5 Werkstofftechnik
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Paper des Monats
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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.
Hierarchical microstructures are created when additional γ particles form in γ’ precipitates and they are linked to improved strength and creep properties in high-temperature alloys. Here, we follow the formation and evolution of a hierarchical microstructure in Ni86.1Al8.5Ti5.4 by in situ synchrotron X-ray diffraction at 1023 K up to 48 h to derive the lattice parameters of the γ matrix, γ’ precipitates and γ particles and misfits between phases. Finite element method-based computer simulations of hierarchical microstructures allow obtaining each phase's lattice parameter, thereby aiding peak identification in the in situ X-ray diffraction data. The simulations further give insight into the heterogeneous strain distribution between γ’ precipitates and γ particles, which gives rise to an anisotropic diffusion potential that drives the directional growth of γ particles. We rationalize a schematic model for the growth of γ particles, based on the Gibbs-Thomson effect of capillary and strain-induced anisotropic diffusion potentials. Our results highlight the importance of elastic properties, elastic anisotropy, lattice parameters, and diffusion potentials in controlling the behavior and stability of hierarchical microstructures.
A global transition towards more sustainable, affordable and reliable energy systems is being stimulated by the Paris Agreement and the United Nation's 2030 Agenda for Sustainable Development. This poses a challenge for the corrosion industry, as building climate‐resilient energy systems and infrastructures brings with it a long‐term direction, so as a result the long‐term behaviour of structural materials (mainly metals and alloys) becomes a major prospect. With this in mind “Corrosion Challenges Towards a Sustainable Society” presents a series of cases showing the importance of corrosion protection of metals and alloys in the development of energy production to further understand the science of corrosion, and bring the need for research and the consequences of corrosion into public and political focus. This includes emphasis on the limitation of greenhouse gas emissions, on the lifetime of infrastructures, implants, cultural heritage artefacts, and a variety of other topics.
Understanding the origins of intrinsic stress in Si nanowires (NWs) is crucial for their successful utilization as transducer building blocks in next-generation, miniaturized sensors based on anoelectromechanical systems (NEMS). With their small size leading to ultrahigh-resonance frequencies and extreme surface-to-volume ratios, silicon NWs raise new opportunities regarding sensitivity, precision, and speed in both physical and biochemical sensing. With silicon optoelectromechanical properties strongly dependent on the level of NW intrinsic stress, various studies have been devoted to the measurement of such stresses generated, for example, as a result of harsh fabrication processes. However, due to enormous NW surface area, even the native oxide that is conventionally considered as a benign surface condition can cause significant stresses. To address this issue, a combination of nanomechanical characterization and atomistic simulation approaches is developed. Relying only on low-temperature processes, the fabrication approach yields monolithic NWs with optimum boundary conditions, where NWs and support architecture are etched within the same silicon crystal. Resulting NWs are characterized by transmission electron microscopy and micro-Raman spectroscopy. The interpretation of results is carried out through molecular dynamics simulations with ReaxFF potential facilitating the incorporation of humidity and temperature, thereby providing a close replica of the actual oxidation environment - in contrast to previous dry oxidation or self-limiting thermal oxidation studies. As a result, consensus on significant intrinsic tensile stresses on the order of 100 MPa to 1 GPa was achieved as a function of NW critical dimension and aspect ratio. The understanding developed herein regarding the role of native oxide played in the generation of NW intrinsic stresses is important for the design and development of silicon-based NEMS.
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
Investigation of degradation of the aluminum current collector in lithium-ion batteries by GD-OES
(2022)
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
Characterization of Ti-6Al-4V fabricated by multilayer laser powder-based directed energy deposition
(2022)
Laser powder-based directed energy deposition (DED-L) is increasingly being used in additive manufacturing (AM). As AM technology, DED-L must consider specific challenges. It must achieve uniform volume growth over hundreds of layers and avoid heat buildup of the deposited material. Herein, Ti–6Al–4V is fabricated using an approach that addresses these challenges and is relevant in terms of transferability to DED–L applications in AM. The assessment of the obtained properties and the discussion of their relationship to the process conditions and resulting microstructure are presented. The quality of the manufacturing process is proven in terms of the reproducibility of properties between individual blanks and with respect to the building height. The characterization demonstrates that excellent mechanical properties are achieved at room temperature and at 400 °C.
