Grain Boundaries and Interfaces: Metastability, Disorder, and Non-Equilibrium Behavior: Microstructures: Crystallography, GB Network, Phase Diagram, etc
Sponsored by: TMS Materials Processing and Manufacturing Division, TMS: Computational Materials Science and Engineering Committee, TMS: Chemistry and Physics of Materials Committee, TMS: Phase Transformations Committee
Program Organizers: Yue Fan, University of Michigan; Liang Qi, University of Michigan; Jeremy Mason, University of California, Davis; Garritt Tucker, Colorado School of Mines; Pascal Bellon, University of Illinois at Urbana-Champaign; Mitra Taheri, Johns Hopkins University; Eric Homer, Brigham Young University; Xiaofeng Qian, Texas A&M University
Thursday 8:30 AM
March 3, 2022
Room: 263B
Location: Anaheim Convention Center
Session Chair: Yue Fan, University of Michigan, Ann Arbor; Eric Homer, Brigham Young University
8:30 AM Invited
Grain Boundary "Phase" Diagrams: Jian Luo1; 1University of California, San Diego
This talk will review our studies to compute grain boundary (GB) counterparts to bulk phase diagrams. A series of earlier studies used a phenomenological thermodynamic model to construct “GB lambda diagrams” to forecast high-temperature GB disorder and an Ising-type lattice model to predict GB adsorption. Recent studies utilize hybrid Monte Carlo and molecular dynamics simulations to compute GB diagrams [PRL 2018; Scripta 2019]. Furthermore, genetic algorithm-guided deep learning was combined with atomistic simulations to predict GB properties as functions of five macroscopic degrees of freedom plus temperature and composition in a 7D space [Materials Today 2020]. Current studies include (a) derivation of a systematics of GB diagrams in binary regular solutions with universal characters, (b) extending the computation of GB diagrams from thermodynamic to mechanical properties, and (c) predicting the GB properties as functions of four independent compositional degrees of freedoms and temperature in a 5D space for high-entropy alloys.
9:00 AM
Characterization of the Structure and Chemistry of Grain Boundaries and Heterointerfaces in Multiphase High Entropy Oxides Processed by Heat Treatment: Hasti Vahidi1; Alexander Dupuy1; Justin Cortez1; Julie Schoenenung1; William Bowman1; 1University of California Irvine
High entropy oxide (HEO) materials greatly expand the available compositional space and possess promising functional properties for a range of ceramic applications, all of which are influenced by the presence of grain boundaries and heterointerfaces. Research on HEOs is still in its early stages and exploratory studies are required to understand the uniqueness and similarities between these complex oxides and conventional oxide ceramics. The rock salt (Co,Cu,Mg,Ni,Zn)O HEO system is known to undergo a reversible entropic phase transformation upon heat treatment, forming secondary phases that significantly change the microstructure of the material, thereby providing a means of controlling behavior and properties through heat treatment. Here, we use advanced transmission electron microscopy (TEM) and scanning TEM to observe the local atomic structure, composition, defect chemistry, and electronic structure of the heterointerfaces between the oxide precipitates and HEO matrix to elucidate how these phases form, grow, and potentially impact functionality.
9:20 AM
Calculating Representative and Statistical Volume Elements for Grain Boundary Networks Using 3D Microstructural Data: Jeremy Green1; Nathan Miller1; Oliver Johnson1; 1Brigham Young University
Appropriately sized microstructural samples can act as predictors for macroscopic material properties while minimizing experimental or computational time and cost. Representative volume elements (RVEs) or statistical volume elements (SVEs) define the smallest volume that reproduces some macroscopic microstructural statistic or material property. We have recently predicted the size or cardinality of 3D RVEs and SVEs for grain boundary networks (GBNs) using 2D microstructural data and stereological methods. However, advances in technology are increasing the prevalence of 3D microstructural data. In this work, synthetically generated 3D microstructures are used to provide the first direct calculations of RVEs and SVEs for GBNs. We compare these to RVEs and SVEs for crystallographic texture, in addition to the previous predictions based on stereological approaches. These results provide size recommendations which will aid computational and experimental researchers to make informed decisions regarding sample size, and thereby obtain quantitatively sound results.
9:40 AM
5D Grain Boundary Energy Landscapes, Paths and Correlations from Bayesian Inference: Sterling Baird1; Eric Homer1; David Fullwood1; Oliver Johnson1; 1Brigham Young University
Leveraging our recently developed Voronoi fundamental zone (VFZ) framework, we use Bayesian inference strategies to infer 5D structure-property models for GB energy. We discuss how distributions of metastable GB states can be easily incorporated into this method both to inform GB structure-property model development, and to incorporate the effects of metastability into property predictions and subsequent mesoscale simulations. By analyzing the resulting models, we quantify the size and shape of FZs for cubic materials, and test and give context to commonly assumed correlation lengths for GBs. We demonstrate the way in which correlation length depends on crystallographic character and describe the implications for computational modeling. Finally, we identify important paths through the resulting GB energy landscapes that may influence microstructural evolution in ways that have not previously been investigated.
