5 Werkstofftechnik
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Paper des Monats
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Efforts towards digitalization in the material science and technology community have enhanced in the last years. In 2019 the German digitalization initiative platform „MaterialDigital“1 (MD) has been started. Numerous projects concerning digitalization, including the copper related project „KupferDigital“ (copper digital) have been initiated under the umbrella of MD. The initiative strives to
address numerous issues concerning data access, exchange, security, provenance and sovereignty. Heterogeneous data origin, storage and evaluation often result in problems concerning comparability and reproducibility of scientific and technological results. In many cases material data are recorded, but the methods of testing are insufficiently described, or such information is not communicated along with the raw data. The material data can also have numerous different formats such as paper printouts, pdfs, excel sheets or csv-files. Hence, gathering and integrating material data from different sources is challenging for potential users like materials scientists and engineers, especially if there are contradictory data where the reasons for contradictions is not clear due their vague description. In order to address these problems, data should comply to the so called „FAIR“ principle which calls for data to be findable, accessible, interoperable, and reusable (FAIR)2 and hence be accessible via so-called decentralized but interconnected data spaces. By using knowledge representation withontologies, data can be enriched with meaning and the methods of the testing procedures can be accurately provided. In this presentation we want to introduce our approach to such knowledge representation based on a high-throughput alloy development process for Cu-based alloys³ along with characterization techniques such as hardness testing and microstructural characterization (e.g. EBSD – Electron Backscattered Diffraction).
A main source of current challenges in materials science and engineering is the ever-increasing complexity in materials chemistry and processing resulting in complex microstructures, making the assessment of process-microstructure-property-performance relations difficult, even unmanageable. Here the computational materials science is facing the same situation. In this talk, I share a viewpoint that the complexities in chemistry, processing and microstructures can be circumscribed by integrating existing knowledges of bulk thermodynamics and kinetics to the unknown thermodynamics and kinetics of microstructure elements. To this end, I discuss several successful examples on grain boundary segregation engineering how this scientific advance can be conducted. A roadmap is proposed, beginning to form on generalizing the concept of phase diagrams.
Präsentation der Aktivitäten an der BAM im Bereich Additive Fertigung unter Mikrogravitationsbedingungen für Anwendungen im Weltraum beim Arbeitsgruppentreffen der AG Werkstoffe & Prozesse vom Netzwerk Space2Motion.
Unlike conventional alloys, high entropy alloys are characterized by one or more solid solution phase(s) without a clearly defined solvent, all element contribute to the matrix in a way that is still not entirely understood. In addition, it is not known to what extent classic thermodynamic rules can be applied to these multi-element alloys, especially concerning the question about what factor incites the matrix to undergo a phase transformation.
This work tackles directly some of these aspects on a chosen alloy, Al8Cr17Co17Cu8Fe17Ni33 (at.%), which presents a high temperature single-phase γ state and a two-phase state with γ′ precipitates, above and below 900 ◦C, respectively. A combined investigation via microstructural observations, hardness testing, X-ray absorption and photoelectron spectroscopy was carried out above the γ′ formation temperature. Hardness values are independent of the annealing temperatures, microstructural analysis shows no phase formation and X-ray absorption spectroscopy does not reveal observable changes in neither local atomic nor electronic structure, indicating that approaching γ′ formation temperature is not influenced by atomic or electronic rearrangements.
Interestingly, short-range chemical order remains quantitatively compatible at any annealing temperature in the single-phase γ state, and the observed preferred pairs Al–Cu and Al–Ni in the γ state match with the γ’ precipitates composition below 900 ◦C.
High- and medium-entropy alloys (HEAs) are a quite new class of materials. They have a high potential for applications from low to high temperatures due to the excellent combination of their structural properties.
Concerning their application as components; processing properties, such as machinability, have hardly been investigated so far. Hence, machinability analyses with a focus on the influence of the milling process and its basic parameters (cutting speed, feed per cutting edge) on the resulting surface integrity of specimens from an equiatomic high- (CoCrFeMnNi) and a medium- (CoCrNi) entropy alloy have been carried out. A highly innovative milling process with ultrasonic assistance (USAM) was compared to conventional milling processes.