The elastic energy of mixing for multi-component solid solutions is derived by generalizing Eshelby's sphere-in-hole model. By surveying the dependence of the elastic energy on the chemical composition and lattice misfit, we derive a lattice strain coefficient λ*. Studying several high-entropy alloys and superalloys, we propose that most solid solution multi-component alloys are stable when λ*<0.16, generalizing the Hume-Rothery atomic-size rule for binary alloys. We also reveal that the polydispersity index δ, frequently used for describing strain in multi-component alloys, directly represents the elastic energy e with e=qδ², q being an elastic constant. Furthermore, the effects of (i) the number and (ii) the atomic-size distribution of constituting elements on the phase stability of high-entropy alloys were quantified. The present derivations and discussions open for richer considerations of elastic effects in high-entropy alloys, offering immediate support for quantitative assessments of their thermodynamic properties and studying related strengthening mechanisms.
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.
Grain boundaries (GBs)’s role in determining the functional and mechanical properties of polycrystalline materials is inscribed in both their structure and chemistry. Upon solute segregation, the structure and composition of a GB can change concurrently. We study the co-evolution of GB’s structure and segregation by enhancing the density-based phase-field model to account for the in-plane structural variations in the GB. Significant mutual coupling is revealed between the GB’s chemical and structural states during Mn segregation in Fe-Mn alloys. We found that the structural degrees of freedom in a GB (the ability of the GB structure to respond to the chemical variation) amplifies Mn segregation transition, even when the GB structure stays unchanged. When the GB structure is not uniform, that is the usual case, the coupling between GB structure and segregation evolution also enables the spinodally formed low- and high-Mn phases (upon segregation transition) to co-exist within the GB region. These findings explain the stabilizing mechanism of pronounced interfacial segregation fluctuations, experimentally evidenced in Fe-Mn GBs, and give new insights on the structural sensitivity of GBs’ segregation phenomena and the mutual chemo-structural interplay.
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.
Engineering grain boundaries demands a quantitative description of both their segregation and specific phase behavior. Recently I have proposed a density-based model for grain boundary thermodynamics that enables CALPHAD integrated derivation of grain boundary phase diagrams, broadly applied now in studying various alloys. Combining this model with experimental investigations, in this talk, new aspects of interfacial segregation and phase transformation revealed in polycrystalline alloys are discussed. The effect of elastic interaction on grain boundary phase behavior is incorporated. We consider Al alloys and novel high-entropy alloys and discuss a general strategy for grain boundary engineering.
Mit der Digitalisierung von Materialien und Prozessen ist ein Paradigmenwechsel in der Materialentwicklung, -gestaltung und -optimierung verbunden, welcher gleichermaßen vielseitige Möglichkeiten eröffnet und eine große Herausforderung darstellt. Insbesondere sind bei den Digitalisierungsbestrebungen die Qualitätssicherung von Prozessen und Ausgabedaten sowie die Interoperabilität zwischen Anwendungen nach FAIR-Prinzipien (Findability, Accessibility, Interoperability, Reusability) sicherzustellen. Dies umfasst die Speicherung, Verarbeitung und Abfrage von Daten in möglichst standardisierter Form, wobei entsprechend auch Normungs- und Standardisierungsgremien beteiligt werden müssen. Um der Herausforderung gerecht zu werden, Materialdaten für alle Beteiligten konsistent zu kontextualisieren, müssen alle notwendigen Informationen zum Zustand des Materials inklusive produktions- und anwendungsbedingter Veränderungen über eine einheitliche, maschinenlesbare Beschreibung verfügbar gemacht werden. Hierfür sollen Ontologien genutzt werden, da sie maschinenverständliche und -interpretierbare Wissensrepräsentationen durch semantische Konzeptualisierungen ermöglichen, die für das Datenmanagement und die Digitalisierung im Bereich der Materialwissenschaften benötigt werden.
