Electron Backscatter Diffraction Data Research Articles

Magnetic Fabrics in Laminated Rocks of the Ilímaussaq Igneous Complex, Southern Greenland

ABSTRACT Nepheline syenites from the ∼1.2 Ga Ilímaussaq Complex of southern Greenland are examined to assess the utility of anisotropy of magnetic susceptibility (AMS) fabrics as proxies for silicate petrofabrics. Mineral lamination is a relatively common structural feature in cumulate rocks, including in the Ilímaussaq intrusion, but there is little consensus on the process (or processes) responsible for its formation. The Ilímaussaq AMS data are combined with rock magnetic experiments and electron backscatter diffraction (EBSD) measurements to characterize the magnetic mineralogy and compare the magnetic fabrics obtained to the silicate petrofabric. The data show that Na-amphibole (arfvedsonite) is most likely the dominant control on the AMS fabrics in the coarse-grained nepheline syenites (referred to as kakortokites), and that the AMS fabric is inverse relative to the observed silicate fabric. The EBSD data for a kakortokite sample suggests that the petrofabric is defined by arfvedsonite and is wholly planar, with evidence of only weak cross-lineation of c axes. The fine-grained nepheline syenites (lujavrites), two of which have a well-developed lamination carried by Na-pyroxene (aegirine), appear to have composite AMS fabrics that are considered to be a consequence of a mixed aegirine (normal) and arfvedsonite (inverse) response. The combined datasets shed light on the mechanisms of fabric acquisition in both lithologies. In the kakortokites, the AMS fabrics and silicate crystallographic preferred orientations, as well as the lack of observed microstructural evidence for subsolidus intra-crystal deformation, support models invoking gravitationally controlled crystal mats in the development of the macro-rhythmic layering of these rocks. In the lujavrites, the strong planar fabrics revealed by both the AMS and EBSD datasets, with some evidence of subsolidus deformation, point to fabric formation and perhaps even aegirine crystallization at the postcumulus stage. The combination of EBSD and AMS fabric datasets is a powerful means of deciphering the processes responsible for mineral alignment in igneous cumulates.

Assessment of former austenite structure in hot rolled steel in terms of its texture after martensitic transformation

Textures of medium carbon steel, hot rolled and then quenched, have been determined by Electron backscatter diffraction (EBSD). To ensure representativeness of results, a rather large treated scan covered about a thousand of prior grains, each containing several thousands of measurement points. Considering inter-phase orientation relationships peculiar to martensitic steels, textures of the high temperature phase (austenite) have been assessed in terms of the transformation textures. Thus, deformed and recrystallized states of austenite dependent on the rolling conditions can be distinguished. To verify EBSD data, martensite textures were measured by an independent method of EBSD whereas morphology of the prior grains was revealed by means of chemical etching.

High-temperature hot deformation behavior and processing map of Ti-22Al-25Nb alloy

The high-temperature deformation behavior of the Ti-22Al-25Nb alloy was investigated by conducting hot compression experiments. A constitutive equation predicting the flow behavior of the Ti-22Al-25Nb alloy was established by analyzing its stress–strain curves. The strain-compensated constitutive equation effectively predicted the flow stress of the alloy with a correlation coefficient of 0.992 between the measured and predicted values and an average absolute relative error of 6.548 %. A hot processing map was obtained based on a dynamic material model. It demonstrated that the optimal processing region corresponded to the deformation temperatures of 1273–1353 K and strain rates of 0.001–0.01 s−1. Using electron backscatter diffraction data, thermal deformation mechanisms were elucidated under different deformation conditions within the safe region. The obtained results revealed that under the low temperature (T ≤ 1323 K) and low strain rate (ε̇ ≤ 1 s−1) conditions, continuous dynamic recrystallization and dynamic recovery (DRV) were the main thermal deformation mechanisms. Under the medium-to-high temperature (T ≥ 1323 K) and low strain rate (ε̇ ≤ 1 s−1) conditions, the main thermal deformation mechanisms were discontinuous dynamic recrystallization and DRV. At high strain rates (ε̇ ≥ 1 s−1), the primary thermaldeformation mechanism was DRV. The occurrence of discontinuous yielding in the alloy at high strain rates was related to the proliferation of mobile dislocations at grain boundaries.

