TY - CONF A1 - Koch, Claudia T1 - Eine moderne Qualitätsinfrastruktur: digital und vernetzt N2 - Überblick über die digitale Transformation der Qualitätsinfrastruktur (QI), die Initiative QI-Digital sowie die Aktivitäten der BAM. T2 - 11. Sitzung DGZfP UA Schnittstellen, Dokumentation, Datensouveränität Speicherung, Archivierung CY - Saarbrücken, Germany DA - 11.4.2024 KW - Qualitätsinfrastruktur KW - Qualitätssicherung KW - Zerstörungsfreie Prüfung KW - digitale Transformation KW - Smart Standard KW - Digitales Zertifikat KW - Quality-X PY - 2024 AN - OPUS4-60347 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Schottner, G. A1 - Wondraczek, L. A1 - Sierka, M. A1 - Deubener, J. A1 - Waurischk, Tina A1 - Reinsch, Stefan A1 - Contreras, A. A1 - Diegeler, A. A1 - Kilo, M. A1 - Pan, Z.-W. A1 - Arendt, F. A1 - Chen, Y.-F. A1 - Gogula, S. A1 - Bornhöft, H. T1 - GlasDigital: Data-driven workflow for accelerated glass development N2 - Glasses stand out by their wide and continuously tunable chemical composition and large variety of unique shaping techniques making them a key component of modern high technologies. Glass development, however, is still often too cost-, time- and energy-intensive. The use of robotic melting systems embedded in an ontology-based digital environment is intended to overcome these problems in future. As part of the German research initiative MaterialDigital, the joint project GlasDigital takes first steps in this direction. The project consortium involves the Fraunhofer ISC in Würzburg, the Friedrich Schiller University Jena (OSIM), the Clausthal University of Technology (INW), and the Federal Institute for Materials Research and Testing (BAM, Division Glasses) and aims to combine all main basic components required for accelerated data driven glass development. For this purpose, a robotic high throughput glass melting system is equipped with novel inline sensors for process monitoring, machine learning (ML)-based, adaptive algorithms for process monitoring and optimization, novel tools for high throughput glass analysis and ML-based algorithms for glass design, including software tools for data mining as well as property and process modelling. The talk gives an overview how all these tools are interconnected and illustrates their usability with some examples. T2 - USTV-DGG joint meeting CY - Orleans, France DA - 22.05.2023 KW - Glass KW - Ontology KW - Data Space KW - Workflow KW - Robotic melting PY - 2023 AN - OPUS4-60372 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Diegeler, A. A1 - Schottner, G. A1 - Niebergall, R. A1 - Kilo, M. A1 - Arendt, F. A1 - Chen, Y.-F. A1 - Sierka, M. A1 - Limbach, R. A1 - Pan, Z. A1 - Wondraczek, L. A1 - Gogula, S. A1 - Bornhöft, H. A1 - Deubener, J. A1 - Waurischk, Tina A1 - Reinsch, Stefan T1 - GlassDigital: Digital Infrastructure for Data-Driven High-Throughput Glass Development N2 - Gläser zeichnen sich durch eine breite und kontinuierlich abstimmbare chemische Zusammensetzung sowie einzigartige Formgebungstechniken aus, was sie oft zur Schlüsselkomponente moderner Hochtechnologien macht. Die Glasentwicklung ist jedoch oft noch zu kosten-, zeit- und energieintensiv. Der Einsatz von robotergestützten Schmelzsystemen, eingebettet in eine Ontologie-basierte digitale Umgebung, soll diese Probleme in Zukunft überwinden. Im Rahmen der BMBF Forschungsinitiative MaterialDigital unternimmt das Verbundprojekt GlasDigital „Datengetriebener Workflow für die beschleunigte Entwicklung von Glas“ erste Schritte in diese Richtung. Das Projektkonsortium, an dem das Fraunhofer ISC in Würzburg, die Friedrich-Schiller-Universität Jena (OSIM), die Technische Universität Clausthal (INW) und die Bundesanstalt für Materialforschung und -prüfung (BAM, Fachgruppe Glas) beteiligt sind, will alle wesentlichen Basiskomponenten für eine beschleunigte datengetriebene Glasentwicklung zusammenführen. Zu diesem Zweck wird ein robotergestütztes Hochdurchsatz-Glasschmelzsystem mit neuartigen Inline-Sensoren zur Prozessüberwachung, auf maschinellem Lernen (ML) basierenden adaptiven Algorithmen zur Prozessüberwachung und -optimierung, neuartigen Werkzeugen für die Hochdurchsatz-Glasanalyse sowie ML-basierten Algorithmen zum Glasdesign, Data Mining sowie Eigenschafts- und Prozessmodellierung ausgestattet. Der Vortrag gibt einen Überblick darüber, wie all diese Komponenten miteinander verzahnt sind, und veranschaulicht ihre Nutzbarkeit anhand einiger Beispiele. T2 - HVG-Fortbildungskurs CY - Offenbach, Germany DA - 27.11.2023 KW - Glas KW - Ontology KW - Workflow KW - Simulation KW - Robotic melting PY - 2023 AN - OPUS4-60386 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Niebergall, R. A1 - Schottner, G. A1 - Wondraczek, L. A1 - Sierka, M. A1 - Deubener, J. A1 - Waurischk, Tina A1 - Reinsch, Stefan A1 - Contreras, A. A1 - Diegeler, A. A1 - Kilo, M. A1 - Puppe, F. A1 - Limbach, R. A1 - Pan, Z. A1 - Arendt, F. A1 - Chen, Y.