5 Werkstofftechnik
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Organisationseinheit der BAM
- 5 Werkstofftechnik (628)
- 5.1 Mikrostruktur Design und Degradation (174)
- 5.2 Metallische Hochtemperaturwerkstoffe (162)
- 5.4 Multimateriale Fertigungsprozesse (121)
- 5.6 Glas (90)
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- 5.5 Materialmodellierung (61)
- 8 Zerstörungsfreie Prüfung (55)
- 7 Bauwerkssicherheit (52)
- 9 Komponentensicherheit (47)
- 8.5 Röntgenbildgebung (42)
- 6 Materialchemie (40)
- 5.0 Abteilungsleitung und andere (34)
- 7.6 Korrosion und Korrosionsschutz (33)
- 9.4 Integrität von Schweißverbindungen (19)
- 6.3 Strukturanalytik (18)
- 6.1 Oberflächen- und Dünnschichtanalyse (16)
- 9.6 Additive Fertigung metallischer Komponenten (16)
- 1 Analytische Chemie; Referenzmaterialien (14)
- 3 Gefahrgutumschließungen; Energiespeicher (12)
- 4 Material und Umwelt (12)
- 7.5 Technische Eigenschaften von Polymerwerkstoffen (11)
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- 9.3 Schweißtechnische Fertigungsverfahren (7)
- 1.2 Biophotonik (6)
- 3.1 Sicherheit von Gefahrgutverpackungen und Batterien (6)
- 4.2 Material-Mikrobiom Wechselwirkungen (6)
- 6.5 Synthese und Streuverfahren nanostrukturierter Materialien (5)
- 8.0 Abteilungsleitung und andere (5)
- 1.6 Anorganische Referenzmaterialien (4)
- 4.1 Biologische Materialschädigung und Referenzorganismen (4)
- 6.0 Abteilungsleitung und andere (4)
- 6.6 Physik und chemische Analytik der Polymere (4)
- 7.4 Baustofftechnologie (4)
- 8.3 Thermografische Verfahren (4)
- 8.4 Akustische und elektromagnetische Verfahren (4)
- 9.2 Versuchsanlagen und Prüftechnik (4)
- 6.4 Materialinformatik (3)
- 8.6 Faseroptische Sensorik (3)
- 1.4 Prozessanalytik (2)
- 2 Prozess- und Anlagensicherheit (2)
- 2.1 Sicherheit von Energieträgern (2)
- 3.0 Abteilungsleitung und andere (2)
- 3.4 Sicherheit von Lagerbehältern (2)
- 3.5 Sicherheit von Gasspeichern (2)
- 4.3 Schadstofftransfer und Umwelttechnologien (2)
- 4.4 Thermochemische Reststoffbehandlung und Wertstoffrückgewinnung (2)
- 6.7 Materialsynthese und Design (2)
- 7.0 Abteilungsleitung und andere (2)
- 7.7 Modellierung und Simulation (2)
- 8.1 Sensorik, mess- und prüftechnische Verfahren (2)
- 1.0 Abteilungsleitung und andere (1)
- 1.8 Umweltanalytik (1)
- 1.9 Chemische und optische Sensorik (1)
- 3.6 Elektrochemische Energiematerialien (1)
- 6.2 Material- und Oberflächentechnologien (1)
- 9.5 Tribologie und Verschleißschutz (1)
- VP Vizepräsident (1)
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Although the slow crack growth in glass is dominated by stress-corrosion phenomena, it also should reflect the underlaying intrinsic fracture behavior controlled by glass chemistry and structure. To investigate such underlaying phenomena, crack growth velocity in alkali silicate glasses was measured in vacuum across 10 orders of magnitude with double cantilever beam technique. Measured and literature crack growth data were compared with calculated intrinsic fracture toughness data obtained from Young’s moduli and theoretical fracture surface energy. Data analysis reveals slight correlation with the packing density and significant deviations from the intrinsic brittle fracture behavior. These deviations do not follow simple compositional trends. Two opposing processes may explain this finding: a decrease in the apparent fracture surface energy due to stress-induced chemical changes at the crack tip and its increase due to energy dissipation during fracture.