Predicting mechanical properties of low-alloy steels using features extracted from Electron Backscatter Diffraction characterization

Machine learning (ML) approaches have recently been increasingly employed to establish quantitative relationships between material composition, processing, microstructure, and properties. However, the complexities of microstructure pose challenges for straightforward modeling, thereby complicating research efforts. This study introduces a series of multi-parametric quantification methods based on Electron Backscatter Diffraction (EBSD) data tailored to the microstructural characteristics of low-alloy steels. These methods include quantification of boundary densities across various misorientation angles, distinct types of boundaries, and geometrically necessary dislocation densities. Through thermomechanical simulation and micro-tensile testing of low-alloy steels, data on yield and ultimate tensile strengths were obtained, alongside EBSD-based extraction of microstructure characteristics. Several ML methods, including Random Forest (RF), Gradient Boosting Decision Trees (GBDT), and Extreme Gradient Boosting (XGBoost), were utilized to predict yield strength (YS) and ultimate tensile strength (UTS) using the aforementioned microstructural features. The GBDT model outperformed other algorithms, demonstrating high accuracy in predicting YS, UTS, and elongation. The model achieved an Mean Squared Error (MSE) of 972.18, an Mean Absolute Error (MAE) of 24.75 and an Coefficient of Determination (R2) of 0.864 for YS, and an MSE of 812.28, an MAE of 22.87 and an R2 of 0.823 for UTS. These results confirm GBDT's effectiveness in predicting mechanical properties from microstructural data.This successful integration of ML with multi-parametric description microstructural features underscores its potential in facilitating material design and development processes.

Imaging and Segmenting Grains and Subgrains Using Backscattered Electron Techniques.

We present two new methods of processing data from backscattered electron signals in a scanning electron microscope to image grains and subgrains. The first combines data from multiple backscattered electron images acquired at different specimen geometries to (1) better reveal grain boundaries in recrystallized microstructures and (2) distinguish between recrystallized and unrecrystallized regions in partially recrystallized microstructures. The second utilizes spherical harmonic transform indexing of electron backscatter diffraction patterns to produce high angular resolution orientation data that enable the characterization of subgrains. Subgrains are produced during high-temperature plastic deformation and have boundary misorientation angles ranging from a few degrees down to a few hundredths of a degree. We also present an algorithm to automatically segment grains from combined backscattered electron image data or grains and subgrains from high angular resolution electron backscatter diffraction data. Together, these new techniques enable rapid measurements of individual grains and subgrains from large populations.

Efficient Phase Segmentation of Light-Optical Microscopy Images of Highly Complex Microstructures Using a Correlative Approach in Combination with Deep Learning Techniques

Reliable microstructure characterization is essential for establishing process–microstructure–property links and effective quality control. Traditional manual microstructure analysis often struggles with objectivity, reproducibility, and scalability, particularly in complex materials. Machine learning methods offer a promising alternative but are hindered by the challenge of assigning an accurate and consistent ground truth, especially for complex microstructures. This paper introduces a methodology that uses correlative microscopy—combining light optical microscopy, scanning electron microscopy, and electron backscatter diffraction (EBSD)—to create objective, reproducible pixel-by-pixel annotations for ML training. In a semi-automated manner, EBSD-based annotations are employed to generate an objective ground truth mask for training a semantic segmentation model for quantifying simple light optical micrographs. The training masks are directly derived from raw EBSD data using modern deep learning methods. By using EBSD-based annotations, which incorporate crystallographic and misorientation data, the correctness and objectivity of the training mask creation can be assured. The final approach is capable of reproducibly and objectively differentiating bainite and martensite in optical micrographs of complex quenched steels. Through the reduction in the microstructural evaluation to light optical micrographs as the simplest and most widely used method, this way of quantifying microstructures is characterized by high efficiency as well as good scalability.

