5 Werkstofftechnik
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Organisationseinheit der BAM
- 5 Werkstofftechnik (121)
- 5.1 Mikrostruktur Design und Degradation (36)
- 5.6 Glas (25)
- 5.2 Metallische Hochtemperaturwerkstoffe (22)
- 5.4 Multimateriale Fertigungsprozesse (22)
- 5.3 Polymere Verbundwerkstoffe (15)
- 6 Materialchemie (15)
- 8 Zerstörungsfreie Prüfung (14)
- 8.5 Röntgenbildgebung (10)
- 1 Analytische Chemie; Referenzmaterialien (9)
Es wird eine Studie zur Charakterisierung eines anisotropen Stahls vorgestellt, bei der Ultraschalluntersuchungen mit Mikrostrukturanalysen verbunden werden. Das Material weist hohe Festigkeit und Korrosionsbeständigkeit auf, zugleich ist mit anisotropen Eigenschaften die mechanischen und betrieblichen Eigenschaften beeinflussen zu rechnen. Vorläufige Ergebnisse lassen vermuten, dass weitere Untersuchungen notwendig sind, um die Fähigkeiten und Grenzen des Materials genau zu bestimmen. Es wird ein systematischer Ansatz mit Array- Prüfköpfen, Time-of-Flight Diffraction (TOFD) Technik und mikrostrukturellen Untersuchungen angewendet, um die Wechselwirkung zwischen Anisotropie und Mikrostruktur des Stahls zu analysieren. Ultraschallprüfungen mit der TOFD-Technik und in Tauchtechnik liefern Einblicke in das anisotrope Verhalten des Werkstoffes, einschließlich entsprechenden Kornorientierung, Dämpfung und Schallgeschwindigkeitsvariation. Diese Messungen führen in Verbindung mit mikrostrukturellen Analysen zu einem tieferen Verständnis des Materialverhaltens. Unser Hauptziel ist es, ein Framework zu erstellen, welches die Ultraschallantwort anisotroper Materialien mit ihren mikroskopischen Struktureigenschaften verbindet. Die vorgestellte Methodik ermöglicht eine zerstörungsfreie und zügige Bewertung der Materialintegrität, was besonders bei der Anwendung von Hochleistungsmaterialien relevant ist. Durch diesen integrativen Ansatz werden verschiedener Charakterisierungsmethoden kombiniert, um ein umfassenderes Materialverständnis zu erreichen.
Interaction of electromagnetic waves, such as electron beams or light, with conductive material can lead to localized surface plasmon resonances (LSPRs) where the incoming energy can be deposited in a collective excitation of electrons of the conduction band, which in turn can result in coherent localized plasmon oscillations. LSPR in metallic nanostructures, such as nanoparticles (NPs), which are sensitive to geometry, material composition and environment, are currently utilized in a wide range of applications, such as surface-enhanced Raman spectroscopy, plasmonic wave guides, improved solar cells, on-chip particle accelerators and nanoantennas. A host of studies that focus on plasmonic NPs ranging from single NPs with several shapes (cubic, spherical, tetrahedral) over 1D assemblies of NPs such as chains, to ordered 2D assemblies of NPs show an increase of the complexity regarding the hybridization behavior of LSPRs eventually lead to delocalized Surface Plasmons. Furthermore, Anderson predicted in 1977 the absence of diffusion or delocalization of waves in disordered systems, which has been discussed as the underlying mechanism for LSPRs localization in disordered metallic thin films and ultrathin 2D networks. Our aim is to further develop these studies on the surface plasmon localization in disordered structures by (1) developing a novel NPs assembly fabrication method that allows fabricating disordered assemblies of NPs of a wide range of NPs sizes, and (2) probing the LSPR with high-resolution electron energy-loss spectroscopy (EELS). Moreover, the dominant dipolar interaction between the NPs, also facilitates an efficient numerical modeling of these systems, which in comparison with the experiments allows for an in-depth study of the impact of various geometric parameters as well as retardation and life-time damping on the observed localization behavior.
To synthesize 2D disordered assemblies of gold NPs on a TEM transparent silicon oxide substrate, a new synthesis routine was developed. This procedure is based on sublimation and redeposition of a gold microparticle precursor induced by an electron beam in a scanning electron microscope (SEM) operated at 30 kV. To characterize the assembly of synthesized NPs in terms of size, shape and spreading over the substrate, TEM measurements were conducted subsequently. To study LSPRs experimentally, EELS in scanning transmission electron microscopy (STEM) mode was carried out. The numerical modelling of LSPRs was performed using a self-consistent dipole model.