-F. A1 - Gogula, S. A1 - Bornhöft, H. T1 - GlasDigital: Data-driven workflow for accelerated glass development N2 - lasses stand out by their wide and continuously tunable chemical composition and large variety of unique shaping techniques making them a key component of modern high technologies. Glass development, however, is still often too cost-, time- and energy-intensive. The use of robotic melting systems embedded in an ontology-based digital environment is intended to overcome these problems in future. As part of the German research initiative MaterialDigital, the joint project GlasDigital takes first steps in this direction. The project consortium involves the Fraunhofer ISC in Würzburg, the Friedrich Schiller University Jena (OSIM), the Clausthal University of Technology (INW), and the Federal Institute for Materials Research and Testing (BAM, Division Glasses) and aims to combine all main basic components required for accelerated data driven glass development. For this purpose, a robotic high throughput glass melting system is equipped with novel inline sensors for process monitoring, machine learning (ML)-based, adaptive algorithms for process monitoring and optimization, novel tools for high throughput glass analysis and ML-based algorithms for glass design, including software tools for data mining as well as property and process modelling. The talk gives an overview how all these tools are interconnected and illustrates their usability with some examples. T2 - HVG-DGG Fachausschuss I CY - Jena, Germany DA - 03.11.2023 KW - Glass KW - Robotic melting KW - Ontologie KW - Simulation KW - Workflow KW - Data Space PY - 2023 AN - OPUS4-60383 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd A1 - Schilling, Markus A1 - Birkholz, Henk T1 - Digital Transformation in Materials Science: Insights From the Platform MaterialDigital (PMD) N2 - The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations. T2 - NIST Seminar on Digital Transformation CY - Gaithersburg, MD, USA DA - 11.06.2024 KW - Digital Transformation KW - Research Data Management KW - Ontology KW - Reusability KW - FAIR PY - 2024 AN - OPUS4-60381 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schlegel, Moritz-Caspar T1 - Circular Economy in der EU - ein neues Verständnis für Produkteffizienz, die EN4555x-Reihe und weitere Beipiele N2 - Übersicht über die Umsetzung des EU Green New Deal, des Circular Economy Action Plan sowie der Sustainable Product Initiative. Ebenfalls erfolgt eine Zusammenfassung der Auswirkungen der Änderungen im EU-Produktrecht auf die Revision des geltenden Rechts und das Zusammenspiel zwischen Rechtssetzung und Normung. T2 - Besuch des Bachelorstudiengangs im Fachbereich Material Knowledge der Fachhochschule Potsdam CY - Berlin, Germany DA - 28.05.2024 KW - Circular Economy KW - ESPR KW - Material efficiency KW - Normung KW - Policy making KW - Labelling PY - 2024 AN - OPUS4-60407 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schlegel, Moritz-Caspar T1 - Rechtsetzungbegleitende Normung zur Circular Economy von Produkten - Beispiel IKT N2 - Überblick über Aktionspläne, Initiativen und Maßnahmen der EU zur Steigerung der Zirkularität von Produkten aus der Informations- und Kommunikationstechnik. Des Weiteren eine Übersicht über relevante nationale und europäische Normungsgremien und die Beteiligung der BAM. T2 - Gründungssitzung des Forschungsfabrik Mikroelektronik Deutschland (FMD) CY - Online meeting DA - 31.01.2024 KW - Circular Economy KW - ESPR KW - Energy labelling KW - Normung KW - Policy making KW - Standardization PY - 2024 AN - OPUS4-60397 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schlegel, Moritz-Caspar T1 - Circular Economy bei der BAM - neu und etabliert zugleich N2 - Übersicht über BAM-Aktivitäten, die ebenfalls der BAM zugeordnet werden können, der Gründung des Aktivitätsfeldes Circular Economy innerhalb der BAM sowie die zukünftige Ausrichtung und Aktivitäten der BAM zu Themen der Circular Economy. T2 - Besuch des Bachelorstudiengangs im Fachbereich Material Knowledge der Fachhochschule Potsdam CY - Berlin, Germany DA - 28.05.2024 KW - Circular Economy PY - 2024 AN - OPUS4-60410 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schilling, Markus A1 - Bayerlein, Bernd A1 - Birkholz, H. T1 - Digital Transformation in Materials Science: Insights from Platform MaterialDigital (PMD), Tensile Test Ontology (TTO), Electronic Lab Notebooks (ELN) N2 - The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations. T2 - NIST Seminar Series CY - Gaithersburg, MD, USA DA - 11.06.2024 KW - Semantic Data KW - Plattform Material Digital KW - Digitalization KW - Data Interoperability KW - NIST KW - Tensile Test Ontology KW - Elctronic Lab Notebook PY - 2024 AN - OPUS4-60392 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schlegel, Moritz-Caspar T1 - Stand der Durchführungsmaßnahmen und delegierte Rechtsakte - Zusammenfassung und Ausblick N2 - Übersicht über den