New insights from crystallography into the effect of Ni content on ductile-brittle transition temperature of 1000 MPa grade high-strength low-alloy steel

The significant effect of Ni content (0.92, 1.94 and 2.94 wt%) on ductile-brittle transition temperature (DBTT) and microstructure in a 1000 MPa grade high-strength low-alloy (HSLA) steel was studied. Using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), Charpy impact test and low-temperature tensile test to study the fundamental reasons for the effect of Ni content on toughness. The results indicated that increasing the Ni content can reduce the DBTT of HSLA steel and improve the impact toughness at low temperatures. EBSD data post-processing analysis revealed that the key reason for the increase in low-temperature toughness is the refinement of the microstructural crystallographic structure, specifically the significant increase in the boundary density of the block and packet. With the increase of Ni content, the density of grain boundary with an orientation difference greater than 5° between two adjacent {110} crystal planes was higher, which can form a higher density of dislocation pile-up group, thus better reducing local stress concentration. Meanwhile, the stacking fault energy (SFE) increases with the increase of Ni content, which made the screw dislocation more prone to cross slip at low temperature, resulting in an increase in plasticity at low temperatures. These observed phenomena and reasons provided a theoretical explanation for the role of Ni content in reducing DBTT and enhancing the toughness of the core in heavy gauge plates.

Kinematic vorticity of shear zones that accommodate vertical crustal advection: Implications for metamorphic core complexes and pluton emplacement

Kinematic analysis of ductile shear zones is an important method to interpret the dynamic evolution of many tectonic and magmatic processes on Earth, such as orogeny, rifting, and plutonism. Despite decades of study, kinematic vorticity analysis is an underutilized tool to interpret the dynamic drivers of shear zones. Determination of the kinematic vorticity number (Wk) quantifies the relative contributions of pure- versus simple-shear strain in shear zones. Here we systematically investigated Wk from mylonitic shear zones associated with metamorphic core complexes (MCCs) developed across the central and southern North American Cordillera using electron backscatter diffraction (EBSD) data that allows consistent and reproducible results from a large number of recrystallized grains. We investigated samples from four distinct MCC systems and the structural aureole of a Cordilleran pluton to investigate their kinematics. We find that most MCC samples display pure-to-general-shear strain (average 70 % pure shear), consistent with significant bulk shear-zone shortening (>80 % shortening) observed in many of the MCC systems. Such strain patterns are remarkably similar to deformation observed around plutons that were forcefully emplaced as diapirs. To further validate and investigate these results, we constructed the Wk field of these geologic processes using numerical simulations to highlight that pure shear kinematics are more common with diapirism and coupled wallrock deformation compared with discrete detachment-involved normal fault systems. These observations support that buoyant doming can be a viable end-member process to form the investigated MCCs. Our results also suggest that pure shear deformation may be a diagnostic strain characteristic for diapir-like crustal processes, and therefore Wk analyses could be used to test similar processes like dome-and-keel models for Early Earth.

Automated analysis framework of strain partitioning and deformation mechanisms via multimodal fusion and computer vision

Simultaneously investigating strain partitioning and the underlying deformation mechanisms for both the grain interior and the grain boundary (GB) is essential for understanding the complex plastic deformation of hexagonal close-packed metals. To this end, an automated analysis framework based on high-resolution digital image correlation (HRDIC) and electron backscatter diffraction (EBSD) data fusion and computer vision, integrating nanoscale resolution and a large field of view, is proposed. This framework consists of: (1) HRDIC-EBSD data fusion; (2) Segmenting the strain field into individual grains each with a core and a mantle; (3) Data clustering of the Matrix and slip bands (SBs) for each grain; (4) Full slip system (SS) identification and SS assignment to the SBs. The capabilities of this framework were demonstrated on Mg-10Y during compression. The strain field data, which was segmented into different clusters, including grain mantle, grain core, Matrix, and SBs, was analyzed statistically and quantitatively. The pixel-based slip activity, which considers the SB morphology, was obtained from a statistical perspective. Inter-granular accommodating mechanisms, including GB strain, slip transfer, and GB sliding, were quantitatively analyzed. Overall, this analysis framework, which can be applied to other materials, can automatically and statistically evaluate both nanoscale strain fields and underlying intra- and inter-granular deformation mechanisms grain-by-grain. This work provides valuable experimental insights into plastic deformation and accommodation mechanisms for polycrystals.