The synthesized 2D disordered gold NPs assemblies exhibit a gradient in the NPs mean size, which ranges from 100 nm close to the precursor location down to 2 nm at a distance of more than 20 µm from the precursor location. Additionally, the interparticle distance between the gold NPs increases with increasing distance to the precursor location.
The experimental investigation as well as the numerical simulation of the LSPRs demonstrate a localization behavior that decreases toward larger energies, which is driven by the disorder of the NPs assembly (mainly the random particle distance). That localization behavior stays in contrast to what was found in ultrathin 2D gold networks showing increasing of localization towards higher LSPRs energies. By varying the geometric parameters of the NPs assembly in the simulation, we could identify the NPs thickness as the parameter, that determines the energy-dependence of the localization. Specifically, a critical thickness of approx. 10 nm separates the two localization regimes, which correlates to the energy of the dipole mode resonance crucially depending on the thickness of the NPs.
2D disordered assemblies of gold NPs of a wide range of NPs sizes and distances can be synthesized directly on thin substrates facilitating structural characterization and EELS measurements in a TEM. It could be shown that such assemblies exhibit LSPRs with a localization behavior that may be tuned by the NPs sizes (including thickness) and interparticle distances. The proposed synthesis of random NPs assemblies opens new avenues for fundamental studies on Anderson localization in disordered plasmonic structures as well as its applications such as surface-enhanced Raman spectroscopy where localization behavior must be tuned to specific wave lengths.
This study introduces an innovative method for efficiently determining the creep properties of high-temperature materials through high-throughput testing, employing digital image correlation [1,2]. The focus is on the AlCoCrFeNiTi alloy [3-5], synthesized by directional solidification, known for its exceptional strength and unique properties. Experimental investigations, including compression, and bending creep tests, were conducted at 750°C.
Capitalizing on the inhomogeneous stress and strain distribution within a cantilever subjected to bending, we leverage this characteristic to extract multiple creep curves from a single test. Stresses at key points were determined using existing analytical solutions [5,6]. Uniaxial tests spanning 300 to 500 MPa initial stress were complemented by bending tests designed to induce similar stress levels. A detailed comparison between bending and uniaxial creep is presented, including the results of verification studies on additional alloys.
This methodology not only expedites testing but also minimizes material usage, energy consumption, and manual labour. This research showcases a reliable and time-efficient approach to exploring the creep behavior of high-temperature materials. The technique is particularly advantageous for characterizing precious alloys with limited dimensions. Microstructural heterogeneity may exist in specimens tested under bending load, however, it can still be correlated to the mechanical properties with modern high-resolution characterization methods. Stress and resulting strain can be directly compared in a single specimen, ensuring uniform manufacturing, and heating history. This method eliminates the possible errors due to testing with different rigs, which could impair the accuracy of studies based on individual tests.
In times of digital data processing and sharing, a central challenge for the Materials Science and Engineering (MSE) community is the complete digital representation of materials, including their relevant processing and microstructure details and the resulting properties. This digital representation, supported by digital infrastructures, enables entirely new qualities of collaborative work and is central to how we will conduct MSE research and develop products in the future. The main challenges are the composition, shaping, and description of the data so that it can be easily interpreted, trusted, and re-used. This presentation introduces our current effort to develop a best practice framework for generating and distributing creep reference datasets for Ni-based superalloys, which builds on previous approaches. Researchers can use such datasets to compare their own experimental or simulation results, used, for instance, to perform simulation-based alloy design and optimization or in the verification of the own testing equipment. The concept includes building an easily accessible digital infrastructure to annotate and discover the datasets and the integration of an ontology that aligns with the necessary metadata schema. With the help of an ontology, the reference dataset for creep can be semantically described, thus enabling the digital representation and reusage of shared concepts from domain experts and the community. To achieve this, it is necessary to establish a defined vocabulary with corresponding relations and annotations. The interplay between a digital infrastructure, the agreement on the necessary metadata and related metadata schema, and an underlying ontology will ensure that data and results can be easily shared, taken up, and re-used, thus fulfilling the FAIR principles (Findable, Accessible, Interoperable, Reusable). Furthermore, we aim to develop a widely accepted definition of reference data and data quality levels and to reach a self-supported community process. We intend to motivate the discussion about reference material datasets, necessary metadata, and future collaborations within the creep community.
Non-equilibrium microstructure evolution in additive manufacturing (AM) is a major barrier for establishing a safe and sustainable application of AM in industrial processes. The constant heat source in the AM continuously affects the just-solidified grains beneath the melting pool, leading to directional grain growth (DGG). While real-time measurements of the non-equilibrium microstructure evolution is challenging, here developing a computational framework to systematically explore DGG becomes imperative.
We have advanced a comprehensive approach, integrating mean-field modeling and phase-field simulations, to elucidate the dynamics of DGG under an external driving force. Our simulations unveil a steady-state power-law grain growth kinetics during DGG, characterized by the interplay between curvature-driven dynamics at grain boundary junctions and directional driving forces.
Modern high-pressure H2 tanks consist of fiber-reinforced composite materials and a plastic lining on the inside. The use of glass would drastically increase the H2 barrier effect. This could be achieved with glass liners or fiber-reinforced polymer-bonded glass capillary storage tanks and would enable lower wall thicknesses, higher gravimetric storage densities and variable designs and thus a much more effective use of space.
However, the decisive material parameters for the development of these technologies, such as the hydrogen permeation, are unknown. This study focuses on H2 diffusion in glasses of different chemical compositions.
H2 permeation is measured by mass spectrometry. For this purpose, the mass spectrometer (MS), which is located in a high vacuum, is separated from the pressure side by the test specimen. Pure H2 gas is present on the pressure side, so that the mass flow is recorded qualitatively and quantitatively in the MS. The permeation coefficients are calculated from the sample geometry and the mass flow rates. The very low H2 permeation of glass is measured on bundles of thin-walled commercially available glass capillaries and compared with the hydrogen permeation data of the glass powder method.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
Following the new paradigm of materials development, design, and optimization, digitalization is the main goal in materials sciences and engineering (MSE) 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 principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web technologies (SWT) are used since they allow for machine-actionable and human-readable knowledge representations needed for data management, retrieval, and (re)use.
The project ‘platform MaterialDigital’ (PMD) aims to bring together and support interested parties from both industrial and academic sectors in a sustainable manner in solving digitalization tasks and implementing digital solutions. Therefore, the establishment of a virtual material data space and the systematization of the handling of hierarchical, process-dependent material data are focused. Core points to be dealt with are the development of agreements on data structures and interfaces implemented in distinct software tools and to offer users specific support in their projects. Furthermore, the platform contributes to a standardized description of data processing methods in materials research. In this respect, selected MSE methods are semantically represented on a prototypical basis which are supposed to serve as best practice examples with respect to knowledge representation and the creation of knowledge graphs used for material data.
Accordingly, this poster presentation illustrates demonstrators developed and deployed within the PMD project. Semantically anchored using the mid-level PMD Core Ontology (PMDco), they address data transformation leading to a novel data management which is based on semantic integrated data. The PMD data acquisition pipeline (DAP), which is fueled by traditional, diverse data formats, and a pipeline applying an electronic laboratory notebook (ELN) as data source are displayed. Additionally, the efficient combination of diverse datasets originating from different sources is demonstrated by the representation of a use case dealing with the well-known Orowan relation.
Electron Back Scatter Diffraction (EBSD) is a very versatile analytical technique allowing for the characterization of material structure. Historically, diffraction images (Kikuchi patterns) registered during EBSD analysis were solved using Hough/Radon transformation. The last decade brought several novel techniques of experimental pattern analysis, focusing entirely on image analysis routines such as pattern matching, or various variants of High-Resolution EBSD. However, all the above-mentioned techniques require prior knowledge of the material structure to perform orientation analysis. The recently presented algorithm employed in Crystallographic Analysis of Lattice Metric (CALM) software, effectively removes this limitation enabling a standard-less analytical approach in EBSD systems. At its core, the CALM technique couples accurate detection of the Kikuchi bands position, with a rigid construction of reciprocal lattice resulting from translational crystal symmetry. A unique characteristic of the methodology also gives an opportunity for application in the analysis of continuous lattice changes, for example tetragonality mapping. During mapping, however, the geometry of the gnomonic projection (represented by the projection center) is continuously altered decreasing overall algorithm efficiency. The work presents an analysis of the projection center in terms of precision and accuracy.
The characterization of really unknown phases typically uses 70 to 150 reflectors for lattice metric calculation. The determination of the lattice parameters follows with 4% accuracy. Including a Z correction up to 1% can be reached. The precision of the lattice parameters ratios (a:b:c) is, however, better than 0.1%.