Aktuellen Stand der Durchführungsmaßnahmen der EU zur Ökodesign-Richtlinie sowie der delegierten Rechtsakte zum EU Energielabel. Der Fokus liegt auf die Änderungen bzgl. gesetzlicher Anforderungen, die Überwachung durch die Vollzugsbehörden und mögliche diesbezügliche Informationsquellen. T2 - Praxisworkshop Marktüberwachung EVPG / EnVKG CY - Weilburg, Germany DA - 14.05.2024 KW - Ecodesign KW - EU Energy Label KW - Policy making KW - Market suveillance PY - 2024 AN - OPUS4-60409 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Data-Driven Chemical Understanding with Bonding Analysis N2 - Bonds and local atomic environments are crucial descriptors of material properties. They have been used to create design rules and heuristics and as features in machine learning of materials properties. Implementations and algorithms (e.g., ChemEnv and LobsterEnv) for identifying local atomic environments based on geometrical characteristics and quantum-chemical bonding analysis are nowadays available. Fully automatic workflows and analysis tools have been developed to use quantum-chemical bonding analysis on a large scale. The lecture will demonstrate how our tools, that assess local atomic environments and perform automatic bonding analysis, help to develop new machine learning models and a new intuitive understanding of materials. Furthermore, the general trend toward automation in density functional-based materials science and some of our recent contributions will be discussed. T2 - Otaniemi Center for Atomic-scale Materials Modeling Seminar CY - Aalto, Finland DA - 11.03.2024 KW - Automation KW - Materials Design KW - Bonding Analysis KW - Machine Learning PY - 2024 AN - OPUS4-59671 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - New Opportunities for Data-Driven Chemistry and Materials Science Through Automation N2 - In recent years, many protocols in computational materials science have been automated and made available within software packages (primarily Python-based). This ranges from the automation of simple heuristics (oxidation states, coordination environments) to the automation of protocols, including multiple DFT and post-processing tools such as (an)harmonic phonon computations or bonding analysis. Such developments also shorten the time frames of projects after such developments have been made available and open new possibilities. For example, we can now easily make data-driven tests of well-known rules and heuristics or develop quantum chemistry-based materials descriptors for machine learning approaches. These tests and descriptors can have applications related to magnetic ground state predictions of materials relevant for spintronic applications or for predicting thermal properties relevant for thermal management in electronics. Combining high-throughput ab initio computations with fitting, fine-tuning machine learning models and predictions of such models within complex workflows is also possible and promises further acceleration in the field. In this talk, I will show our latest efforts to link automation with data-driven chemistry and materials science. T2 - MRS Spring CY - Seattle, Washington, USA DA - 21.04.2024 KW - Automation KW - Workflows KW - Chemical Bonding KW - Thermal Properties KW - Materials Design PY - 2024 AN - OPUS4-59982 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - High-throughput and automated bonding Analysis N2 - Talk as a part of the LOBSTER CECAM SCHOOL. This talk introduced all participants to automation tools around the software LOBSTER. T2 - CECAM LOBSTER School CY - Aalto, Finland DA - 12.03.2024 KW - Automation KW - Workflows KW - Bonding Analysis KW - Materials Design KW - Chemically Complex Materials PY - 2024 AN - OPUS4-59672 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Data-driven approaches for materials understanding and design N2 - Bonds and local atomic environments are crucial descriptors of material properties. They have been used to create design rules and heuristics and as features in machine learning of materials properties. Implementations and algorithms (e.g., ChemEnv and LobsterEnv) for identifying local atomic environments based on geometrical characteristics and quantum-chemical bonding analysis are nowadays available. Fully automatic workflows and analysis tools have been developed to use quantum-chemical bonding analysis on a large scale. The lecture will demonstrate how our tools, that assess local atomic environments and perform automatic bonding analysis, help to develop new machine learning models and a new intuitive understanding of materials. Furthermore, the general trend toward automation in computational materials science and some of our recent contributions will be discussed. T2 - Machine Learning of First Principles Observables CY - Berlin, Germany DA - 08.07.2024 KW - Automation KW - Bonding Analysis KW - Machine Learned Potentials PY - 2024 AN - OPUS4-60660 