Electron Backscatter Diffraction Data Research Articles

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.

Prediction and Elucidation of Physical Properties of Polycrystalline Materials Using Multichannel Machine Learning of Electron Backscattering Diffraction

AbstractThe application of machine learning in materials science has yielded several benefits, including the prediction of physical properties and the improvement of experimental efficiency. However, with complex models, such as convolutional neural networks (CNN), learning has become a black box, from which no universal physical knowledge can be obtained. In this study, a highly accurate prediction of the electrical properties of polycrystalline semiconductor thin films is achieved by learning multichannel CNN models from electron backscattering diffraction (EBSD) data, that is band contrasts, grain boundaries, and inverse pole figures. In addition, it examines how the CNN model learned the correlation between the crystallinity, grain boundaries, crystallographic orientation, and carrier mobility by polarizing certain EBSD data and checking the predicted changes in carrier mobility. Physical parameters affecting carrier mobility can be extracted, which is challenging via human image recognition. The methods proposed in this study will not only enable the prediction of electrical properties from EBSD data for all materials but also will contribute to the discovery of complex physical phenomena beyond the limits of human analysis.

Three-Dimensional Columnar Microstructure Representation Using 2D Electron Backscatter Diffraction Data for Additive-Manufactured Haynes®282®.

This study provides a methodology for exploring the microstructural and mechanical properties of the Haynes®282® alloy produced via the Powder Bed Fusion-Electron Beam (PBF-EB) process. Employing 2D Electron Backscatter Diffraction (EBSD) data, we have successfully generated 3D representations of columnar microstructures using the Representative Volume Element (RVE) method. This methodology allowed for the validation of elastic properties through Crystal Elasticity Finite Element (CEFE) computational homogenization, revealing critical insights into the material behavior. This study highlights the importance of accurately representing the grain morphology and crystallographic texture of the material. Our findings demonstrate that created virtual models can predict directional elastic properties with a high level of accuracy, showing a maximum error of only ~5% compared to the experimental results. This precision underscores the potential of our approach for predictive modeling in Additive Manufacturing (AM), specifically for materials with complex, non-homogeneous microstructures. It can be concluded that the results uncover the intricate link between microstructural features and mechanical properties, underscoring both the challenges encountered and the critical need for the accurate representation of grain data, as well as the significance of achieving a balance in EBSD area selection, including the presence of anomalies in strongly textured microstructures.

Текстура рекристалізації та анізотропії пружних властивостей листів сталі DC04

We studied steel sheets DC04 (0.06% C, up to 0.35% Mn, up to 0.40% Si, ~ 0.025% S and P) with a thickness of 0.95 mm as delivered. Sheets of A4 size were annealed in a laboratory oven (6000C in an argon atmosphere, hold for 1 hour). The structure of DC04 steel sheets after recrystallization annealing was studied. The microstructure of the steel sheets under study is presented from the side of the rolling plane and in the section of the sheet perpendicular to the direction. In the plane of the sheets, the grains are elongated; in the cross section, the grains are approximately equiaxed. Pole figures (PF) were constructed based on the results of electron backscatter diffraction (EBSD) on a LEO 1455 VP electron microscope at an accelerating voltage of 20 kV from the plane of the sheets and from the section of the sheet perpendicular to the rolling direction. To improve statistics, PF were constructed by averaging reflex stereographic projections from 20 different representative volumes of material relative to the rolling direction and transverse direction. The texture and anisotropy of Young's modulus in the plane and cross section of steel sheets DC04 after recrystallization annealing was studied using EBSD method. A connection has been obtained between ideal orientations that describe the texture in two mutually perpendicular planes and the corresponding integral characteristics of texture (ICT). Rectangular samples with a length of 100 and a width of 10 mm at different angles to the rolling direction every 150 to measure Young's modulus. Samples were processed in a bag to ensure uniform dimensions. Young's modulus was determined by the dynamic method from the frequency of natural transverse vibrations. Three batches of samples were used to construct Young's modulus anisotropy curves. The anisotropy of the Young's modulus in the plane of steel sheets, calculated from the ICT based on the results of EBSD data, is in good agreement with the results of direct measurements. The value of Young's modulus in the direction normal to the plane of the sheet and in the section plane in the direction normal to the plane of the sheet, calculated from the ICT and the values of the compliance constants of iron, coincide. Keywords: texture, pole figure, anisotropy, integral characteristics of texture, Young's modulus.

