A molecular dynamics view of hysteresis and functional fatigue in martensitic transformations

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Date
2010
Volume
1497
Issue
Journal
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Publisher
Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik
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Abstract

Shape memory alloys (SMA) exhibit a number of features which are not easily explained by equilibrium thermodynamics, including hysteresis in the phase transformation and ?reverse? shape memory in the high symmetry phase. Processing can change these features: repeated cycling can ?train? the reverse shape memory effect, while changing the amount of hysteresis and other functional properties. These effects are likely to be due to creation of persistent localised defects, which are impossible to study using non-atomistic methods. Here we present a molecular dynamics simulation study of this behaviour. To ensure the largest possible system size, we use a two dimensional binary Lennard-Jones model, which represents a reliable qualitative model system for martensite/austenite transformations. The evolution of the defect structure and its excess energy is investigated in simulations of cyclic transformation/ reverse transformation processes with 160,000 atoms. The simulations show that the transformation proceeds by non-diffusive nucleation and growth processes and produces distinct microstructure. Upon transformation, lattice defects are generated which affect subsequent transformations and vary the potential energy landscape of the sample. Some of the defects persist through the transformation, providing nucleation centres for subsequent cycles. Such defects may provide a memory of previous structures, and thereby may be the basis of a reversible shape memory effect.

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Keywords
Martensitic transformations, shape memory alloys, solid-solid phase transitions, hysteresis, functional fatigue
Citation
Kastner, O., Ackland, G. J., Eggeler, G., & Weiss, W. (2010). A molecular dynamics view of hysteresis and functional fatigue in martensitic transformations (Vol. 1497). Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik.
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