Modeling local deformation, damage distribution, and phase transformation in zirconia particle-reinforced TRIP steel composites

This study investigates tensile deformation, damage analysis, and the effect of microtexture on a 10 % vol. zirconia particle-reinforced TRIP steel composite. In situ tensile tests and simulations were conducted, with sequential SEM images captured during tensile loading tests and electron backscatter diffraction (EBSD) providing initial crystal orientation data. SEM images were utilized in digital image correlation (DIC) analysis to calculate the local plastic strain distribution using VEDDAC software. Initial micrographs and EBSD data were transformed into geometry files for simulations, employing crystal plasticity with a dislocation density-based model and a newly proposed phase field approach-based ductile-brittle damage criterion for both austenite and ceramic particles. MATLAB's image processing functions were used to compare and validate experimentally observed damage instances with simulation predictions. The effect of microtexture combined with various physical quantities was explored using MTEX. The results show that the simulations accurately predict strain concentration around ceramic particles, with a higher strain observed in the middle region compared to the DIC observations. The simulated strain in the austenitic matrix is found to be 1.4 times higher than the DIC measurements. Quantitative analysis of damage pixels reveals that the proposed critical plastic strain value aligns closely with experimental results, showing an error of - 0.25 % compared to 1.121 % for a smaller strain case. This comprehensive analysis provides insight into the effect of microstructural attributes on material performance and behavior under tensile deformation, leading to a validated microstructural-informed damage-inclusive crystal plasticity model.

Effect of unusual texture on tension-compression asymmetry for Mg-RE alloy by viscoplastic self-consistent modeling

The tension-compression asymmetry presents notable challenges for the application of magnesium alloys in many fields. In this study, the solid-solution treated Mg-8.5Gd-4.5Y-0.8Zn-0.4Zr alloy's tension-compression asymmetry was examined using optical microscope (OM), x-ray diffraction (XRD), viscoplastic self-consistent (VPSC) modeling, and electron backscatter diffraction (EBSD). The VPSC hardening parameters were significantly adjusted based on the Schmid factor of deformation modes in rare earth magnesium (Mg-RE) alloy, which came from the EBSD data. Excellent agreement was found between the modified VPSC model's calculation results, especially the stress-strain curves and pole figures. The alloy exhibited good strength with a negligible tension-compression asymmetry and an impressive 0.98 ratio of compressive yield strength to tensile yield strength (CYS/TYS). The main cause could be attributed to the unusual texture of (11-20) <0001> in alloy, which eliminated the imbalance in tension and compression deformation by having a negative effect on the activation of {10-12} twinning in tensile and a positive effect in compressive deformation. The activation level of {10-12} twinning was 0.37 and 0.40 calculated by VPSC model, in the plastic deformation of tension and compression, respectively; in the tensile and compression samples, the EBSD data indicated that approximately 31.9% and 31.1% (area proportion) of the grains were deformed with twins, respectively. Both tension and compression deformation showed the {10-12} twinning in the early stage of deformation, which transformed to {11-22} twinning in the later stage. The considerable activation of pyramidal <c+a> during the later stages of deformation endowed the alloy with good ductility.

