Boundary Network Topology Research Articles

Through-thickness microstructural evolution during grain boundary engineering type thermomechanical processing and its implication on sensitization behavior in austenitic stainless steel

Through-thickness microstructural variations and their synergistic influence on degree of sensitization in grain boundary engineering (GBE) treated 304L stainless steel was compared with solution-annealed and marginally cold-worked (~3% thickness reduction) specimens. The solution-annealed specimen has shown higher degree of sensitization due to the presence of lower fraction of Σ3 (as well as other low Σ CSL) boundaries and dominant random high-angle boundaries (RHAGBs) connectivity. However, it has shown thickness-independent sensitization behavior as grain boundary character distribution, residual strain and grain boundary network topology towards thickness direction are similar. Owing to higher residual strain, as revealed by local misorientation analysis, the cold-worked specimen showed maximum degree of sensitization (higher than solution-annealed condition) at surface. The GBE specimen has shown much lower degree of sensitization at surface due to higher-fraction of Σ3 boundaries and discontinuous RHAGBs connectivity. However, increasing fraction of RHAGBs and their connectivity, as confirmed by twinning-related domain and fractal analysis, cause more sensitization at interior of this specimen. In spite of this, the degree of sensitization at the interior of GBE specimen is lower than the solution-annealed or cold-worked specimen. Even though the residual strain in GBE specimen is higher than the solution-annealed condition, the lower degree of sensitization indicates that the grain boundary character distribution and grain boundary network topology have higher implication than residual strain in controlling sensitization.

Evolution of grain boundary network topology in 316L austenitic stainless steel during powder hot isostatic pressing

The grain boundary network evolution of 316L austenitic steel powder during its densification by hot isostatic pressing (HIPing) was investigated. While the as-received powder contained a network of random high angle grain boundaries, the fully consolidated specimen had a large fraction of annealing twins, indicating that during densification, the microstructure evolves via recrystallization. By interrupting the HIPing process at different points in time, microstructural changes were tracked quantitatively at every stage using twin boundary fractions, distribution of different types of triple junctions, and the parameters associated with twin related domains (TRDs). Results revealed that, with increase in temperature, (i) the fraction of annealing twins increased steadily, but they mostly were not part of the grain boundary network in the fully consolidated specimen and (ii) the average number of grains within a TRD, the length of longest chain, and twinning polysynthetism increased during HIPing and (iii) the powder characteristics and the HIPing parameters have a strong influence on the development of grain boundary network. Based on the results obtained, possible alterations to the HIPing process are discussed, which could potentially allow twin induced grain boundary engineering.

The uncorrelated triple junction distribution function: Towards grain boundary network design

Triple junctions are recognized as important microstructural features in the context of grain boundary network topology and grain boundary sensitive materials properties. In spite of this prominence, mathematical tools for quantifying distributions of misorientations around triple junctions have been limited to special cases. Here we derive a general formula for the uncorrelated triple junction distribution function (TJDF) for materials of arbitrary texture. Additionally, we provide the mathematical link between TJDF and the orientation distribution function, which should facilitate the use of materials design paradigms on the grain boundary network.

Discriminant Models of Uncertainty in Nominal Fields

AbstractDespite developments in error modeling in discrete objects and continuous fields, there exist substantial and largely unsolved conceptual problems in the domain of nominal fields. This article explores a novel strategy for uncertainty characterization in spatial categorical information. The proposed strategy is based on discriminant space, which is defined with essential properties or driving processes underlying spatial class occurrences, leading to discriminant models of uncertainty in area classes. This strategy reinforces consistency in categorical mapping by imposing class‐specific mean structures that can be regressed against discriminant variables, and facilitates scale‐dependent error modeling that can effectively emulate the variation found between observers in terms of classes, boundary positions, numbers of polygons, and boundary network topology. Based on simulated data, comparisons with stochastic simulation based on indicator kriging confirmed the replicability of the discriminant models, which work by determining the mean area classes based on discriminant variables and projecting spatially correlated residuals in discriminant space to uncertainty in area classes.

Analysis of grain boundary network topology using grain boundary wetting

A statistical method for the experimental study of the grain boundary network topology is proposed. The experimental binary classification of grain boundaries is based on their wetting behavior (wetted and non-wetted grain boundaries). The grain boundary energy distribution is used to describe the intergranular liquid network topology by means of the percolation theory. The model is applied to the experimental study of grain boundary wetting of polycrystalline zinc and aluminum by liquid gallium. Elemental mapping in a scanning electron microscope is used for cluster determination. The experimental observations are in accordance with the theory.

Analysis of grain boundary networks and their evolution during grain boundary engineering

The goal of grain boundary engineering is to increase the fraction of so-called special grain boundaries, while decreasing the contiguity of the remaining random boundaries which are susceptible to intergranular degradation such as cracking, cavitation, corrosion and rapid self-diffusion. In the present work, we describe a technique for the quantitative experimental study of grain boundary network topology, with an emphasis on the connectivity of special and random grain boundaries. Interconnected grain boundary networks, or “clusters”, of either entirely random or entirely special boundaries are extracted from electron backscatter diffraction data on a Ni-base alloy, and characterized according to their total normalized length (their “mass”), as well as their characteristic linear dimensions. The process of grain boundary engineering, involving cycles of straining and annealing, is found to substantially reduce the mass and size of random boundary clusters. Furthermore, quantitative assessment of the boundary network topology shows that the special grain boundary fraction is a poor predictor of network topology, but that the higher-order correlation derived from triple junction distributions can successfully describe the length scales of random boundary clusters.

Microstructural evolution during grain boundary engineering of low to medium stacking fault energy fcc materials

Grain boundary engineering comprises processes by which the relative fractions of so-called special and random grain boundaries in microstructures are manipulated with the objective of improving materials properties such as corrosion, creep resistance, and weldability. One such process also referred to as sequential thermomechanical processing (TMP), consists of moderate strains followed by annealing at relatively high temperatures for short periods of time. These thermomechanical treatments on fcc metals and alloys with low to medium stacking fault energies result in microstructures with high fractions of Σ3 n and other special boundaries, as defined by the coincidence site lattice (CSL) model. More importantly, the interconnected networks of random boundaries are significantly modified as a consequence of the processing. The modifications in the grain boundary network have been correlated with post-mortem electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM) observations of the deformed and annealed states of the material. The evolution of the microstructure to a high fraction of Σ3 n boundaries is correlated with the decomposition or dissociation of immobile boundaries during annealing. This is evidenced by TEM observations of the decomposition of relatively immobile boundaries into two components, one with very low energy and thus immobile, and the other a highly mobile boundary that migrates into neighboring areas of higher strain levels. The formation of low-energy grain boundaries through this mechanism and its effect on boundary network topology is discussed within the context of grain boundary engineering and linked to known microstructural evolution mechanisms.

On the Grain Boundary Character Distributions and Grain Boundary Network Topology (Grain Boundary Statistics in Materials Susceptible to Annealing Twinning, Revisited)

On the Grain Boundary Character Distributions and Grain Boundary Network Topology (Grain Boundary Statistics in Materials Susceptible to Annealing Twinning, Revisited)