5 Werkstofftechnik
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Lightweighting as a cross-cutting technology contributes significantly to achieve the European Green Deal goals. Based on, but not limited to, advanced materials and production technologies, the demand for natural resources and CO2 emmissions are reduced by lightweighting during production, as well as use phase. Therefore, lightweighting is a crucial transformation technology assisting in decoupling economic growth from resource consumption. In this manner, lightweighting contributes significantly as a key technology of relevance for many industrial sectors such as energy, mobility, and infrastructure, towards resource efficiency, climate action and economic strength, as well as a resilient Europe. To strengthen international partnerships, addressing global issues of today at the edge of science with high performance lightweight material based on carbon fibers, an overview about the BAM expertise in carbon fiber reinforced materials is given.
This research deals with the development of the Vickers hardness knowledge graph, mapping the example dataset in them, and exporting the data-mapped knowledge graph as a machine-readable Resource Description Framework (RDF). Modeling the knowledge graph according to the standardized test procedure and using the appropriate upper-level ontologies were taken into consideration to develop the highly standardized, incorporable, and industrial applicable models. Furthermore, the Ontopanel approach was utilized for mapping the real experimental data in the developed knowledge graphs and the resulting RDF files were successfully evaluated through the SPARQL queries.
The high-temperature corrosion behaviors of the equimolar CrCoNi medium- and CrMnFeCoNi high-entropy alloy were studied in a gas atmosphere consisting of a volumetric mixture of 10% H2O, 2% O2, 0.5% SO2, and 87.5% Ar at 800 °C for up to 96 h. Both alloys were initially single-phase fcc structured and showed a mean grain size of ~50 µm and a homogeneous chemical composition. The oxide layer thickness of the Cantor alloy CrMnFeCoNi increased linearly with exposure time while it remained constant at ~1 µm for CrCoNi. A Cr2O3 layer and minor amounts of (Co,Ni)Cr2O4 developed on CrCoNi while three layers were detected on the Cantor alloy. These layers were a thin and continuous chromium rich oxide layer at the oxide/alloy interface, a dense (Mn,Cr)3O4 layer in the center and a thick and porous layer of Mn3O4 and MnSO4 at the gas/oxide interface. Additionally, a few metal sulfides were observed in the CrMnFeCoNi matrix. These results were found to be in reasonable agreement with thermodynamic calculations.
Der Beitrag behandelt verschiedene Themen aus dem H2Safety@BAM-Kompetenzfeld Sensorik, Analytik und zertifizierte Referenzmaterialien (SensRef) mit Schwerpunkt auf Mess- und Prüfverfahren, die verschiedene Analyseverfahren, Sensortechnologien und Ultraschallwellen nutzen. Ein Teil davon ist das Euramet-Vorhaben "MefHySto" zur Metrologie der Wasserstoffspeicherung. Des Weiteren werden Verfahren zur Erkennung von freigesetztem Wasserstoff und zur Bestimmung des Wasserstoff-Luftverhältnisses mithilfe von Gassensoren behandelt. Ein weiterer Aspekt ist die zerstörungsfreie Fehlstellenerkennung mit einem integrierten Zustandsüberwachungssystem, das auf geführten Ultraschallwellen basiert und zur Überwachung der Lebensdauer von Composite-Behältern (Wasserstoffspeicher) dient. Zudem wird die Anwendung faseroptischer Sensorik zur Schadenfrüherkennung an Wasserstoffspeichern diskutiert. Dabei werden erkennbare Dehnungsänderungen an Druckbehältern als Indikatoren genutzt.
Several recent studies have revealed that the phase decomposition in medium- and high-entropy alloys is triggered by solute segregation at grain boundaries. The chemically complex nature of these alloys already clues that such segregation in materials should be something more than the interaction between solutes and grain boundary, but also affected by the solute-solute interactions during the segregation. In fact, experiments indicate the significance of such solute-solute interaction. Yet, the mechanisms of co-segregation in multi-component alloys are rather challenging to explore and rarely studied quantitatively. Recently, a CALPHAD-integrated density-based phase-field model has been proposed for studying grain boundary phenomena. Several applications of this model have shown its expansive capacity for investigating grain boundary segregation and phase behavior. In this talk, the applications of this model to studying co-segregation phenomena and grain boundary phase diagrams in multi-component alloys are presented ––the term ‘co-segregation’ here refers to co-evolution and any mutual interplay among the solutes and grain boundary during the segregation. In particular, the iron-based ternary and quaternary alloys are discussed. I show how a grain boundary may have its own miscibility gap and how this immiscibility can influence the co-segregation behavior. As an alternative to grain boundary phase diagrams, rather suited for binary and ternary alloys, a new concept of co-segregation maps for screening and segregation design in multi-component alloys is presented. Applying the co-segregation maps, the nonlinear Mn and Cr co-segregation in Fe-Co-Mn-Cr is discussed.
Grain boundary (GB) chemical and structural variations can significantly influence materials performance. The former is generally ascribed to the structural gradient between the grain and GB. While GB segregation may be accompanied by chemical and structural variations, clear insights about the GB’s thermodynamic phase behaviour upon coupling between its chemistry and structure is lacking. Using the CALPHAD integrated density-based phase field model, we study the co-evolution of GB’s structure and segregation in Fe-Mn alloys. We found that the GB segregation transition is amplified if its structure can respond to chemical variation. Additionally, the coupling between GB structural and segregation evolution was found to enable co-existence of the spinodally formed low- and high-Mn phases within the GB. In the light of atomistic simulations, we expand on investigating the correlation between the parameters that characterise the GB density map with GB properties.
Recent advances in Deep Learning (DL) have significantly impacted the field of materials modelling. DL tools have been recently considered as promising tools to address the complex relationships among processing, microstructure and property of materials. The thermal stability of polycrystalline materials is a highly interesting and complex problem that could be addressed using DL techniques. The Multi-Phase-Field (MPF) method has emerged as a powerful tool for addressing grain growth phenomena from multiple perspectives. Unlike sharp-interface based methods, the MPF approach bypasses the need for detailed information on individual grains. In this work, we use DL to address issues related to MPF simulations of grain growth including numerical efficiency, computing speed, and resource consumption. This presents specific challenges for high-performance computing (HPC) due to the large datasets and complex computations required by both MPF and DL methods. We study various 3D microstructure settings with the goal of accelerating the simulation process while exploring different physical effects. In particular, the impact of grain boundary and triple junction energies on grain growth are to be investigated. The results will be presented in terms of the evolving size and shape distribution of the grains.