Factors influencing shape memory effect and phase transformation behaviour of Fe–Mn–Si based shape memory alloys

Abstract

The objective of this research work was to investigate the factors influencing the shape memory effect and phase transformation behaviour of three Fe–Mn–Si based shape memory alloys: Fe-28Mn-6Si, Fe-13Mn–5Si-10Cr-6Ni and Fe-20Mn-6Si-7Cr-1Cu. The research results show that the shape memory capacity of Fe–Mn–Si based shape memory alloys varies with annealing temperature, and this effect can be explained in terms of the effect of annealing on γ↔e transformation. The nature and concentration of defects in austenite are strongly affected by annealing conditions. A high annealing temperature results in a low density of stacking faults, leading to a low nucleation rate during stress induced γ→e transformation. The growth of e martensite plates is favoured rather than the formation of new e martensite plates. Coarse martensite plates produce high local transformation strains which can be accommodated by local slip deformation, leading to a reduction in the reversibility of the martensitic transformation and to a degradation of the shape memory effect. Annealing at low temperatures (≤673 K) for reasonable times does not eliminate complex defects (dislocation jogs, kinks and vacancy clusters) created by hot and cold working strains. These defects can retard the movement and rearrangement of Shockley partial dislocations, i.e. suppress γ→e transformation, also leading to a degradation of shape memory effect. Annealing at about 873 K was found to be optimal to form the dislocation structures which are favourable for stress induced martensitic transformation, thus resulting in the best shape memory behaviour. Transmission electron microscopy observations supported the concept that the regular overlapping of stacking faults can result in the formation of bulk e martensite plates. Stacking faults were also found to exist in e martensite plates, and it is inferred that these faults can act as embryos for e→γ reverse transformation.