Abnormal Grain Growth in Four Dimensions
Abstract
Nearly all classes of materials Ñ from soap froths to metallic superalloys Ñ are composed of small domains known as grains. The sizes, orientations, and boundaries of the grains influence many of the solidÕs properties. For instance, the yield strength of polycrystalline materials decreases nonlinearly with increasing average grain size, as empirically described by the Hall-Petch relationship. While it is well known how the average grain size influences mechanical properties, comparatively very little is known on how a target grain size distribution can be obtained in the first place. During thermal processing, normal grain growth occurs, wherein some grains enlarge while others shrink and disappear. A second possibility, termed abnormal grain growth, is that a very few grains grow at a much faster rate than the others and eventually consume the microstructure. Abnormal grain growth has been observed in a vast array of metallic and semi-metallic alloys. Even so, the origins and mechanisms of abnormal grain growth have remained an enigma for at least the past seventy years. One such long-standing mystery concerns abnormal grain growth in the presence of second-phase particles. Our traditional understanding is that particles retard and eventually "pin" the grain boundaries. Yet, and paradoxically so, abnormal grain growth is most frequently seen in particle-containing systems. To explain this behavior, Holm et al. (2015) proposed a new model dubbed "particle assisted abnormal grain growth." From computer simulations, it was observed that a few grain boundaries thermally fluctuate from their pinned configurations and are thus allowed to propagate freely. Yet it remains to be determined which grain boundaries are most likely to break free and why. Secondly, it is unclear how abnormal grain growth is sustained as the freely propagating boundaries encounter new microstructural neighborhoods. Largely, the model is unsubstantiated due to the lack of in situ and 3D experiments. Our goal is to verify Holm et al. s model by making use of new strides in laboratory-based 4D (i.e., 3D space plus time) imaging. In particular, a key strength of this proposal is the integration of two nondestructive imaging modalities Ñ absorption-based and diffraction-based X-ray computed tomographies Ñ to understand particle-boundary interactions in all their complexity. The particle-containing, Al-Cu and Fe-Si alloys to be investigated here will be quenched at various stages during annealing to image the resulting microstructures via our multimodal imaging platform. Following the experiments, advances in computational methods and high performance computing will open the doors to a wealth of information on the collection of grains undergoing abnormal growth: For instance, the 4D data will be analyzed via PI Shahani s computational toolbox to extract grain boundary characteristics and velocities (via diffraction-based tomography) together with particle locations (via absorption-based tomography), as a function of time. These metrics will provide direct evidence on the kinetic pathways leading to the growth of abnormal grains. They will also serve as inputs for canonical correlation analysis, in order to determine which combinations of processing variables are most strongly tied to the occurrence of abnormal grain growth. These processing?structure linkages will have immediate and profound impact to the structural materials community: for instance, the insights gained can be used by researchers to design polycrystalline materials with controllable grain sizes.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 19, 2019
- Source ID
- W911NF1810162
Entities
People
- Ashwin Shahani
Organizations
- Army Contracting Command
- United States Army
- University of Michigan