Temperature dependent deformation behavior and texture evolution in AA6082 aluminum alloy: An integrated experimental and crystal plasticity simulation approach

This research provides a comprehensive analysis of the texture and temperature dependent deformation behavior of the aluminum alloy AA6082. The study is performed using a combination of experimental deformation tests and computational simulations using a crystal plasticity (CP) framework. The primary objective is to identify the critical influence of temperature on local stress states and dislocation density within the material during tensile tests. From an experimental perspective, the study employs ex-situ deformation tests and subsequent electron backscatter diffraction (EBSD) data in combination with energy dispersive x-ray spectrometer (EDS) analysis at 200 °C and 400 °C. The experimental EBSD data are adopted, preprocessed and converted into a geometry file for the numerical simulations. On the computational front, a dislocation density-based material model is adopted for CP simulations. The physical and fitting parameters of the model are calculated, adopted from the literature, or calibrated by comparing the global simulation results with experimental stress-strain observations under uniaxial tensile load at room temperature, 200 °C and 400 °C. Empirical functions for solid solution strengthening, dislocation density, fitting parameters controlling mean free path and dislocation annihilation have been derived that can be used to quickly interpolate them for any intermediate temperature. These functions combined with other model parameters can now be used for temperature-dependent CP modeling of AA6082. The isothermal grain-scale simulation and ex-situ experimental results confirmed a noteworthy texture transformation at higher temperatures, characterized by a reduction in the primary Cube orientation and its transition into a Copper orientation due to the stretching process. The correlation between the experimental results and the simulations on macro- and micro-scales is reasonable, indicating the accuracy and effectiveness of the CP approach in predicting the temperature dependent deformation behavior and texture evolution in aluminum alloys.

Electron backscatter diffraction analysis unveils foraminiferal calcite microstructure and processes of diagenetic alteration

Abstract. Electron backscatter diffraction (EBSD) analysis enables a unique perspective of the internal microstructure of foraminiferal calcite. Specifically, EBSD provides crystallographic data from within the test, highlighting the highly organised “mesocrystal” structure of crystallographically aligned domains throughout the test, formed by sequential deposits of microgranular calcite. We compared EBSD maps across the test walls of both poorly preserved and well-preserved specimens of the planktonic foraminifera species Globigerinoides ruber and Morozovella crater. The EBSD maps, paired with information about intra-test distributions of Mg/Ca ratios, allowed us to examine the effects of different diagenetic processes on the foraminifera test. In poorly preserved specimens EBSD data show extensive reorganisation of the biogenic crystal microstructure, indicating differing phases of dissolution, re-precipitation and overgrowth. The specimens with the greatest degree of microstructural reorganisation also show an absence of higher concentration magnesium bands, which are typical features of well-preserved specimens. These findings provide important insights into the extent of post-depositional changes, in both microstructure and geochemical signals that must be considered when utilising foraminifera to generate proxy archive data.

Quantification of melt pool dynamics and microstructure during simulated additive manufacturing

The dynamics of laser spot melting and metallic alloy solidification are investigated through synchrotron x-ray radiography, 3D electron backscatter diffraction data, and computational fluid dynamics (CFD) simulations on a model NiMoAl alloy. Solidification velocities are measured from in-situ images to validate a CFD model of the spot melt. TriBeam tomography is used to reconstruct the melt pool in 3D, characterize the microstructure, and validate the CFD model melt pool dimensions. 3D geometrically necessary dislocation (GND) density calculations reveal extensive deformation at the sample surface. GND calculations integrated with the CFD model reveal that the halo of small, equiaxed grains adjacent to the fusion line is a result of recrystallization that occurred in the heat affected zone. By combining in-situ and ex-situ data modalities across a variety of temporal and spatial length scales, the microstructure formation mechanisms and their relationship to melt pool solidification are quantified.

