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

了解形状记忆合金中可恢复变形和永久变形之间的相互作用

• 批准号: 1851603
• 负责人: Samantha Daly
• 金额: $ 39.97万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1851603&HistoricalAwards=false
• 关键词: Understanding; Interactions; between; Recoverable; Permanent

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.

形状记忆合金是一种金属材料，具有独特的性能，包括超弹性行为。这项研究旨在指导这些合金的加工和设计，使其在生物医疗设备、航空航天和汽车零部件以及其他应用中的用途迅速扩大。镍钛合金(NiTi)是目前应用最广泛、造型最多的形状记忆合金，其研究成果在实际应用中对改善其性能将产生最广泛的影响。这项研究将使用新开发的实验方法--包括通过在扫描电子显微镜中跟踪纳米颗粒组件来测量微尺度变形的能力--来绘制和了解这些合金如何恢复大变形，以及哪些变形保持永久性。将应用机器学习方法将变形与原子结构联系起来，使人们能够更好地理解加工的影响，并进一步提高对形状记忆合金部件进行建模和设计的能力。除了这些新的信息，这项研究中开发的技术将对实验力学基础设施做出宝贵贡献，这些基础设施可以用于对广泛的材料进行研究。计划了几项外展活动，包括科学日和竞赛，向从小学到大学的学生介绍实验机械和材料。本研究将从实验上表征多晶形状记忆合金中应力诱发马氏体相变和位错滑移之间的相互作用，特别是微观结构对这些相互作用的性质和所导致的超弹性行为的影响。全场、高分辨率的形变映射将与高维聚类和计算机视觉方法相结合，以分割和识别关于微观结构的相变和滑移，从而揭示随机和确定性的贡献。这项研究将在实验上解决预测多晶形状记忆合金行为的一个核心困难，即晶粒之间存在应变不相容。目前的本构模型在很大程度上是通过与实验应力-应变曲线的比较来评估的。然而，这种比较并不理想，因为它是在两个不同的长度尺度上进行的：宏观曲线与基于微观力学的模型进行比较。这项研究的结果将提供对形状记忆合金行为至关重要的晶内相互作用的实验洞察，通过实验验证本构模型的基础，并定量地解决正在激烈辩论的假设；例如，转变和塑性可以协同发生的假设，塑性提供了跨越不利于转变的颗粒的桥梁机制。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。