Investigation of constitutive models and microstructure evolution during hot deformation and solution treatment of Al–Zn–Mg–Cu alloy

In this paper, isothermal thermal compression tests were carried out on Al–Zn–Mg–Cu alloys at varying deformation temperatures (360°C∼440°C) and strain rates (0.001s−1∼10s−1) using a Gleeble-3500C thermal simulation tester. Based on the true strain stress data obtained from the tests, the flow behavior of Al–Zn–Mg–Cu alloys during thermal deformation was investigated. Through a comprehensive consideration of deformation temperature, strain rate, and strain compensation, a high-precision constitutive model was established. Additionally, the specimens subjected to hot compression were further treated with solution annealing for different durations (0 h–2 h) to investigate the static recrystallization (SRX) behavior and the associated microstructural evolution of the alloy during the solution treatment process. Electron Backscatter Diffraction (EBSD) was employed to characterize the microstructure evolution of Al–Zn–Mg–Cu alloy under various deformation and solution treatment conditions. The EBSD data were further processed and analyzed using the MTEX toolbox. The results revealed that dynamic recovery (DRV) is the predominant softening mechanism during the deformation process, accompanied by a small amount of dynamic recrystallization (DRX). The dynamically recrystallized grains exhibit a random crystallographic orientation. Further investigation showed that low temperature and high strain rate conditions are unfavorable for the occurrence of dynamic recovery and dynamic recrystallization during the thermomechanical processing. However, dislocations accumulated during deformation provided sufficient stored energy for the growth of static recrystallized grains during subsequent solution treatment, with static recrystallized grains predominantly forming at grain boundaries.

High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction

The need to optimize the processing conditions of additively manufactured (AM) metals and alloys has driven advances in throughput capabilities for material property measurements such as tensile strength or hardness. High-throughput (HT) characterization of AM metal microstructure has fallen significantly behind the pace of property measurements due to intrinsic bottlenecks associated with the artisan and labor-intensive preparation methods required to produce highly polished surfaces. This inequality in data throughput has led to a reliance on heuristics to connect process to structure or structure to properties for AM structural materials. In this study, we show a transformative approach to achieve laser powder bed fusion (LPBF) printing, HT preparation using dry electropolishing and HT electron backscatter diffraction (EBSD). This approach was used to construct a library of > 600 experimental EBSD sample sets spanning a diverse range of LPBF process conditions for AM Kovar. This vast library is far more expansive in parameter space than most state-of-the-art studies, yet it required only approximately 10 labor hours to acquire. Build geometries, surface preparation methods, and microscopy details, as well as the entire library of >600 EBSD data sets over the two sample design versions, have been shared with intent for the materials community to leverage the data and further advance the approach. Using this library, we investigated process–structure relationships and uncovered an unexpected, strong dependence of microstructure on location within the build, when varied, using otherwise identical laser parameters.

Evolution mechanism of rapid solidification microstructure of an undercooled copper-based single phase alloy

Using undercooling technology combined with melt purification of glass and recirculation overheating, different undercoolings were successfully obtained for Cu60Ni38Co2 alloy samples. Applying high speed photography technique, the physical process of undercooled solidification was observed and relationship between undercooling and solidification rate was analyzed. Experimental results indicate the critical undercoolings exist in the structure evolution process. Electron backscatter diffraction (EBSD) analysis was applied to characterize the Cu60Ni38Co2 alloy sample with a maximum undercooling of 255K, revealing grain orientation and the corresponding orientation difference distribution. In addition, transmission electron microscopy (TEM) showed high density dislocation networks. Combining EBSD and TEM data analysis, an important conclusion was drawn: recrystallization is the main factor for grain refinement at high undercooling. This finding is of great significance for a deeper understanding of the structure evolution in the physical process of undercooled alloys.

Granitic mush compaction by impingement of a large felsic enclave: Evidence from the Aztec Wash pluton (Nevada, USA)