Recent studies have shown that USAM has a high potential to significantly reduce the mechanical load on the tool and workpiece surface during milling. In this study, the basic machining and ultrasonic parameters were systematically varied. After machining, the surface integrity of the alloys was analyzed in terms of topography, defects, subsurface damage, and residual stresses. It was observed that USAM reduces the cutting forces and increases the surface integrity in terms of lower tensile residual stresses and defect density near the surfaces for the CoCrFeMnNi alloy. It was shown that the cutting forces and the metallurgical influence in the sub surface region are reduced by increasing the cutting speed and reducing the feed rate per cutting edge. With the CoCrNi alloy, the tool revealed severe wear. As a result, for this alloy no influence of the parameters on the machinability could be determined.
Creep and creep damage behavior of stainless steel 316L manufactured by laser powder bed fusion
(2022)
This study presents a thorough characterization of the creep properties of austenitic stainless steel 316L produced by laser powder bed fusion (LPBF 316L) contributing to the sparse available data to date. Experimental results (mechanical tests, microscopy, X-ray computed tomography) concerning the creep deformation and damage mechanisms are presented and discussed. The tested LPBF material exhibits a low defect population, which allows for the isolation and improved understanding of the effect of other typical aspects of an LPBF microstructure on the creep behavior. As a benchmark to assess the material properties of the LPBF 316L, a conventionally manufactured variant of 316L was also tested. To characterize the creep properties, hot tensile tests and constant force creep tests at 600 °C and 650 °C are performed. The creep stress exponents of the LPBF material are smaller than that of the conventional variant. The primary and secondary creep stages and the times to rupture of the LPBF material are shorter than the hot rolled 316L. Overall the creep damage is more extensive in the LPBF material. The creep damage of the LPBF material is overall mainly intergranular. It is presumably caused and accelerated by both the appearance of precipitates at the grain boundaries and the unfavorable orientation of the grain boundaries. Neither the melt pool boundaries nor entrapped gas pores show a significant influence on the creep damage mechanism.
Rotorblätter von Windenergieanlagen (WEA) weisen häufig nach wenigen Jahren, lange vor dem Erreichen der prognostizierten Lebensdauer von 20 bis 30 Jahren Risse in der Blattschale auf. Die Folge sind aufwendige Reparaturen am installierten und schwer zugänglichen Rotorblatt und der kostenintensive Nutzungsausfall durch den Stillstand der WEA.
Als mögliche Initiatoren für die Schäden in der Blattschale der Rotorblätter gelten fertigungsbedingte Imperfektionen. Für die Untersuchung des Einflusses dieser Imperfektionen auf das Ermüdungsverhalten der Rotorblätter wurde an der BAM (Bundesanstalt für Mate-rialforschung und -prüfung) ein Prüfstand für statische und zyklische Versuche von Schalensegmenten im intermediate scale entwickelt und betrieben. Die untersuchten Schalensegmente in Sandwichbauweise sind der Rotorblattschale von WEA im Hinblick auf die Strukturmechanik, die eingesetzten Halbzeuge, den Laminataufbau und dem eingesetzten Fertigungsverfahren ähnlich. Als Imperfektionen wurden verschiedenen Variationen von Lagenstößen in die Hautlagen und Schaumstöße mit Breitenvariation in den Stützkern reproduzierbar eingebracht. Die Überwachung des Schädigungszustandes während der Schwingversuche unter realistischen Lastszenarien erfolgt über eine kombinierte in situ Schädigungsüberwachung mittels passiver Thermografie und Felddehnungsmessung.
Mit den durchgeführten Schwingversuchen und der begleitenden Überwachung des Schädigungszustandes ließen sich die Schadensinitiation und die signifikante Herabsetzung der Lebensdauer durch die eingebrachten Imperfektionen zweifelsfrei nachweisen und entsprechende Konstruktionshinweise für die betriebssichere Auslegung von Sandwichstrukturen ableiten.
Metal Additive Manufacturing (AM) technologies such as Laser Powder Bed Fusion (LPBF) are characterized by layer wise construction, which enable advancements of component design, with associated potential gains in performance and efficiency. However, high magnitude residual stresses (RS) are often a product of the rapid thermal cycles typical of the layerwise process. Therefore, a deep understanding of the formation of RS, the influence of process parameters on their magnitude and the impact on mechanical performance is crucial for widespread application. The experimental characterisation of these RS is essential for safety related engineering application and supports the development of reliable numerical models. Diffraction-based methods for RS analysis using neutrons and high energy X-rays enable non-destructive spatially resolved characterisation of both surface and bulk residual stresses in complex components. This presentation will provide an overview of recent research by the BAM at large scale facilities for the characterization of residual stresses in LPBF metallic alloys as a function of process parameters. In addition, the challenges posed by the textured and hierarchical microstructures of LPBF materials on diffraction-based RS analysis in AM materials will be discussed. This will include the question of the d0 reference lattice spacing and the appropriate choice of the diffraction elastic constants (DECs) to calculate the level of RS in LPBF manufactured alloys.