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).
3D-printed landing pads on the moon: Paving the road for large area sintering of lunar regolith.
A prerequisite for lunar exploration and beyond is the manufacturing of objects directly on the moon, given the extreme costs involved in the shipping of material from Earth. Looking at processes, raw materials, and energy sources, equipment will certainly have to be brought from Earth at the beginning. Available on the moon are lunar regolith as raw material and the sun as an energy source. One of the first steps towards the establishment of a lunar base is the creation of infrastructure elements, such as roads and landing pads.
We’ll introduce you to the ESA-project PAVER that demonstrates the sintering and melting of lunar regolith simulant material to produce large scale 3D printed elements that could be used during human and robotic lunar explorations.
Additive manufacturing methods such as laser powder bed fusion (LPBF) allow geometrically complex parts to be manufactured within a single step. However, as an aftereffect of the localized heat input, the rapid cooling rates are the origin of the large residual stress (RS) retained in as-manufactured parts. With a view on the microstructure, the rapid directional cooling leads to a cellular solidification mode which is accompanied by columnar grown grains possessing crystallographic texture. The solidification conditions can be controlled by the processing parameters and the scanning strategy. Thus, the process allows one to tailor the microstructure and the texture to the specific needs. Yet, such microstructures are not only the origin of the mechanical anisotropy but also pose metrological challenges for the diffraction-based RS determination. In that context the micromechanical elastic anisotropy plays an important role: it translates the measured microscopic strain to macroscopic stress. Therefore, it is of uttermost importance to understand the influence of the hierarchical microstructures and the texture on the elastic anisotropy of LPBF manufactured materials.
This study reveals the influence of the build orientation and the texture on the micro-mechanical anisotropy of as-built Inconel 718. Through variations of the build orientation and the scanning strategy, we manufactured specimens possessing [001]/[011]-, [001]-, and [011]/[111]-type textures. The resulting microstructures lead to differences in the macroscopic mechanical properties. Even further, tensile in-situ loading experiments during neutron diffraction measurements along the different texture components revealed differences in the microstrain response of multiple crystal lattice planes. In particular, the load partitioning and the residual strain accumulation among the [011]/[111] textured specimen displayed distinct differences measured up to a macroscopic strain of 10 %. However, the behavior of the specimens possessing [001]/[011]-and [001]-type texture was only minorly affected. The consequences on the metrology of RS analysis by diffraction-based methods are discussed.
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.
Die technischen Möglichkeiten der robotischen Glasschmelzanlage der BAM werden vorgestellt.
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.
The homogeneous introduction of organic additives is a prerequisite for good processability of ceramic powders during dry pressing. The addition of organic additives by wet route via ceramic slurries offers advantages over dry processing. The organic content can be reduced and a more homogeneous distribution of the additives on the particle surface is achieved. In addition to the measurements of zeta potential and viscosity, sedimentation analysis by optical centrifugation was also tested and successfully used to characterize the ceramic slurries and accurately evaluate of the suitability of different types, amounts, and compositions of organic additives.
Spray drying of well-stabilized slurries usually results in mostly hollow granules with a hard shell leading to sintered bodies with defects and reduced strength and density. By purposefully degrading the slurry stability after dispersion of the ceramic powder, the drying behavior of the granules in the spray drying process and thus the granule properties can be influenced. Destabilization of the slurry and thus partial flocculation was quantified by optical centrifugation. Spray drying of the destabilized alumina slurries resulted in "non-hollow" granules without the detrimental hard shell and thus improved granule properties.
Further improvement of the granules was achieved by installing ultrasonic atomization in the spray dryer. A narrower granule size distribution was achieved, which had a positive effect on, among other things, the flowability of the granules.