10:00 AM
Percolation Behavior of Three-dimensional Grain Boundary Networks: Jiwoong Kang1; Ashwin Shahani1; 1University of Michigan
The connectivity of grain boundaries plays a critical role in many intergranular phenomena, including corrosion, cracking, and liquid metal embrittlement. To characterize the complex structure of the grain boundary network, Schuh and others have invoked standard percolation theory based on a simulated microstructure with an arbitrarily imposed grain topology. To generalize these results to real materials, we have experimentally probed the three dimensional (3D) grain boundary network in Al-3.5wt%Cu as a model system via laboratory-based X-ray diffraction-contrast tomography. The 3D data and the scaling laws of percolation theory enable us to quantify the percolation threshold and compare to simulation and theory. We find self-consistent percolation thresholds using different order parameters. Furthermore, we confirm a reasonable agreement between results from our 3D experiments and other simulations when grain topology is normalized. Further work is underway to achieve larger 3D grain maps to avoid potential bias from limited size of data.
10:20 AM Break
10:35 AM Invited
Relationships between Grain Boundary Crystallographic Structure and Grain Boundary Properties: Gregory Rohrer1; 1Carnegie Mellon University
Much of what we know about grain boundaries and the way they move derives from the study of bicrystals using elegant experiments and atomistic simulations. In a bicrystal, the grain boundaries are free to migrate without the constraints imposed by a grain boundary network. In a polycrystal, each boundary is connected to (on average) ten other boundaries at five triple lines. In this talk, I will discuss measurements of grain boundary properties (areas, curvatures, energies, and velocities) from the study of many (on the order of 100,000) grain boundaries in three-dimensional polycrystals. We find that all of these properties vary with all five crystallographic parameters describing the boundary. In addition, we find that some of these properties are dependent on one another and others are independent. The findings highlight the important of grain boundary crystallography and imply the importance of grain boundary atomic structure.
11:05 AM
Spanning the 5D Space of Grain Boundaries: A Comprehensive Database of Computed Aluminum Grain Boundary Structures and Their Interface Energy: Braxton Owens1; Lydia Serafin1; Derek Hensley1; Jay Spendlove1; Gus Hart1; Eric Homer1; 1Brigham Young University
The space of possible grain boundary structures is vast, with 5 macroscopic, crystallographic degrees of freedom that define the character of a grain boundary. While numerous datasets of grain boundaries have examined this space, none has systematically examined the full range of possibilities. We present a computed dataset of more than 5000 unique aluminum grain boundaries in the 5D crystallographic space. Our sampling includes a range of possible microscopic, atomic configurations for each unique 5D crystallographic structure, which we refer to as metastable grain boundary structures. In all, the number of metastable structures associated with all the unique grain boundaries is over 36 million. We will present an overview of the methods used to generate this dataset, an initial examination of the raw data, as well as methods and insights gained in machine learning of grain boundary energy structure-property relationships and relationships between metastable structures for each unique grain boundary.
11:25 AM
Motion of a Dislocation Boundary in Thermal Annealing Resolved with Dark-field X-ray Microscopy: Leora Dresselhaus-Marais1; Can Yildirim2; Henning Poulsen3; Carsten Detlefs2; Grethe Winther3; 1Stanford University; 2ESRF; 3DTU
Dislocation boundaries dominate the multiscale structure and properties of metals, setting the complex dynamics that determine how they respond to external stresses or heating. Recovery during thermal annealing leads to dislocation annihilation, self-organization into and coarsening of dislocation structures through mechanisms that are poorly understood at the single-dislocation level – especially deep inside bulk materials. I present a new view of how dislocation boundaries migrate, evolve and destabilize over the course of thermal annealing, using the novel time-resolved dark-field X-ray microscopy (DFXM). With movies of long-range dislocation motion and interactions that span hundreds of micrometers, we reveal the dynamics that cause these 3D structures to migrate and dissolve at temperatures >0.9 Tm, illustrating how stochastic thermal motion drives the high-T recovery.
11:45 AM
Study of the Evolution of the Grain Boundary Network Using Spectral Graph Theory: Jose Nino1; Oliver Johnson1; 1Brigham Young University
The evolution of the structure of the Grain Boundary network (GBN) during grain growth strongly influences material properties. If we could characterize the structure of GBNs, then it would be possible to perform design/optimization for improved material performance. However, the structure of GBNs is highly complicated. Traditional microstructural descriptors like grain size distribution, orientation distribution function, or even grain boundary character distribution fail to encode the main features of the GBN, including e.g. its topological structure and the spatial distribution of GB types. For this reason, we apply a new technique called Spectral Graph Theory (SGT) which allows us to encode the GB character information as well as the topological structure of the GBN. We calculate and analyze the spectrum of several microstructures and develop a reconstruction method to obtain the microstructure from its spectrum. We evaluate whether the spectrum of a microstructure encodes the main features of the GBN.