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Understanding the Interactions between Recoverable and Permanent Deformations in Shape Memory Alloys

$403,674FY2019ENGNSF

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

Shape memory alloys are metallic materials that exhibit unique properties, including superelastic behavior. This research is targeted towards guiding the processing and design of these alloys for their rapidly expanding use in biomedical devices, aerospace and automotive components, and other applications. Nickel-Titanium (NiTi) will be examined because it is the most widely used and modeled shape memory alloy, and results from this work applied to improving its performance in practice will have the broadest impact. This research will use newly developed experimental approaches - including the ability to measure microscale deformations by tracking nanoparticle assemblies in a scanning electron microscope - to map and understand how these alloys recover large deformations, and what deformation remains permanent. Machine learning approaches will be applied to relate deformations to atomic structure, enabling an improved understanding of the effects of processing and furthering the ability to both model and design shape memory alloy components. In addition to this new information, the techniques developed in this research will be valuable contributions to the experimental mechanics infrastructure that can be used in investigations of a wide host of materials. Several outreach activities are planned, including science days and competitions to introduce students from elementary school to college to experimental mechanics and materials. This research will experimentally characterize the interactions between stress-induced martensitic phase transformation and dislocation slip in polycrystalline shape memory alloys, specifically the impact of microstructure on the nature of these interactions and the superelastic behavior that results. Full-field, high resolution deformation mapping will be combined with high-dimensional clustering and computer vision approaches to segment and identify transformation and slip with respect to microstructure, shedding light on stochastic and deterministic contributions. This research will experimentally address a core difficulty in predicting the behavior of polycrystalline shape memory alloys, which is the existence of strain incompatibilities between the grains. Current constitutive models are largely evaluated by the comparison to experimental stress-strain curves. However, this comparison is not ideal in that it is between two different length scales: macroscopic curves are being compared to micromechanics based models. The results from this research will offer experimental insights into the intragranular interactions that are critical to the behavior of shape memory alloys, experimentally validate the underpinnings of the constitutive models, and quantitatively address hypotheses that are under active debate; such as the hypothesis that transformation and plasticity can occur synergistically, with plasticity providing a bridging mechanism across grains that are poorly oriented for transformation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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