Specimens produced from this granules had fewer defects of smaller size, leading to better results for the density and strength of the sintered bodies. The observations made for alumina could be transferred to zirconia and as well to ZTA with 20 wt% zirconia.
A large amount of publicly available data is reproduced every day in the field of materials science, while these kind of material data can have different formats and types like paper-type publications, standards, datasheets or isolated datasets in repositories. However, gathering a specific library from such extensive and diverse material data is always challenging for the materials scientists and engineers, since the time-related limitations are not allowed to fully access the large publicly available databases; search across these disparate databases, manage the large volumes of heterogeneous datasets, and integrate data from multiple sources. To address these challenges and make data findable, accessible, interoperable, and reusable (FAIR), an efficient data management system is necessary to build comprehensive, documented, and connected data spaces in the future. A formal standardized knowledge representation through an ontology can address such problems and make data more available and interoperable between related domains. Ontology can also rich machine processable semantic descriptions that increases the performance of scientific searches. In this regard, the Platform MaterialDigital (PMD) is currently working on developing a high-level ontology for the materials and material related processes. For example, in one of the PMD projects of “KupferDigital”, we will try to develop a data ecosystem for digital materials research based on ontology-based digital representations of copper and copper alloys. As a case study, this paper describes the methodology for ontology development of Brinell hardness, based on PMD core ontology. The methodology we describe includes the following steps; gathering the required domain terminology from different resources like standards (DIN EN ISO 6506-1) and test reports, representing the performance of a standard-conformant hardness test and the treatment of the recorded values up to a “reportable” hardness value for a material, designing the process chain according to the semantic technologies, and developing a domain-level ontology of Brinell hardness based on PMD ontology semantic formalization. Apart the mentioned methodology, some interesting tools and methods were introduced and ontology design challenges and possible solutions for modelling materials and processes were discussed. Furthermore, a dataset from the Brinell hardness measurement of cast copper samples is prepared for testing the query process.
Up to now, oriented surface crystallization phenomena are discussed controversially, and related studies are restricted to few glasses. For silicate glasses we found a good correlation between the calculated surface energy of crystal faces and oriented surface nucleation. Surface energies were estimated assuming that crystal surfaces resemble minimum energy crack paths along the given crystal plane. This concept was successfully applied by Rouxel in calculating fracture surface energies of glasses. Several oriented nucleation phenomena can be herby explained assuming that high energy crystal surfaces tend to be wetted by the melt. This would minimize the total interfacial energy of the nucleus. Furthermore, we will discuss the evolution of the microstructure and its effect on the preferred crystal orientation.
Up to now, oriented surface crystallization phenomena are discussed controversially, and related studies are restricted to few glasses. For silicate glasses we found a good correlation between the calculated surface energy of crystal faces and oriented surface nucleation. Surface energies were estimated assuming that crystal surfaces resemble minimum energy crack paths along the given crystal plane. This concept was successfully applied by Rouxel in calculating fracture surface energies of glasses. Several oriented nucleation phenomena can be herby explained assuming that high energy crystal surfaces tend to be wetted by the melt. This would minimize the total interfacial energy of the nucleus. Furthermore, we will discuss the evolution of the microstructure and its effect on the preferred crystal orientation.
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.
The dataset contains experimental mechanical data from complex service-like creep-fatigue experiments performed isothermally at 620 °C and a low strain amplitude of 0.2 % on tempered martensite-ferritic grade P92 steel. The data sets in text file format provide cyclic deformation (min. and max. stresses) and the total (hysteresis) data of all recorded fatigue cycles for three different creep-fatigue experiments: 1) a standard relaxation fatigue (RF) test with symmetrical dwell times of three minutes introduced at minimum and maximum strain, 2) a fully strain-controlled service-like relaxation (SLR) test combining these three-minute peak strain dwells with a 30-minute dwell in between at zero strain, and 3) a partly stress-controlled service-like creep (SLC) test combining the three-minute peak strain dwells with 30-minute dwells at constant stress.