Abstract Compaction and melt extraction are key processes in the generation of melt-dominated magma bodies. We analyze magmatic fabrics in the Aztec Wash pluton (15.7 Ma; Nevada, USA) to understand magma dynamics during emplacement of a large (2 m diameter) felsic enclave (LFE) in a silicic magma body. We hypothesize that the LFE moved through crystal-poor magma, settling into crystal-rich magma. We analyze four granite samples collected near the enclave: two 0.25 m below the enclave (E-5 and E-2); one 0.5 m below (E-6); and one 2.5 m to the side (E-3, far field). We use the scanning electron microscope (SEM) to gather data using backscattered electron (BSE) microscopy, energy dispersive spectroscopy (EDS), and electron backscatter diffraction (EBSD) imaging. BSE maps show large (up to 10 mm) euhedral alkali feldspar grains in E-5 and E-2, while E-6 and E-3 have large (up to 6 mm) alkali feldspar with distinct irregular and wavy rims. Dark BSE alkali feldspar rims correlate with Ba depletion in EDS maps. Broken feldspars in E-5 and E-2 have mismatched zones in BSE and orientation differences in EBSD. Grain orientation spread (GOS) maps show that alkali feldspar has the highest degree of intragrain deformation, followed by plagioclase, then quartz. Histograms of the angle between the vertical plane and the pole to the (010) plane demonstrate clustering in E-5, suggesting an enhanced fabric. Differences in rim texture suggest melt extraction beneath the enclave and melt retained in the far field. EBSD data reveal an enhanced foliation beneath the LFE. We conclude that mush under the LFE was deformed during emplacement of the LFE, expelling melt and reorienting grains.

Aligned Permanent Magnet Made in Seconds–An In Situ Diffraction Study

AbstractThe synthesis of a strontium hexaferrite magnet is studied using in situ synchrotron powder X‐ray diffraction (PXRD) with a 16‐ms time resolution. The precursor material is cold compacted shape‐controlled goethite and strontium carbonate. The time evolution of the phases is modeled with sequential Rietveld refinements revealing that strontium hexaferrite forms within seconds at ≈1173 K. Texture analysis is performed on selected PXRD frames throughout the experiment, and the preferred orientation introduced by cold‐pressing goethite prevails through the iron oxide phase transitions (goethite → hematite → strontium hexaferrite). Electron backscatter diffraction (EBSD) data on the final pellet confirms the preferred orientation observed with PXRD. The resulting magnet has respectable magnetic properties, considering the simplicity of the preparation method, with an energy product (BHmax) of 18.6(8) kJ m−3.

Electrical current-assisted reactive crucible melting technique: Case study of the Fe-Sn system

Modern materials science relies heavily on the advancement of combinatorial high-throughput experimental and computational methods to discover new advanced materials. Among these methods, the reactive crucible melting (RCM) technique stands out as particularly promising. However, a significant challenge in RCM combinatorial analysis is the occurrence of "missing" phases. In this study, we successfully addressed this limitation through the application of electrical current stressing. Furthermore, we investigate the influence of electric current stressing on diffusion rates and the phase formation processes within the reactive crucible. We employed Comsol Multiphysics modeling to analyze the experimental results in the framework of electromigration theory, focusing on the distribution of electrical field lines, temperature gradients, and current density values. Additionally, through the integration of finite element calculations with analysis of Electron Backscatter Diffraction (EBSD) and Magneto-Optical Kerr Effect (MOKE) data, we estimated the gradient of internal stresses along the boundaries of the crucible's reaction volume induced by the diffusion of electrically-induced vacancies and adatoms. Due to modest values of the current density in our experiment and the disparity between the rates of crucible body dissolution and vacancy diffusion, no compressive or tensile stresses were observed. Nonetheless, we propose that the developed electrical current-assisted reactive crucible melting technique holds promise for synthesizing metastable phases existing under high positive or negative pressures.

The influence of rapid-diffusive β-stabilizers on the microstructure formation and superplasticity of titanium-based alloys