Dieses hochaktuelle Thema der Integration und Wiederverwendung von Wissen und Daten aus Herstellung, Bearbeitung und Charakterisierung von Materialien wird in den Projekten Innovationsplattform MaterialDigital (PMD, materialdigital.de) und Materials-open-Lab (Mat-o-Lab, matolab.org) adressiert. Diese beiden unter der Beteiligung der Bundeanstalt für Materialforschung und -prüfung (BAM) durchgeführten Projekte wurden auf der 39. Vortrags- und Diskussionstagung „Werkstoffprüfung“ (2021) grundlegend vorgestellt. In dieser Präsentation sollen die Weiterentwicklungen hinsichtlich der Speicherung von Zugversuchsdaten gemäß einer normenkonformen ontologischen Repräsentation vorgestellt werden. Das umfasst den Weg von der Entwicklung einer Ontologie nach Norm, der Konvertierung von Daten aus Standardtests in das interoperable RDF-Format bis hin zur Verknüpfung von Ontologie und Daten. Letztendlich können die entsprechenden Daten in einem Triple Store abgelegt und abgefragt werden.
Die übliche Standardisierung von mechanischen Prüfverfahren im Bereich der Materialwissenschaft und Werkstofftechnik dient als solide Grundlage für die Ontologieentwicklung. Daher wurde der Zugversuch von Metallen bei Raumtemperatur nach DIN EN ISO Norm 6892-1:2019-11 als einer der ersten Anwendungsfälle in den genannten Projekten ausgewählt. Die Betrachtung und Beschreibung des Zugversuchs beinhaltet sowohl dessen ontologische Darstellung als auch eine exemplarische Datengenerierung. Die semantische Verbindung von Ontologie und Daten führt zu Interoperabilität und einer verbesserten Abfragefähigkeit.
Following the new paradigm of materials development, design and optimization, the digitalization of materials and processes is the main goal which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR (findability, accessibility, interoperability, reusability) principles are to be ensured. This includes storage, processing and querying of data in a preferably standardized form, also addressing the incorporation of standardization bodies. To meet the challenge to contextualize material data in a way that is consistent with all stakeholders, all necessary information on the condition of the material including production and application-related changes have to be made available via a uniform, machine-readable description. For this purpose, ontologies are to be used since they allow for machine-understandable knowledge representations and semantic conceptualizations that are needed for data management and the digitalization in the field of materials science.
With respect to this currently ever-growing topic of integration and reuse of data and knowledge from synthesis, production and characterization of materials, this presentation shows the efforts taken within the project Platform MaterialDigital (PMD, materialdigital.de) to store tensile test data in accordance with a standard-compliant ontological representation. The includes the path from developing an ontology in accordance with the respective standard, converting ordinary and arbitrarily selected data gained from standard tests into the interoperable RDF format, up to connecting the ontology and data, respectively. Finally, such data can be queried from a triple store.
In the field of material science and engineering (MSE), most mechanical test methods are standardized which serves as a valid basis for ontology development. Therefore, the well-known tensile test of metals at room temperature (DIN EN ISO standard 6892-1:2019-11) was selected to be considered as one of the first use cases in PMD. This consideration within the PMD features both, the ontological representation of such a tensile test in accordance with the standard as well as exemplary data generation. The semantic connection of the ontology and data leads to interoperability and an enhanced ability of querying.
Turbine blades often contain cylindric holes used to generate an air film that protects the blade alloy from the hot gases. These cooling holes of diameter around one mm are drilled by laser through the thickness of the blades. Unfortunately, the resulting stress concentration and the drilling-induced damage are known to favor crack initiation from the holes. It is thus necessary to assess the impact of these cooling holes on the structural integrity of the blades. Since cracks initiate very readily, the fatigue life of the components is mainly controlled by the propagation of the cracks in the stress gradient induced by the holes.
For this purpose, displacement controlled high-temperature LCF (Low-Cycle-Fatigue) tests were performed with center hole specimens of a coarse-grained Nickel base Superalloy. The tests were stopped after a defined load drop. In addition, crack propagation tests with Double Edge Notch specimens were performed. Moreover, specimens with different hole surface finishes were investigated, which showed a detrimental effect of the hole surface roughness. In parallel, an evaluation of the LCF tests based on a fracture mechanics-based model (Madia et al., Eng. Fract. Mech., 2018) has been applied. Thereby, the specimen life is controlled by the crack propagation time until failure. Crack growth is controlled by a modified NASGRO equation accounting for large-scale yielding and a progressive build-up of crack closure. The initial crack size has been derived from the measurements of defects around the borehole. A reasonable agreement between predicted and measured lifetimes is observed if one keeps in mind the large uncertainty regarding the effective shape of the cracks.
