Filtern
Dokumenttyp
Sprache
- Englisch (6)
Schlagworte
- Additive manufacturing (1)
- Alloy Safety (1)
- Alloy microstructure (1)
- Atom probe tomography (1)
- Brightness (1)
- CALPHAD (1)
- Defects engineering (1)
- Density-based Thermodynamics (1)
- Digitalization (1)
- Hierarchical microstructure (1)
Organisationseinheit der BAM
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.
Instead of foreseeing and preparing for all possible scenarios of machine failures, accidents, and other challenges arising in space missions, it appears logical to take advantage of the flexibility of additive manufacturing for “in-space manufacturing” (ISM). Manned missions into space rely on complicated equipment, and their safe operation is a great challenge. Bearing in mind the absolute distance for manned missions to the Moon and Mars, the supply of spare parts for the repair and replacement of lost equipment via shipment from Earth would require too much time. With the high flexibility in design and the ability to manufacture ready-to-use components directly from a computer-aided model, additive manufacturing technologies appear to be extremely attractive in this context. Moreover, appropriate technologies are required for the manufacture of building habitats for extended stays of astronauts on the Moon and Mars, as well as material/feedstock. The capacities for sending equipment and material into space are not only very limited and costly, but also raise concerns regarding environmental issues on Earth. Accordingly, not all materials can be sent from Earth, and strategies for the use of in-situ resources, i.e., in-situ resource utilization (ISRU), are being
envisioned. For the manufacturing of both complex parts and equipment, as well as for large infrastructure, appropriate technologies for material processing in space need to be developed.
For more than half a century, spinodal decomposition has been a key phenomenon in considering the formation of secondary phases in alloys. The most prominent aspect of the spinodal phenomenon is the lack of an energy barrier on its transformation pathway, offering an alternative to the nucleation and growth mechanism. The classical description of spinodal decomposition often neglects the influence of defects, such as grain boundaries, on the transformation because the innate ability for like-atoms to cluster is assumed to lead the process. Nevertheless, in nanocrystalline alloys, with a high population of grain boundaries with diverse characters, the structurally heterogeneous landscape can greatly influence the chemical decomposition behavior. Combining atom-probe tomography, precession electron diffraction and density-based phase-field simulations, we address how grain boundaries contribute to the temporal evolution of chemical decomposition within the miscibility gap of a Pt-Au nanocrystalline system. We found that grain boundaries can actually have their own miscibility gaps profoundly altering the spinodal decomposition in nanocrystalline alloys. A complex realm of multiple interfacial states, ranging from competitive grain boundary segregation to barrier-free low-dimensional interfacial decomposition, occurs with a dependency upon the grain boundary character.
Single particle imaging of upconversion nanoparticles (UCNPs) has typically been realized using hexagonal (β) phase lanthanide-doped sodium yttrium fluoride (NaYF4) materials, the upconversion luminescence (UCL) of which saturates at power densities (P) of several hundred W cm−2 under 980 nm nearinfrared (NIR) excitation. Cubic (α) phase UCNPs have been mostly neglected because of their commonly observed lower UCL efficiency at comparable P in ensemble level studies. Here, we describe a set of sub-15 nm ytterbium-enriched α-NaYbF4:Er3+@CaF2 core/shell UCNPs doped with varying Er3+ concentrations (5–25%), studied over a wide P range of ∼8–105 W cm−2, which emit intense UCL even at a low P of 10 W cm−2 and also saturate at relatively low P. The highest upconversion quantum yield (ΦUC) and the highest particle brightness were obtained for an Er3+ dopant concentration of 12%, reaching the highest ΦUC of 0.77% at a saturation power density (Psat) of 110 W cm−2. These 12%Er3+-doped core/shell UCNPs were also the brightest UCNPs among this series under microscopic conditions at high P of ∼102–105 W cm−2 as demonstrated by imaging studies at the single particle level. Our results underline the potential applicability of the described sub-15 nm cubic-phase core/shell UCNPs for ensemble- and single particle-
level bioimaging.
The embrittlement of metallic alloys by liquid metals leads to catastrophic material failure and severely impacts their structural integrity. The weakening of grain boundaries by the ingress of liquid metal and preceding segregation in the solid are thought to promote early fracture. However, the potential of balancing between the segregation of cohesion-enhancing interstitial solutes and embrittling elements inducing grain boundary decohesion is not understood. Here, we unveil the mechanisms of how boron segregation mitigates the detrimental effects of the prime embrittler, zinc, in a Σ5 [0 0 1] tilt grain boundary in α −Fe (4 at.% Al). Zinc forms nanoscale segregation patterns inducing structurally and compositionally complex grain boundary states. Ab-initio simulations reveal that boron hinders zinc segregation and compensates for the zinc induced loss in grain boundary cohesion. Our work sheds new light on how interstitial solutes intimately modify grain boundaries, thereby opening pathways to use them as dopants for preventing disastrous material failure.
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.