The superplasticity of Ti-based alloys is improved due to grain refinement, an increase in grain size stability, and an increase in the β-phase fraction up to ∼0.5. Alloying with β-stabilizers reduces the β-transus temperature and increases the β-phase fraction at low forming temperatures, thus improving the superplasticity and lowering its temperature. Both grain growth and superplastic deformation mechanisms are diffusion-controlled phenomena, and, therefore, the diffusivity of the alloying elements should have a significant effect on superplasticity. This work deals with the influence of the high-diffusive elements Fe, Co, and Ni on the grain structure and superplasticity of titanium alloys. For this purpose, the Ti-Al-Mo-V alloy, and alloys with proportional replacement of low-diffusive Mo by Fe, Co, or Ni, exhibiting an interstitial diffusion mechanism, were studied. The alloying elements content was selected to ensure the same β-phase fraction at a deformation temperature of ∼875 °C. The microstructure evolution after thermomechanical processing, annealing, and superplastic deformation, as well as post-deformation room-temperature mechanical properties of the studied alloys, were compared. The actual phase ratio was reconstructed by comparing scanning electron microscopy images in backscattered electrons and electron backscatter diffraction data for the same fragments. It was found that Mo replacement for highly diffusive elements accelerated dynamic grain growth during superplastic deformation at an elevated temperature of 875 °C but improved superplasticity at a lower temperature of 775 °C. The results confirmed that alloying with high-diffusive elements is a promising strategy for the design of low-temperature superplastic forming alloys.

Influence of grain boundary plane distribution on ionic conductivity in yttria-stabilized zirconia sintered at elevated temperatures

The paper investigates electrical properties of fully stabilized zirconia, which is widely applied as a solid electrolyte in electrochemical devices such as solid oxide fuel cells. High ionic conductivity of these materials is crucial for effective operating of the devices; however, grain boundary resistivity limits conductivity in polycrystalline ceramics. Thus, optimisation of the microstructure of zirconia is necessary from an application point of view. Based on three-dimensional electron backscatter diffraction (3D EBSD) data, the research employed a complex impedance spectroscopy to establish a correlation between microstructure of cubic zirconia sinters and their conductivity. Samples with different levels of anisotropy in grain boundary plane parameters were investigated. The obtained results indicate that the conduction of ions through the grain boundaries is higher in the sample with the higher representation of the near-(001) grain boundaries. Such a relationship suggests that an over-representation of low-energy grain boundaries in zirconia polycrystals leads to an increase of ionic conductivity.

Fatigue Analysis of the Nickel-Based Superalloy Inconel 617 by Fatigue Experiments and EBSD Data-Based Finite Element Simulations in Correlation with E·m Theories

Nickel-based superalloys exhibit pronounced elastic anisotropy and, hence, the local grain orientation strongly affects the stress and strain distribution in the material under mechanical loadings. Therefore, the crack initiation and failure behaviour of components made from nickel-based superalloys are complex and hardly predictable. A better fundamental understanding of the phenomena that occur in nickel-based superalloys under a quasistatic and cyclic load is therefore desired. Previously, a continuum mechanics-based model has been successfully developed, considering the grain structure, the elastic anisotropy, and the Schmid factor, based on data from electron backscatter diffraction (EBSD). The E·m model was confirmed by the finite element method (FEM) simulations and experimental observations regarding the resulting average stresses and strains in the individual grains as well as the formation of slip bands under a quasistatic load with few restrictions. The behaviour under cyclic loadings has been investigated in this work to correlate the mechanical behaviour, simulated by the previously developed FE models, with the local stiffness and Schmid factors considering fatigue failure. For this purpose, the fatigue behaviour of Inconel 617 samples was characterised up to the high-cycle fatigue (HCF) regime, accompanied by EBSD measurements for stress amplitudes that resulted in strains close to the elastic–plastic regime. The EBSD data were used to create digital twins of the samples to simulate the mechanical reaction to a displacement similar to the associated strain of the fatigue tests. An analysis of the fractured samples by scanning electron microscopy was performed to retrace the location of the crack initiation supported by the EBSD measurements before and after fatigue testing. Two samples were investigated in detail that showed different fracture types. Sample 1 showed transcrystalline failure in a grain that showed a high Young’s modulus, Schmid factor, and resolved shear stress that indicates a failure due to the properties of the grain itself. In contrast, an intercrystalline failure was observed for sample 2 that showed large differences in the orientation and, hence, largely different mechanical properties in the area of failure as well. The observed failure types, the resulting stresses and strains calculated by the FE model, and the consideration of the E·m model showed an agreement of all the methods. Therefore, the findings of this work complement previous investigations of the mechanical behaviour of coarse-grained anisotropic nickel-based superalloys with a focus on the orientations of the grains towards the loading direction.