A “step” in the right direction: Quantifying error in twinning analysis due to EBSD scan resolution

Accurate evaluation of deformation twinning statistics is key when performing research on the twinning behavior of magnesium alloys or other HCP materials, and typically utilizes electron backscatter diffraction (EBSD). However, many modern studies that perform EBSD for twinning analysis do not have a consistent step size used during EBSD data collection between studies, or do not report their step size at all. In this work, the effect of step size on the resultant twinning statistics calculated from the EBSD data was determined by comparing multiple scans of the same region with varying step size. Increasing the step size during data collection was found to increase the error of all considered twinning statistics, indicating a potential source of unquantified error in other studies. Additionally, a method for improving the accuracy from scans with coarse step sizes was considered and found to reduce error in most cases.

A novel method for segmentation of titanium microtexture regions via sensor data fusion

The current nondestructive inspection paradigm of mono-modal testing and signal-over-threshold call criteria is insufficient for characterization of microtexture regions in titanium alloys, which exceeds the capabilities of any single, practical sensing technique that could be deployed to a manufacturing environment for quality control. In this work, we develop a data fusion-based solution to microtexture region characterization. The material problem and potential inspection methods are reviewed, and registered datasets are presented. Next, we develop a data fusion algorithm that combines covariance-generalized matching component analysis and a conditionally Gaussian hypermodel to successfully estimate the boundaries and average crystallographic orientations of microtexture regions from scanning electron microscopy electron backscatter diffraction and eddy current testing data.

Estimating dislocation density from electron backscatter diffraction data for an AZ31/Mg-0.6Gd hybrid alloy fabricated by high-pressure torsion

ABSTRACT The Geometrically Necessary Dislocation (GND) density was estimated from Electron Backscatter Diffraction (EBSD) data for an AZ31/Mg-0.6Gd (wt.%) hybrid material fabricated by high-pressure torsion (HPT) at room temperature through an equivalent strain range of ϵeq = 0.3–144 using Kernel Average Misorientation (KAM) and the Nye tensor approaches. The results show that generally the GND densities are significant at the beginning of the deformation (ϵeq = 0.3) and decrease in both alloys when ϵeq increases. The Mg-0.6Gd alloy exhibits a lower GND density due to rapid dynamic recrystallization. These results were compared to the GND densities measured in AZ31 and Mg-0.6Gd mono-materials processed separately by HPT under the same experimental conditions. In these mono-materials the GND densities increase with increasing equivalent strain up to 7 and then decrease with further straining. The Mg-0.6Gd and AZ31 regions of the hybrid material exhibit higher GND densities than the mono-materials particularly at low strain where the disc thickness and the bonding of the AZ31/Mg-0.6Gd interfaces cause more deformation heterogeneity in the hybrid material. It is shown that the GND density evolution as a function of ϵeq has the same tendency for the KAM and the Nye approaches but the average values are significantly higher with the Nye approach. An analysis suggests that the Nye approach overestimates the GND density of the Mg-based alloys.

A new approach to three-dimensional microstructure reconstruction of a polycrystalline solar cell using high-efficiency Cu(In,Ga)Se2

A new method for efficiently converting electron backscatter diffraction data obtained using serial sectioning by focused ion beam of a polycrystalline thin film into a computational, three-dimensional (3D) structure is presented. The reported data processing method results in a more accurate representation of the grain surfaces, reduced computer memory usage, and improved processing speed compared to traditional voxel methods. The grain structure of a polycrystalline absorption layer from a high-efficiency Cu(In,Ga)Se2 solar cell (19.5%) is reconstructed in 3D and the grain size and surface distribution is investigated. The grain size distribution is found to be best fitted by a log-normal distribution. We further find that the grain size is determined by the [Ga]/([Ga] + [In]) ratio in vertical direction, which was measured by glow discharge optical emission spectroscopy. Finally, the 3D model derived from the structural information is applied in optoelectronic simulations, revealing insights into the effects of grain boundary recombination on the open-circuit voltage of the solar cell. An accurate 3D structure like the one obtained with our method is a prerequisite for a detailed understanding of mechanical properties and for advanced optical and electronic simulations of polycrystalline thin films.