Further information on data and data acquisition, analysis, and experimental details are given in “Experimental Data from Service-Like Creep-Fatigue Experiments on Grade P92 Steel”, submitted to Data in Brief. Additional analyses of these datasets, as well as experimental findings and discussions are presented in “Creep-Fatigue of P92 in Service-Like Tests with Combined Stress- and Strain-Controlled Dwell Times”, submitted to International Journal of Fatigue.
Due to the increasing scarcity of critical raw materials current high-temperature materials are sought to be replaced by alloys based on more abundant metals. One possibility within the class of intermetallics are iron aluminides, which combine sustainability and cost-efficiency with the prospect of mass savings. Iron aluminides show competitive specific strength up to 700 °C and excellent creep and wet corrosion resistance by small additions of Mo, Ti and B. Nevertheless, a Mo content of above 2 at.% which is needed for optimum corrosion resistance results in enhanced brittleness, especially at room temperature. This is why alloys with these Mo fractions were only mechanically tested under compressive loading so far. Still, testing of static and creep properties under tensile loading is required for reliable component design. Besides high standards for crack-free processing, data acquisition for tensile loads is especially complicated by environmental embrittling effects for iron aluminides. To cope with these challenges, the AiF research project “WAFEAL – Materials applications for iron aluminides” was initiated. The main goal is to collect standardised data on ambient and high-temperature tensile properties and creep properties. Samples with a nominal composition of Fe-26Al-4Mo-0.5Ti-1B [at.%] were manufactured via centrifugal casting in ceramic shell moulds followed by machining. Heat treatment for homogenisation and final polishing were carried out where appropriate. A summary of the achieved tensile and creep properties such as yield and tensile strength, maximum elongation, secondary creep rate and stress exponents will be given. Results will be also discussed regarding the influence of temperature, stress level and microstructure on the damage mechanisms. Furthermore, the effect of different alloy concentrations on the mechanical response at different temperatures will be outlined within a small experimental series.
The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience. In the IGF project "iFrakto", software is being developed that quantitatively determines fracture characteristics and fracture mechanisms utilizing digitized expert knowledge, machine learning, and standard 2D and topographical data from SEM imaging. Topographical data are obtained from 4QBSE detector using shape-from-shading technology. In the medium term, a software tool should provide knowledge-based suggestions for the evaluation of fracture surfaces in real time during SEM work or at subsequent evaluation. As a basis for this, round robins were carried out among fractographers in order to create a knowledge base, to query the practice-relevant requirements for such tools and to carry out first practical tests. Actual results are presented and the relevance of the evaluation strategy is evaluated.
The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience.
Machine learning methods enables the quantitative determination of fracture characteristics and fracture mechanisms utilizing digitized expert knowledge [1]. Although the application of SE images provides promising results, additional information is required to obtain reliable solutions. As expected, BSE and 3D information helps to improve the classification (Fig. 1). But only a fast, widely integrated, and automated topography measurement can provide the required amount of referenced surface data for the application of machine learning methods.
To fulfil these requirements, topographical data are obtained from a BSE detector with four symmetric segments (4Q-BSE) using shape-from-shading technology [2]. Surface height calculation is performed live during image acquisition and provides immediate feedback in three dimensions. All available signals (SE, BSE and more if applicable) are recorded simultaneously together with the surface topography and stored in a multichannel data file. This guaranties the same geometrical reference for all data, which is required for further analysis (Fig. 2).
When applying machine learning methods to topographic data together with SEM images, topographic information must be provided as depth image. Consequently, a unique height scale is required for all applied data with different magnifications. This requires a calibrated height measurement, which is ensured with the integrated 3D calibration of the topographic acquisition and a dedicated calibration sample. Thus, a large number of data sets from different fracture samples was generated and used as training data for machine learning.
