Leibniz-Institut für Werkstofforientierte Technologien – IWT
Shape memory alloys (SMAs) exhibit unique properties that make them ideal for functionally integrated components, such as actuators. In our research we explore the integration of additive manufacturing with Fe-based SMAs, offering a cost-effective method for producing geometrically complex parts. While commonly used Ni-Ti alloys are well-established, especially in biomedicine and aerospace, their high cost limits wider applications. Fe-based SMAs present an affordable alternative, suitable for diverse applications, but with a larger thermal hysteresis. However, our initial findings demonstrate an improvement in the recovery stress of additively manufactured Fe-based SMAs compared to conventional processing. In addition, the shape memory effect of Fe-based SMAs can be adjusted by changing the alloy composition.
To address the challenge of optimizing Fe-based SMAs for different applications, a novel approach is used. Our Smart-Alloying technology enables in-situ re-alloying of metals within the laser-based powder bed fusion process. This method allows local adjustment of the alloying degree of individual elements in a component, providing a cost- and material-efficient high-throughput method for alloy modification and functional grading.
The talk showcases the advantages of additive manufacturing using an FeMnSiCr-alloy as an example. Alterations in the alloying degree of individual elements of this base alloy are explored, analyzing their effects on shape recovery strain and stress, as well as microstructural changes of phases and precipitates. The findings contribute to a deeper understanding of the influence of individual alloying elements, such as carbon, on the shape memory effect—a topic that is still partly debated in the literature.
Attendees will gain insights into a novel re-alloying process for additive manufacturing, offering a pathway to optimize SMA composition. The research extends our understanding of the influence of individual alloying elements on the shape memory effect, providing valuable contributions to the field.
Abstract
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