 - Thiede, Tobias A1 - Zscherpel, Uwe ED - Puente León, F. ED - Zagar, B. T1 - Moderne Methoden der CT-gestützten Strukturanalyse T1 - Modern techniques of CT based structure analysis N2 - Durch den großflächigen Einsatz der Computertomographie (CT) in unterschiedlichen Industriebereichen steigen auch die Anforderungen an die quantitative Bildanalyse. Subjektive Bildwahrnehmung muss durch objektive Algorithmen ersetzt werden. In diesem Artikel stellt die Bundesanstalt für Materialforschung und -prüfung (BAM), die seit den 1980er Jahren an der Entwicklung der industriellen CT beteiligt ist, anhand ausgewählter Beispiele den aktuellen Stand ihrer Analysemethoden an verschiedenen Anwendungsbeispielen der CT vor. N2 - The increasing use of computed tomography (CT) in various industrial sectors requires more sophisticated techniques of quantitative image analysis. Subjective image perception needs to be replaced by objective algorithms. The German Federal Institute for Materials Research and Testing (BAM) has been involved in the development of industrial CT since the 1980s. This paper summarizes the current status of quantitative 3D image analysis techniques based on selected examples. KW - Computed tomography KW - Computertomographie KW - Röntgen-Refraktion KW - X-Ray refraction KW - Schadensanalyse KW - Damage analysis KW - Normung KW - standardization PY - 2020 DO - https://doi.org/10.1515/teme-2019-0125 SN - 0171-8096 SN - 2196-7113 VL - 87 IS - 2 SP - 81 EP - 91 PB - de Gruyter CY - Berlin AN - OPUS4-50337 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ukrainczyk, Neven A1 - Bernard, Thomas A1 - Babaahmadi, Arezou A1 - Huang, Liming A1 - Zausinger, Christoph A1 - Soive, Anthony A1 - Bonnet, Stéphanie A1 - Georget, Fabien A1 - Mrak, Maruša A1 - Dolenec, Sabina A1 - Völker, Tobias A1 - Suraneni, Prannoy A1 - Wilson, William T1 - Test methods for chloride diffusivity of blended cement pastes: a review by RILEM TC 298-EBD N2 - The use of supplementary cementitious materials (SCM) is an important part of the roadmap for reducing CO2 emissions and extending the service life of reinforced concrete structures. To accelerate the adoption of SCMs, the RILEM Technical Committee 298-EBD evaluates scaled-down cement paste test methods to assess the effect of SCM on resistance to chloride and sulfate ingress and reactivity, which are critical to concrete durability. This review focuses on methods for measuring chloride diffusivity and is divided into four sections: diffusivity models and parameters, diffusion test methods (including NMR and chloride measurements), migration test methods and implications for future research. Key insights highlight the complexities of multi-species ionic and molecular diffusion/migration, including various binding interactions, and compares the different measurement methodologies. The review also addresses the test scale and aggregate effects, noting the pros and cons of testing at the paste, mortar, and concrete scales. The review underscores the need for further investigation into testing protocols and the influence of SCM on chloride diffusion, emphasizing that comprehensive testing across different scales provides complementary information for assessing durability performance. KW - Chloride ingress KW - Diffusion tests KW - Migration test KW - Cement paste KW - Concrete KW - Supplementary cementitious materials (SCM) PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-645889 DO - https://doi.org/10.1617/s11527-025-02809-4 SN - 1359-5997 VL - 58 IS - 10 SP - 1 EP - 35 PB - Springer Science and Business Media LLC AN - OPUS4-64588 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -