Litcius/Paper detail

Thermodynamically Guided Improvement of Fe–Mn–Al–Ni Shape‐Memory Alloys

Alexander Walnsch, André Bauer, J. Freudenberger, Katharina Freiberg, Christina Wüstefeld, Malte Vollmer, Stephanie Lippmann, Thomas Niendorf, Andreas Leineweber, Mario J. Kriegel

2023Advanced Materials15 citationsDOIOpen Access PDF

Abstract

A microstructural informed thermodynamic model is utilized to tailor the pseudoelastic performance of a series of Fe-Mn-Al-Ni shape-memory alloys. Following this approach, the influence of the stability and the amount of the B2-ordered precipitates on the stability of the austenitic state and the pseudoelastic response is revealed. This is assessed by a combination of complementary nanoindentation measurements and incremental-strain tests under compressive loading. Based on these investigations, the applicability of the proposed models for the prediction of shape-memory capabilities of Fe-Mn-Al-Ni alloys is confirmed. Eventually, these thermodynamic considerations enable the guided enhancement of functional properties in this alloy system through the direct design of alloy compositions. The procedure proposed renders a significant advancement in the field of shape-memory alloys.

Topics & Concepts

Shape-memory alloyMaterials sciencePseudoelasticityAusteniteAlloyNanoindentationMetallurgyStability (learning theory)MicrostructureMartensiteComputer scienceMachine learningShape Memory Alloy TransformationsMicrostructure and Mechanical Properties of SteelsHigh Entropy Alloys Studies