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maaß, Robert T1 - On an unusual career path and unusual transport in metallic glasses N2 - Planning an academic career is a bit like enjoying a box of chocolate – you never know what you are going to get next. In this talk, I will begin with sharing how luck, difficult decisions, fate, and family constraints affected my career path across continents, universities, the private sector, and to becoming a director at a national laboratory. This journey was certainly not planned and highlights how opportunities and compromises together allow you to make much more out of your engineering degree than you ever have dreamed of. After this unusual journey as a materials scientist, I am transitioning to the technical part of my talk, where we will discuss transport in metallic glasses. This out-of-equilibrium material has a long suite of remarkable mechanical and physical properties but suffers from property deterioration via physical aging. As a function of time, relaxation may indeed constitute significant threads to safe applications, such as a complete loss of toughness. In the search for a physical understanding of aging, we exploit here the ability to track atomic-scale dynamics with coherent x-ray scattering. Conducted across temperatures and under the application of stress, the results reveal unexpected transport. In concert with microsecond molecular dynamic simulations, we identify possible mechanisms of atomic-scale dynamics that underly physical aging of metallic glasses. We find that classical Kohlrausch-Williams-Watts behavior is only suited for the short relaxation-time regime, whereas anomalous diffusion emerges at practically relevant times. We discuss these results in terms of the structural relaxation modes and propose a picture of a true microstructure in metallic glasses. T2 - Department Seminar IIT Delhi 2023 CY - Delhi, India DA - 15.12.2023 KW - Metallic glass KW - Transport KW - Structure KW - Dynamics PY - 2023 AN - OPUS4-60649 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maaß, Robert A1 - Rizzardi, Quentin A1 - Mc Elfresh, Cameron A1 - Sparks, Gregory T1 - Transitions from scale-free to scale-dependent fluctuations in plasticity N2 - Plastic deformation in crystals is mediated by the motion of line defects known as dislocations. For decades, dislocation activity has been treated as a homogeneous, smooth continuous process that relies on well-average quantities. However, it is now recognized that plasticity can be determined by long-range correlated and intermittent collective dislocation activity, known as avalanches. These abrupt plastic fluctuations often exhibit pure power-law scaling or truncated power-law scaling, which indicates at least some degree of scale-free dislocation behavior. Intriguingly, such statistical signatures can persist across scales exceeding those of the material’s microstructure, raising the question of what relationship there may be between structure and long-range correlated dislocation activity that underlie power-law scaling. In this talk, we address this question by highlighting examples in which a transition from scale-free to scale-dependent plastic deformation is observed either due to changing external testing conditions (stress-state or temperature) or by tuning the microstructure. In particular, we will focus on the details of the temperature-driven change, that demonstrates how scale-free intermittent flow in body-centered cubic Nb is progressively quenched out with decreasing temperature. The plastic response of Nb is shown to be bimodal across the studied temperature regime, with conventional thermally-activated smooth plastic flow coexisting with sporadic bursts controlled by athermal screw dislocation activity, thereby violating the classical notion of temperature-dependent screw dislocation motion at low temperatures. An abrupt increase of the athermal avalanche component is identified at the critical temperature of the material. We combine the experimental observations with 3D dislocation dynamics simulations, identify a possible origin to athermal screw activity, and discuss the co-existence scale-free and scale-dependent plasticity. T2 - Cairo Symposium on The Physics of Metal Plasticity CY - Cairo, Egypt DA - 05.09.2023 KW - Plastic deformation KW - Dislocations KW - Avalanches PY - 2023 AN - OPUS4-60648 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Maaß, Robert A1 - Ikdea, Yuki A1 - Yuan, Renliang A1 - Chakraborty, Anirban A1 - Ghassemi-Armaki, Hassan A1 - Zuo, Jian-Min A1 - Kamachali, Reza T1 - Liquid Metal Embrittlement in High-Strength Steels N2 - One contribution of materials science to energy efficiency is the continuous development of novel high-performance structural materials that push the strength-ductility envelope. A prominent example are modern advanced high-strength steels (AHSSs), which have enabled considerable weight reductions in the automotive