Adapting the Mn content within a Fe-Mn-Si-based shape memory alloy by <i>in situ</i> parameter variations in laser-based additive manufacturing

Shape memory alloys exhibit unique properties ideal for functionally integrated components, such as actuators. While commonly used Ni-Ti alloys are well established, especially in biomedicine and aerospace, their high cost limits wider applications. Fe-based shape memory alloys present an affordable alternative, suitable for diverse applications, with a larger thermal hysteresis but lower recovery strain. Nonetheless, their functional properties can be enhanced through optimized processing methods like laser powder bed fusion and adjustments to their alloy composition. In the present study, laser powder bed fusion was used for modifying the composition and microstructure of a Fe-30Mn-6Si-5Cr alloy. For this purpose, laser parameters were varied to evaporate up to 47.3% of the initial Mn in the manufacturing process. In this context, the amount of Mn evaporated was dependent on both the line energy and more considerably on the volume energy density introduced in the manufacturing process. Subsequently, the impact of the resulting compositional changes on the microstructure was analyzed, and the functional properties were visualized using a demonstrator. Lowering the Mn content below 24.1% led to a higher degree of ferrite in the otherwise austenitic microstructure. This also affected the functional properties. These findings highlight the potential of laser-based additive manufacturing for modifying the composition and microstructure of shape memory alloys in situ and, thus, tailoring their functional properties.

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Publication Details

Journal
Journal of Laser Applications
Published
2024-09-16
DOI
https://doi.org/10.2351/7.0001560
Citations
2
Primary Topic
Shape Memory Alloy Transformations
Type
article
Field-Weighted Citation Impact
0.23

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article

Adapting the Mn content within a Fe-Mn-Si-based shape memory alloy by in situ parameter variations in laser-based additive manufacturing

Anastasiya Toenjes, Jonas Schmidt, Maylin Homfeldt
2 citations
Journal of Laser Applications
Shape Memory Alloy Transformations
0.23
article

Adapting the Mn content within a Fe-Mn-Si-based shape memory alloy by in situ parameter variations in laser-based additive manufacturing

Anastasiya Toenjes, Jonas Schmidt, Maylin Homfeldt
article en
2 citations

Abstract

Shape memory alloys exhibit unique properties ideal for functionally integrated components, such as actuators. While commonly used Ni-Ti alloys are well established, especially in biomedicine and aerospace, their high cost limits wider applications. Fe-based shape memory alloys present an affordable alternative, suitable for diverse applications, with a larger thermal hysteresis but lower recovery strain. Nonetheless, their functional properties can be enhanced through optimized processing methods like laser powder bed fusion and adjustments to their alloy composition. In the present study, laser powder bed fusion was used for modifying the composition and microstructure of a Fe-30Mn-6Si-5Cr alloy. For this purpose, laser parameters were varied to evaporate up to 47.3% of the initial Mn in the manufacturing process. In this context, the amount of Mn evaporated was dependent on both the line energy and more considerably on the volume energy density introduced in the manufacturing process. Subsequently, the impact of the resulting compositional changes on the microstructure was analyzed, and the functional properties were visualized using a demonstrator. Lowering the Mn content below 24.1% led to a higher degree of ferrite in the otherwise austenitic microstructure. This also affected the functional properties. These findings highlight the potential of laser-based additive manufacturing for modifying the composition and microstructure of shape memory alloys in situ and, thus, tailoring their functional properties.

Journal of Laser ApplicationsVol. 36(4)
University of Bremen (DE), Leibniz-Institut für Werkstofforientierte Technologien - IWT (DE)
Leibniz-Gemeinschaft
Openalex Percentile: Top 51%
Shape Memory Alloy Transformations
0.23
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