Predicting nonlinear physical aging of glasses from equilibrium relaxation via the material time
(2022)
The noncrystalline glassy state of matter plays a role in virtually all fields of materials science and offers complementary properties to those of the crystalline counterpart. The caveat of the glassy state is that it is out of equilibrium and therefore exhibits physical aging, i.e., material properties change over time. For half a century, the physical aging of glasses has been known to be described well by the material-time concept, although the existence of a material time has never been directly validated. We do this here by successfully predicting the aging of the molecular glass 4-vinyl-1,3-dioxolan-2-one from its linear relaxation behavior. This establishes the defining property of the material time. Via the fluctuation-dissipation theorem, our results imply that physical aging can be predicted from thermal-equilibrium fluctuation data, which is confirmed by computer simulations of a binary liquid mixture.
To mitigate carbon dioxide emissions CO2 is compressed and sequestrated into deep geological layers (Carbon Capture and Storage CCS). The corrosion of injection pipe steels is induced when the metal is in contact with CO2 and at the same time the geological saline formation water. Stainless steels X35CrMo17 and X5CrNiCuNb16-4 with approximately 17% Cr show potential as injection pipes to engineer the Northern German Basin geological onshore CCS-site. Static laboratory experiments (T = 60 ◦C, p = 100 bar, 700–8000 h exposure time, aquifer water, CO2-flow rate of 9 L/h) were conducted to evaluate corrosion kinetics. The anomalous surface corrosion phenomena were found to be independent of heat treatment prior to exposure. The corrosion process is described as a function of the atmosphere and diffusion process of ionic species to explain the precipitation mechanism and better estimate the reliability of these particular steels in a downhole CCS environment.
In this paper, columnar cellular growth with kinetic effects including kinetic undercooling and solute trapping in rapid directional solidification of alloys was investigated by using a recent quantitative phase-field model for rapid solidification. Morphological transition and primary spacing selection with and without kinetic effects were numerically investigated. Numerical results show that doublon structure is an intermediate state in the primary spacing adjustment of cellular arrays. It was found that the inclusions of kinetic effects result in the increase of the solute in the solid phase and the solute enrichment in the interdendritic liquid channel. Moreover, predicted results indicate that the growth directions of the cellular arrays in rapid directional solidification with and without kinetic effects are independent of the Péclet number. Therefore, the kinetic effects play important roles in numerical simulations of the growth pattern selection and solute distribution during rapid solidification. Neglecting them will result in the inaccurately predicted results.
Detailed microstructural characterization of the AlMo0.5NbTa0.5TiZr refractory high entropy superalloy in the as-cast state is reported for first time and compared with the state annealed at 1400 oC for 24 h. The former shows a dendritic structure, with a mixture of A2/B2 phases < 20 nm in both the dendritic and interdendritic regions. A mostly amorphous phase, rich in Al and Zr, is found within the interdendritic region. The annealed state reproduced the combination of A2/B2/Al-Zr-rich phases reported previously. Calculations from two relevant ThermoCalc databases were compared with the experimental results. Equilibrium calculations were compared with results for the annealed alloy, whereas solidification paths calculated using Scheil-Gulliver model were used for comparison with the as-cast alloy. A previously hypothesized spinodal decomposition during cooling as the mechanism responsible for the patterned A2/B2 microstructure is confirmed via the CALPHAD calculations, pointing to its use as an efficient design tool for such alloys. Finally, the comparison between the experimental and computational findings allowed better understanding the solidification path and equilibrium stability of this alloy, giving a base to make better decisions on the field of new refractory superalloy design.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
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.