Prior austenite grain measurement: A direct comparison of EBSD reconstruction, thermal etching and chemical etching

It is well known that the prior austenite grain (PAG) microstructure of steels has a significant impact on their microstructure evolution and mechanical properties. Many PAG measuring techniques have been developed over many decades, with the effectiveness of each varying alloy-to-alloy. Some of the more common techniques, specifically for bainitic and martensitic grades, are thermal etching and picric acid etching, which both involve the preferential etching of PAG boundaries in order to reveal the austenitic microstructure. More recently, parent grain reconstruction techniques using EBSD (electron backscatter diffraction) mapping have shown good promise in recreating PAG microstructures from BCC-FCC orientation relationships, and can now be deployed at speed with the advent of rapid detectors (1000s of pixels per second). This study aims to compare the accuracy and relative advantages/disadvantages of picric acid etching, thermal etching and EBSD reconstruction methods. A TESCAN and NewTec In-Situ Testing (TANIST) capability was used to directly observe and measure the true high-temperature PAG structure during the austenitisation of SA-540 B24 low alloy steel. These high-temperature PAG measurements were then compared to measurements from the same area obtained using thermal etching, picric acid etching and EBSD parent grain reconstructions after quenching to room temperature. Reconstructing the parent austenite grains from EBSD data resulted in the closest measurement of PAG size. PAG boundaries were delineated well by thermal etching but surface effects (such as surface relief and ghost traces) created complexities when identifying the exact position of boundaries. Picric acid etching, which produced the least accurate measurement, was found to reveal PAG boundaries well, however it was limited by its ability to sufficiently etch annealing twin boundaries and its susceptibility to microsegregational effects. EBSD reconstruction and thermal etching were more consistent at reconstructing/revealing these boundaries, although inaccuracies with the techniques were still observed.

Microstructural Response of Highly Porous Sintered Nano-silver Particle Die Attachments to Thermomechanical Cycling

This paper deals with the performance of sintered nano-silver bonds used as wide-bandgap power module die attachment technology. The paper specifically explores the fine-scale microstructures of highly porous sintered attachments under power cycling to provide a deeper understanding of the significance of porosity as a reliability-related microstructural parameter. Attachments prepared at 220°C using a pressure of 6 MPa for 1 s (parameters known to generate approximately 50% porosity from previous work) and subsequently subjected to 650,000 power cycles between 50°C and 200°C are assessed. A correlative workflow integrating x-ray computed tomography, focused ion beam (FIB) and electron backscatter diffraction (EBSD) data is applied to merge meso- and nanoscale microstructural features to illuminate the degradation mechanisms. The as-sintered Ag layer has a high volume of heterogeneously distributed pores, and consists of randomly oriented equiaxed grains whose sizes vary depending on the local density of the region sampled. Power cycling promotes grain growth and the loss of twin boundaries, and these changes are more pronounced within more dense regions of the Ag attachment. In contrast, the copper substrate appears to undergo some grain refinement, with deformation twins visible within finer-grained zones during power cycling. Cracks, which appear to start off within the Ag layer, propagate across the Ag-Cu boundary and transgranularly through fine-grained regions within the copper with little tortuosity. These observations are discussed within the context of reliability behaviour.Graphical

Grain size and orientation affected deformation inhomogeneity and local damage of hot-deformed Al-Zn-Mg alloy

The forming defects at elevated temperature caused by the microstructural evolution such as grain size, crystal orientations are the critical issue that induced deformation inhomogeneity and local damage which severely limits the application of Al-Zn-Mg alloys in thin-walled structure manufacturing. In this study, the hot deformation behavior and microstructural evolution were investigated via hot stretching tests, electron backscatter diffraction (EBSD) and the transmission electron microscopy (TEM) characterization. Then, an integrated multiscale constitutive model coupled dislocation density based crystal plasticity (CP) model and phase field method (PFM) was established through the reconstructed configuration of deformation gradient emphasized on a damaged part. The coupled CP-PFM model was numerically implemented into Düsseldorf Advanced Material Simulation Kit (DAMASK) software. Subsequently, a set of virtual polycrystalline RVE models assigned with different average grain sizes and two types of RVE models with realistic crystal orientations were constructed from EBSD data. The experimental and simulation results of the Al-Zn-Mg alloy under hot tensile loading showed that the grain size refinement leads to the increase of grain boundary density, which leads to the rapid increase of dislocation density, uniform damage distribution and better work hardening ability. In addition, the coordination of the activation of different slip systems between adjacent grains will lead to the uneven distribution of dislocation density and local damage.

