Abstract
Superelasticity in shape memory alloys (SMAs) is an important feature which caused by martensitic transformation and microstructural evolution. The composition of crystal variants and microstructures during the superelasticity process are simulated by molecular dynamics in the current work. Then, a computational post-processing scheme, which can identify variants type and interface orientation are proposed. This method reveals that the crystal adopts a multi-phase mixture during the superelsticity process, including many crystal systems, such as orthorhombic (O), R-phase (R), monoclinic (M) and body-centered-orthorhombic (BCO). In addition, the interface normal vectors between two different variants are examined by the compatibility equation, and the result has good agreement. The stress–strain curve, volume fraction for present variants and total energy diagram are illustrated. The microstructural evolution shows that R phase can serve as the transitional region between pairs of BCO variants. The variants O, BCO, M phase coherent between each other with specific pattern to form twinned arrangement. Furthermore, different random seeds for the initial velocity of the atoms, are used in the simulation to obtain equivalent microstructural evolution paths. The corresponding macroscopic properties are analyzed. The microstructural evolution path can have different energy barrier of initialization, which also leads to different present variant in the crystal. The results discovered in the current work are expected to provides design guidelines for the applications in SMAs.
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Acknowledgements
The authors wish to acknowledge the support of the Ministry of Science and Technology (MOST), Taiwan, Grant no. MOST 104-2628-E-009-004-MY2. We would also like to thank the National Center for High-performance Computing (NCHC) of the National Applied Research Laboratories (NARLabs) of Taiwan for providing a computational platform.
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Lai, MJ., Lu, HY. & Tsou, NT. Microstructural Evolution of Superelasticity in Shape Memory Alloys. Multiscale Sci. Eng. 1, 141–149 (2019). https://doi.org/10.1007/s42493-018-00010-0
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DOI: https://doi.org/10.1007/s42493-018-00010-0