sector, thereby enabling greenhouse emission reductions. To protect such advanced alloys from property degradation via corrosion, zinc (Zn) coatings are often applied through galvanization. Whilst protective, a Zn-coating comes with problems – the AHSS substrate becomes susceptible for liquid-metal embrittlement (LME) than can be the origin of significant mechanical property degradation when liquified Zn infiltrates into the steel substrate. Being for from understood, we focus here on non-cracked environments to capture the early stages of LME. This approach revealed the nucleation and growth of nano-scale intermetallic phases inside uncracked GBs (Materials Today Advances 13, 100196, 2022), highlighting the complex multi-phase microstructure developing before cracking occurs. To shed further light on the early stages of LME in AHSSs, we also consider the microstructural evolution of interrupted welds. We discuss our findings in the context of the time-resolved substructure evolution right beneath the interface between the AHSS and the Zn-based coating and track how Zn progressively infiltrates the substrate along phase and grain boundaries. The experimental results are further corroborated with thermodynamic simulations. T2 - ASATM CY - Singapore DA - 10.01.2023 KW - Liquid-metal embrittlement KW - Steels KW - Grain boundaries KW - Micro-cracking PY - 2023 AN - OPUS4-60647 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Markötter, Henning A1 - Sintschuk, Michael A1 - Dayani, Shahabeddin A1 - Mishurova, Tatiana A1 - Mehta, B. A1 - Eddah, Mustapha A1 - Mieller, Björn A1 - Böttcher, Nils A1 - Krug von Nidda, Jonas T1 - In situ tomographic imaging with hard x rays at Bamline (BESSY II) N2 - The BAMline at the synchrotron X-ray source BESSY II (Berlin, Germany) is supporting researchers especially in materials science [1]. As a non-destructive characterization method, synchrotron X-ray imaging, especially tomography (SXCT) with hard X-Rays, plays an important role in structural 3D characterization. The imaging capabilities allow for in-situ and operando experiments. In this presentation the equipment, data handling pipeline as well as various examples from material science are presented. In series-connected lithium-ion cells are susceptible to an electrical safety hazard called over-discharge. Here the behavior of copper dissolution and deposition during over-discharge is presented, which leads to irreversible loss of capacity and internal short circuits. The concentration of dissolved and deposited copper is quantified. Also, a non-uniform distribution pattern of copper deposition on the cathode is shown. The second example deals with an Al alloy 7017 customized for a 3d-printing process by means of laser-based powder bed fusion (PBF-LB) technique. These advanced alloys have a significantly higher modulus of elasticity than conventional Al alloys, making them attractive for applications requiring high stiffness. SXCT during In-situ tensile tests confirmed that fracture initiation strongly depends on defects created during printing. However, the cracks are deflected from decohesion around inclusions/precipitates embedded in the Al matrix, increasing ductility. Low temperature cofired ceramic (LTCC) multilayer housings offer 3D-circuits for a wide range of applications in telecommunications, microsystems and sensor technology. Such housings are produced by combining structured and metallized ceramic layers using tape-casting and multilayer technology. The characterization of the integrity, deformation, defects, and positioning of the internal metal features was carried out using in-situ SXCT at up to 950°C. A high-precision nail penetration tool was developed to characterize the mechanically induced thermal runaway (TR) of lithium-ion battery (LIB) cells in a dynamic temperature range down to -190 °C. To investigate safety-specific low-temperature transport conditions, the damaged cells were tomographically imaged during thawing. T2 - ICTMS - International Conference on Materials and Structures 2024 CY - Cape Town, South Africa DA - 01.07.2024 KW - Synchrotron radiation KW - X-ray tomography KW - Li-ion battery PY - 2024 AN - OPUS4-60658 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schartel, Bernhard T1 - Fire Behaviour and Flame Retardancy of Polymeric Materials N2 - Lecture-like introduction in the topic. Fundamental aspects are discussed: Burning of polymers, fire risks, pyrolysis, combustion in the flame, physical chemistry of ignition, flame spread and steady state burning, flame retardancy mechanisms and groups of flame retardants, fire hazards (smoke, toxic products) and environmental concerns, fire testing. T2 - International Combustion Institute Summer School on Near-Wall Reactive Flows CY - Darmstadt, Germany DA - 10.06.2024 KW - Flame retardants KW - Fire behaviour PY - 2024 AN - OPUS4-60246 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -