5 Werkstofftechnik
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- 2024 (14) (entfernen)
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- Bioactive glass (2)
- Crystallization (2)
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- Additive Manufacturing (1)
- Aging (1)
- Atomistic Simulation (1)
- Austenitic alloys (1)
- Automated image analysis (1)
- CALPHAD (1)
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- 5 Werkstofftechnik (14) (entfernen)
In the past two decades, numerous relaxation or physical aging experiments of metallic glasses have revealed signatures of intermittent atomic-scale processes. Revealed via intensity cross-correlations from coherent scattering using X-ray photon correlation spectroscopy (XPCS), the observed abrupt changes in the time-domain of atomic motion does not fit the picture of gradual slowing down of relaxation times and their origin continues to remain unclear. Using a binary Lennard-Jones model glass subjected to microsecond-long isotherms, we show here that temporally and spatially heterogeneous atomic-cluster activity at different length-scales drive the emergence of highly non-monotonous intensity cross-correlations. The simulated XPCS experiments reveal a variety of time-dependent intensity-cross correlations that, depending on both the structural evolution and the 𝑞-space sampling, give detailed insights into the possible structural origins of intermittent aging measured with XPCS.
A density-based phase field model is developed where the free energy functional is explicitly linked with molecular dynamics and is referred to as the Molecular Phase Field Method (MoPF). MoPF simulations involve expressing interatomic potentials in terms of density to form a density based free energy functional. Inputs to this functional are taken from atomistics such that the phase field density profile matches the corresponding density profile from atomistic simulations. We analyze our results by comparing the MoPF calculated excess interfacial energies with excess interfacial energies calculated using molecular dynamics associated with several nickel grain boundaries. Additionally, a comparison is made between our results and the interfacial energies of a \Sigma7 boundary across a variety of FCC systems simulated using density functional theory. The MoPF method is able to successfully predict grain boundary free energy trends between grain boundary and material types offering an atomistically informed mesoscale formulation for studying grain boundary physics.
Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer–Emmet–Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
The digitalization of materials science and engineering (MSE) is currently leading to remarkable advancements in materials research, design, and optimization, fueled by computer‐driven simulations, artificial intelligence, and machine learning. While these developments promise to accelerate materials innovation, challenges in quality assurance, data interoperability, and data management have to be addressed. In response, the adoption of semantic web technologies has emerged as a powerful solution in MSE. Ontologies provide structured and machine‐actionable knowledge representations that enable data integration, harmonization, and improved research collaboration. This study focuses on the tensile test ontology (TTO), which semantically represents the mechanical tensile test method and is developed within the project Plattform MaterialDigital (PMD) in connection with the PMD Core Ontology. Based on ISO 6892‐1, the test standard‐compliant TTO offers a structured vocabulary for tensile test data, ensuring data interoperability, transparency, and reproducibility. By categorizing measurement data and metadata, it facilitates comprehensive data analysis, interpretation, and systematic search in databases. The path from developing an ontology in accordance with an associated test standard, converting selected tensile test data into the interoperable resource description framework format, up to connecting the ontology and data is presented. Such a semantic connection using a data mapping procedure leads to an enhanced ability of querying. The TTO provides a valuable resource for materials researchers and engineers, promoting data and metadata standardization and sharing. Its usage ensures the generation of finable, accessible, interoperable, and reusable data while maintaining both human and machine actionability.
A giant Zn segregation transition is revealed using CALPHAD-integrated density-based modeling of segregation into Fe grain boundaries (GBs). The results show that above a threshold of only a few atomic percent Zn in the alloy, a substantial amount of up to 60 at.% Zn can segregate to the GB. We found that the amount of segregation abruptly increases with decreasing temperature, while the Zn content in the alloy required for triggering the segregation transition decreases. Direct evidence of the Zn segregation transition is obtained using high-resolution scanning transmission electron microscopy. Base on the model, we trace the origin of the segregation transition back to the low cohesive energy of Zn and a miscibility gap in Fe-Zn GB, arising from the magnetic ordering effect, which is confirmed by ab-initio calculations. We also show that the massive Zn segregation resulting from the segregation transition greatly assists with liquid wetting and reduces the work of separation along the GB. The current predictions suggest that control over Zn segregation, by both alloy design and optimizing the galvanization and welding processes, may offer preventive strategies against liquid metal embrittlement.