Substitution of lead oxide in low-melting glasses, e.g., for application in silver metallization pastes, is a current research goal. This work is focused on the investigation of silver diffusion in alkali zinc borate glasses (X2O-ZnO-B2O3, X = Li, Na, K, Rb). In addition, the redox state of silver (Ag) and thus the type of diffusing silver species were studied. For this purpose, a metallic silver coating was applied on glass cubes by means of sputtering. Heat treatment of the samples was performed close to the glass transition temperatures at 470 °C for 2 h under air and nitrogen atmosphere. Coating thickness was 1.8 µm after heat treatment, measured by a white light interferometer.
Silver diffusion profiles were measured by means of secondary neutral mass spectrometry. The silver diffusion coefficients are in the range of ~10-14 cm2/s and indicate no significant differences depending on the type of alkali ions in the glass. Dissolved Ag+-ions and [Agm]n+-clusters in the glasses were differentiated using fluorescence spectroscopy.
Precipitated metallic silver particles in the sodium containing glass were observed by means of transmission electron microcopy. Their mean particle diameter was ~6 nm.
Towards Interoperability: Digital Representation of a Material Specific Characterization Method
(2022)
Certain metallic materials gain better mechanical properties through controlled heat treatments. For example, in age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which represent obstacles to dislocation movement. Precise tuning of the material structure is critical for optimal mechanical behavior in the application. Therefore, analysis of the microstructure and especially the precipitates is essential to determine the ideal parameters for the interplay of material and heat treatment. Transmission electron microscopy (TEM) is utilized to identify precipitate types and orientations in a first step. Dark-field imaging (DF-TEM) is often used to image the precipitates and to quantify their relevant dimensions.
The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, an automatable, digital approach is demonstrated. Based on DF-TEM images of different precipitation states of a wrought aluminum alloy, a modularizable digital workflow for quantitative precipitation analysis is presented. The integration of this workflow into a data pipeline concept will also be discussed. Thus, by using ontologies, the raw image data, their respective contextual information, and the resulting output data from the quantitative precipitation analysis can be linked in a triplestore. Publishing the digital workflow and the ontologies will ensure the reproducibility of the data. In addition, the semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability.
The presented work is part of two digitization initiatives, the Platform MaterialDigital (PMD, materialdigital.de) and Materials-open-Laboratory (Mat-o-Lab).
Ontologies that represent a map of the concepts and relationships between them, are becoming an effective solution for data standardization and integration of different resources in the field of materials science, as efficient data storage and management is the building block of material digitization. However, building a domain ontology is not a simple task. It requires not only a collaborative effort between ontologists and domain experts, but also the modeling approaches and tools play a key role in the process. Among all approaches, graphical representation of domain ontologies based on standard conceptual modeling languages is widely used because of its intuitiveness and simplicity. Various tools have been developed to realize this approach in an intuitive way, such as Protégé plugins and web visualization tools.
The Materials-open-Lab (MatOLab) project, which aims to develop ontologies and workflows in accordance with testing standards for the materials science and engineering domains, adopted a UML (Unified Modeling Language) approach based on the diagrams.net. It is a powerful, popular, open-source graphical editor. In practical case studies, however, many users’ needs could not be met, such as reusing ontology, conversion, and data mapping. Users must switch between different tools to achieve a certain step, and thereby invariably increase learning cost. The lack of validation also leads to incorrect diagrams and results for users who are not familiar with the ontology rules. To address these issues, we designed Ontopanel, a diagrams.net-based plugin that includes a set of pipeline tools for semantic modeling: importing and displaying protégé-like ontologies, converting diagrams to OWL, validating diagrams by OWL rules, and mapping data. It uses diagrams.net as the front-end for method modeling and Django as the back-end for data processing. As a web-based tool, it is very easy to expand its functionality to meet changing practical needs.
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.