6.4 Materialinformatik
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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.
Ni-Mn-Ga shape-memory alloys are promising candidates for large strain actuation and magnetocaloric cooling devices. In view of potential small-scale applications, we probe here nanomechanically the stress-induced austenite–martensite transition in single crystalline austenitic thin films as a function of temperature. In 0.5 μm thin films, a marked incipient phase transformation to martensite is observed during nanoindentation, leaving behind pockets of residual martensite after unloading. These nanomechanical instabilities occur irrespective of deformation rate and temperature, are Weibull distributed, and reveal large spatial variations in transformation stress. In contrast, at a larger film thickness of 2 μm fully reversible transformations occur, and mechanical loading remains entirely smooth. Ab-initio simulations demonstrate how an in-plane constraint can considerably increase the martensitic transformation stress, explaining the thickness-dependent nanomechanical behavior. These findings for a shape-memory Heusler alloy give insights into how reduced dimensions and constraints can lead to unexpectedly large transformation stresses that need to be considered in small-scale actuation design.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.