AbstractThe high-temperature corrosion behaviors of the equimolar CrCoNi medium-entropy alloy and CrMnFeCoNi high-entropy alloy were studied in a gas atmosphere consisting of a volumetric mixture of 10% H2O, 2% O2, 0.5% SO2, and 87.5% Ar at 800 °C for up to 96 h. Both alloys were initially single-phase fcc with a mean grain size of ~ 50 μm and a homogeneous chemical composition. The oxide layer thickness of CrMnFeCoNi increased linearly with exposure time while it remained constant at ~ 1 μm for CrCoNi. A Cr2O3 layer and minor amounts of (Co,Ni)Cr2O4 developed on the latter while three oxide layers were detected on the former, i.e., a thin and continuous chromium rich oxide layer at the oxide/alloy interface, a dense (Mn,Cr)3O4 layer in the center and a thick and porous layer of Mn3O4 and MnSO4 at the gas/oxide interface. Additionally, a few metal sulfides were observed in the CrMnFeCoNi matrix. These results were found to be in reasonable agreement with thermodynamic calculations.
Irradiation assisted stress corrosion cracking (IASCC) is a form of intergranular stress corrosion cracking that occurs in irradiated austenitic alloys. It requires an irradiated microstructure along with high temperature water and stress. The process is ubiquitous in that it occurs in a wide range of austenitic alloys and water chemistries, but only when the alloy is irradiated. Despite evidence of this degradation mode that dates back to the 1960s, the mechanism by which it occurs has remained elusive. Here, using high resolution electron backscattering detection to analyze local stress-strain states, high resolution transmission electron microscopy to identify grain boundary phases at crack tips, and decoupling the roles of stress and grain boundary oxidation, we are able to unfold the complexities of the phenomenon to reveal the mechanism by which IASCC occurs. The significance of the findings impacts the mechanical integrity of core components of both current and advanced nuclear reactor designs worldwide.
Extended X-ray absorption fine structure (EXAFS) conducted on an equiatomic MoNbTaW bcc medium-entropy alloy that was annealed at 2273 K reveals unexpectedly small 1st and 2nd shell element-specific lattice distortions. An experimental size-mismatch parameter, δexp, is determined to be ca. 50% lower than the corresponding calculated value. Around W, short-range order (SRO) preferring 4d elements in the 1st and 2nd shells persists. A Nb-W ordering is found, which is reminiscent of ordering emerging at lower temperatures in the B2(Mo,W;Ta,Nb)- and B32(Nb,W)-phases. With high-temperature ordering preferences in fcc also foreshadowing low-temperature phase, these findings suggest a general feature of high-temperature SRO.
Mean-field modeling and Phase-field simulation of Grain Growth under Directional driving forces
(2024)
Directional grain growth is a common phenomenon in the synthetic and natural evolution of various polycrystals. It occurs in the presence of an external driving force, such as a temperature gradient, along which grains show a preferred, yet competitive, growth. Novel additive manufacturing processes, with intense, localized energy deposition, are prominent examples of when directional grain growth can occur, beneath the melting pool. In this work, we derive a phenomenological mean-field model and perform 3D phase-field simulations to investigate the directional grain growth and its underlying physical mechanisms. The effect of the intensity of driving force is simulated and systematically analyzed at the evolving growth front as well as various cross-sections perpendicular to the direction of the driving force. We found that although the directional growth significantly deviates from normal grain growth, it is still governed by a power law relation <R> \propto t^n with an exponent n ~ 0.6–0.7. The exponent
exhibits a nontrivial dependence on the magnitude of the directional driving force, such that the lowest growth exponent is observed for intermediate driving forces. We elaborate that this can originate from the fact that the forces at grain boundary junctions evolve out of balance under the influence of the directional driving force. With increasing the driving forces, the growth exponent asymptotically approaches a value of n~0.63, imposed by the largest possible grain aspect ratio for given grain boundary energies. The current combined mean-field and phase-field framework pave the way for future exploration in broader contexts such as the evolution of complex additively manufactured microstructures.