{332}[formula omitted] twinning in a [formula omitted]-type Ti-Nb alloy over a wide range of strain rates

The {332}〈113〉 twinning in a β-type Ti-25Nb alloy is investigated quantitatively at 10% compression strain over a wide range of strain rate from 10−2 s−1 to 106 s−1, using material testing system, split Hopkinson pressure bar, and gas gun loading. Electron backscatter diffraction data are collected from the postmortem samples to obtain activated twinning systems and twinning strain tensors. With increasing strain rate, yield stress and twin density increase, and twin thickness decreases. At low strain rate, only the twinning systems with high Schmid factor can be activated to form thick twins. However, at medium and high strain rates, certain twinning activation deviates from the Schmid law, and twin thickening is relatively insensitive to Schmid factor. Twinning strain is the highest for the matrix grain orientations near 〈114〉, but approximately zero for the orientations near 〈111〉. Contribution of twinning to plastic strain at medium strain rate is significantly higher than those at low and high strain rates.

A lightweight transformer for faster and robust EBSD data collection

Three dimensional electron back-scattered diffraction (EBSD) microscopy is a critical tool in many applications in materials science, yet its data quality can fluctuate greatly during the arduous collection process, particularly via serial-sectioning. Fortunately, 3D EBSD data is inherently sequential, opening up the opportunity to use transformers, state-of-the-art deep learning architectures that have made breakthroughs in a plethora of domains, for data processing and recovery. To be more robust to errors and accelerate this 3D EBSD data collection, we introduce a two step method that recovers missing slices in an 3D EBSD volume, using an efficient transformer model and a projection algorithm to process the transformer’s outputs. Overcoming the computational and practical hurdles of deep learning with scarce high dimensional data, we train this model using only synthetic 3D EBSD data with self-supervision and obtain superior recovery accuracy on real 3D EBSD data, compared to existing methods.

Diversity of the Structure of Diamond Crystals and Aggregates: Electron Backscatter Diffraction Data

Diversity of the Structure of Diamond Crystals and Aggregates: Electron Backscatter Diffraction Data

Weighted Burgers Vector analysis of orientation fields from high-angular resolution electron backscatter diffraction

The Weighted Burgers Vector (WBV) method can extract information about dislocation types and densities present in distorted crystalline materials from electron backscatter diffraction (EBSD) maps, using no assumptions about which slip systems might be present. Furthermore, high-angular resolution EBSD (HR-EBSD) uses a cross-correlation procedure to increase the angular precision of EBSD measurements by an order of magnitude compared to conventional EBSD. However, the WBV technique has not previously been applied to HR-EBSD data and therefore it remains unclear as to which low-angle substructures can be reliably characterised by WBV analysis of conventional EBSD data and which require additional HR-EBSD processing. To establish some practical examples that can be used to guide future data-acquisition strategies, we compare the output of the WBV method when applied to conventional EBSD data and HR-EBSD data collected from the most common minerals in Earth's lower crust (plagioclase feldspar) and upper mantle (olivine). The results demonstrate that HR-EBSD and WBV processing are complementary techniques. The increase in angular precision achieved with HR-EBSD processing allows low-angle (on the order of 0.1°) structures, which are obscured by noise in conventional EBSD data, to be analyzed quantitatively using the WBV method. Combining the WBV and HR-EBSD methods increases the precision of calculated WBV directions, which is essential when using information about active slip systems to infer likely deformation mechanisms from naturally deformed microstructures. This increase in precision is particularly important for low-symmetry crystals, such as plagioclase, that have a wide range of available slip systems that vary in relative activity with changing pressure, temperature and differential stress. Because WBV directions are calculated using no assumptions about which slip systems may be present, combining this technique with HR-EBSD to refine the precision of lattice orientation gradients is ideal for investigating complex natural materials with unknown deformation histories.