The scatter of fatigue crack growth data can become significant for coarse grained materials. By using a probabilistic description of crack propagation as the foundation of a lifetime prediction model, lifetime scatter of laboratory specimens can be reproduced. However, the lifetime of real components is subjected to additional scattering factors such as surface condition or uncertainty regarding direction and shape of emerging cracks. These factors need to be addressed in order to exploit the advantages of probabilistic description, i.e. the reduction of unnecessary conservatisms.
High temperature LCF (Low-Cycle-Fatigue) tests were performed with center hole specimens of a coarse-grained Nickel base Superalloy. In addition, crack propagation tests with Double Edge Notch specimens were performed. A procedure to detect the shape of the starting crack that combines the potential drop method and induction thermography was developed. The geometry and the number of notches were varied. Moreover, specimen with different hole surface finishes were investigated, which showed a detrimental effect of the roughness of the hole surface.
The results have been compared to predictions of a probabilistic tool for the estimation of lcf lifetime that has been calibrated beforehand on laboratory specimens with and without notches. In parallel, a fracture mechanics-based lifetime model was developed, which includes the initial crack size as a critical parameter. Thereby, the influence of the large grain size (>1mm), and the shape of the starting crack at the notch were considered.
Acknowledgements
The investigations are conducted as part of the joint research program COOREFLEX-Turbo in the frame of AG Turbo. The work is supported by Siemens AG and the Bundesministerium für Wirtschaft und Technologie (BMWi) as per resolution of the German Federal Parliament under grant number 03ET7071E.
The dataset provided in this repository comprises data obtained from a series of characterization tests performed to a sheet of typical S355 (material number: 1.0577) structural steel (designation of steel according to DIN EN 10025-2:2019). The tests include methods for the determination of mechanical properties such as, e.g., tensile test, Charpy test and sonic resonance test. This dataset is intended to be extended by the inclusion of data obtained from further test methods. Therefore, the entire dataset (concept DOI) comprises several parts (versions), each of which is addressed by a unique version DOI.
The data were generated in the frame of the digitization project Innovationplatform MaterialDigital (PMD) which, amongst other activities, aims to store data in a semantically and machine understandable way. Therefore, data structuring and data formats are focused in addition to aspects in the field of material science and engineering (MSE). Hence, this data is supposed to provide reference data as basis for experimental data inclusion, conversion and structuring (data management and processing) that leads to semantical expressivity as well as for MSE experts being generally interested in the material properties and knowledge.
Grain boundaries (GBs) are planar lattice defects that govern the properties of many types of polycrystalline materials. Hence, their structures have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the atomic length scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability to quantify chemical characteristics at near-atomic scale. Using APT data sets, we present here a machine-learning-based approach for the automated quantification of chemical features of GBs. We trained a convolutional neural network (CNN) using twenty thousand synthesized images of grain interiors, GBs, or triple junctions. Such a trained CNN automatically detects the locations of GBs from APT data. Those GBs are then subjected to compositional mapping and analysis, including revealing their in-plane chemical decoration patterns. We applied this approach to experimentally obtained APT data sets pertaining to three case studies, namely, Ni-P, Pt-Au, and Al-Zn-Mg-Cu alloys. In the first case, we extracted GB specific segregation features as a function of misorientation and coincidence site lattice character. Secondly, we revealed interfacial excesses and in-plane chemical features that could not have been found by standard compositional analyses. Lastly, we tracked the temporal evolution of chemical decoration from early-stage solute GB segregation in the dilute limit to interfacial phase separation, characterized by the evolution of complex composition patterns. This machine-learning-based approach provides quantitative, unbiased, and automated access to GB chemical analyses, serving as an enabling tool for new discoveries related to interface thermodynamics, kinetics, and the associated chemistry-structure-property relations.
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.