Optimizing the properties of next-generation high-temperature and corrosion-resistant alloys is rooted in balancing structure-property relationships and phase chemistry. Here, we implement a complementary approach based on transmission electron microscopy (TEM) and atom probe tomography (APT) to ascertain aspects of hierarchical phase separation behavior, by understanding the microstructural evolution and the three-dimensional (3D) nanochemistry of a single crystal Fe79.5Si15.5V5.0 (at%) alloy. A maze-like hierarchical microstructure forms, in which a complex network of metastable disordered α plates (A2 phase) emerges within ordered α1 precipitates (D03 phase). The supersaturation in α1 (D03) precipitates with Fe and V drives the formation of α (A2) plates. The morphology of α (A2) plates is discussed concerning crystal structure, lattice misfit, and elastic strain. Phase compositions and a ternary phase diagram aid the thermodynamic assessment of the hierarchical phase separation mechanism via the Gibbs energy of mixing. A perspective on the stabilization of hierarchical microstructures beyond Fe79.5Si15.5V5.0 is elaborated by comparing hierarchical alloys. We find that the ratio of elastic anisotropy (Zener ratio) serves as a predictor of the hierarchical particles’ morphology. We suggest that the strengthening effect of hierarchical microstructures can be harnessed by improving the temporal and thermal stability of hierarchical particles. This can be achieved through phase-targeted alloying aiming at the hierarchical particles phase by considering the constituents partitioning behavior. Beyond Fe79.5Si15.5V5.0, our results demonstrate a potential pathway for improving the properties of high-temperature structural materials.
A systematic study on a face‐centered cubic‐based compositionally complex alloy system Al–Co–Cr–Cu–Fe–Ni in its single‐phase state is carried out, where a mother senary compound Al₈Co₁₇Cr₁₇Cu₈Fe₁₇Ni₃₃ and five of its suballoys, obtained by removing one element at a time, are investigated and exhaustively analyzed determining the contribution of each alloying element in the solid solution. The senary and the quinaries are compared using experimental techniques including X‐ray absorption spectroscopy, X‐ray diffraction, transmission electron microscopy, and first principles hybrid Monte Carlo/molecular dynamics simulations. Chemical short‐range order and bond length distances have been determined both at the experimental and computational level. Electronic structure and local atomic distortions up to 5.2 Å have been correlated to the microhardness values. A linear regression model connecting hardness with local lattice distortions is presented.
Liquid-metal embrittlement (LME) of galvanized (Zn-coated) advanced high-strength steels is a long-known problem in materials science. Here we reveal the initial microstructural processes underneath the Zn-coating that lead to LME-microcrack initiation in the steel substrate. We track the microstructural evolution during the first tens of milliseconds and find pronounced signatures of Fe-Zn intermetallic precipitation in both ferrite grain boundaries and at internal ferrite-oxide phase boundaries. In concert with novel CALPHAD-integrated density-based thermodynamic modelling, we demonstrate that Zn-rich intermetallic phase-nucleation can occur at markedly low processing temperatures due to a segregation transition. We show that a small Znenrichment caused by Zn bulk-diffusion during the initial temperature rise in a joining process is sufficient to induce the segregation transition and subsequent nucleation of Fe-Zn intermetallic grain-boundary phases, which the experiments link to crack initiation sites. These findings direct focus onto LME-controlling microstructural and thermodynamic phenomena at temperatures below the ductility trough and the austenite formation temperature.
Density-based phase-field (DPF) methods have emerged as a technique for simulating grain boundary thermodynamics and kinetics. Compared to the classical phase-field, DPF gives a more physical description of the grain boundary structure and chemistry, bridging CALPHAD databases and atomistic simulations, with broad applications to grain boundary and segregation engineering. Notwithstanding their notable progress, further advancements are still warranted in DPF methods. Chief among these are the requirements to resolve its performance constraints associated with solving fourth-order partial differential equations (PDEs) and to enable the DPF methods for simulating moving grain boundaries. Presented in this work is a means by which the aforementioned problems are addressed by expressing the density field of a DPF simulation in terms of a traditional order parameter field. A generic DPF free energy functional is derived and used to carry out a series of equilibrium and dynamic simulations of grain boundaries in order to generate trends such as grain boundary width vs. gradient energy coefficient, grain boundary velocity vs. applied driving force, and spherical grain radius vs. time. These trends are compared with analytical solutions and the behavior of physical grain boundaries in order to ascertain the validity of the coupled DPF model. All tested quantities were found to agree with established theories of grain boundary behavior. In addition, the resulting simulations allow for DPF simulations to be carried out by existing phase-field solvers.
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.