Electron Backscatter Diffraction Datasets Research Articles

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.

Ambient grain orientation imaging on complex surfaces

Crystal orientation imaging is generally confined to the laboratory, typically following destructive sectioning, with most current techniques reliant on electron-material interactions that require a vacuum. This information is gathered in a manner that requires careful planning, however a more desirable approach would allow the manufacturer to acquire this data non-destructively at the point of manufacture, with little or no time penalty. We show that coupling a numerically controlled etching method to topographical data processing can be used to spatially map grain orientations over planar and non-planar surfaces. Our method allows the construction of large area orientation maps (≈400 mm2) in agreement with electron backscatter diffraction datasets. We have characterized spatial and angular resolution limits for the technique, which are correlated to length scales of microscale etch surfaces and our ability to measure their geometries. This approach has the potential to augment materials processing technologies, where resultant microstructures require strict control in order to guarantee through-life integrity.

Automated characterization and classification of 3D microstructures: an application to 3D deformation twin networks in titanium

The advent of techniques enabling three-dimensional (3D) analysis of objects, defects, and fields has been key to discoveries and paradigm shifts in molecular biology, astrophysics, medicine, quantum physics, etc. In materials science, the 3D nature of materials microstructures remains largely hidden; leading to a fragmented understanding of microstructure-property linkages. Current tools cannot characterize large volumes of 3D microstructures at fine resolution. To this end, this study introduces a graph-theory-based framework to automatically extract 3D microstructures and statistics of electron-backscatter diffraction datasets. Further, leveraging network science, the study introduces a new approach to classify and compare microstructures; the keystone to materials taxonomy. The significance of this tool is demonstrated by studying deformation twin structures in Titanium. The study reveals extraordinarily complex and tortuous twin networks never observed via traditional two-dimensional analysis. This changes our perception of the ability of metals to withstand severe microstructure changes without failing.

Registration between DCT and EBSD datasets for multiphase microstructures

The ability to characterise the three-dimensional microstructure of multiphase materials is essential for understanding the interaction between phases and their associated materials properties. Here, laboratory-based diffraction-contrast tomography (lab-based DCT), a recently-established materials characterization technique that can determine grain phases, morphologies, positions and orientations in a voxel-based reconstruction method, was used to map part of a dual-phase steel alloy sample. To assess the resulting microstructures produced by the lab-based DCT technique, an electron backscatter diffraction (EBSD) map was collected within the same sample volume. To identify the two-dimensional (2D) slice of the three-dimensional (3D) lab-based DCT reconstruction that best corresponded to the 2D EBSD map, a novel registration technique based solely on grain-averaged orientations was developed – this registration technique requires very little a priori knowledge of dataset alignment and can be extended to other techniques that only recover grain-averaged orientation data such as far-field 3D X-ray diffraction microscopy. Once the corresponding 2D slice was identified in the lab-based DCT dataset, comparisons of phase balance, grain size, shape and texture were performed between lab-based DCT and EBSD techniques. More complicated aspects of the microstructural morphology such as grain boundary shape and grains less than a critical size were poorly reproduced by the lab-based DCT reconstruction, primarily due to the difference in resolutions of the technique compared with EBSD. However, lab-based DCT is shown to accurately determine the centre-of-mass position, orientation, and size of the large grains for each phase present, austenite and martensitic ferrite. The results reveals a complex ferrite grain network of similar crystal orientations that are absent from the EBSD dataset. Such detail demonstrates that lab-based DCT, as a technique, shows great promise in the field of multi-phase material characterization.

Tool for automatic macrozone characterization from EBSD data sets of titanium alloys.

Microtexture heterogeneities are commonly found in titanium forgings because of the thermomechanical processing. Also known as macrozones, these regions can reach millimetres in length, with grains sharing a similar crystallographic orientation leading to less resistance to crack propagation. Since the link between macrozones and the reduction of cold-dwell-fatigue performance on rotative components in gas turbine engines was established, efforts have been put into macrozone definition and characterization. The electron backscatter diffraction (EBSD) technique, widely used for texture analysis, allows for a qualitative macrozone characterization; however, further processing is required to define the boundaries and disorientation spread of each macrozone. Current approaches often use c-axis misorientation criteria, but this can sometimes lead to a large disorientation spread within a macrozone. This article describes the development and application of a computational tool implemented in MATLAB for automatic macrozone identification from EBSD data sets on the basis of a more conservative approach where both the c-axis tilting and rotation are considered. The tool allows for detection of macrozones according to the disorientation angle and density-fraction criteria. The clustering efficiency is validated by pole-figure plots, and the effects of the key parameters defining the macrozone clustering (disorientation and fraction) are discussed. In addition, this tool was successfully applied to both fully equiaxed and bimodal microstructures of titanium forgings.

Advancing analytical electron microscopy methodologies to characterise microstructural features in superalloys

Electron backscatter diffraction (EBSD) generally links crystallographic orientation to the microstructure of crystalline materials. EBSD datasets are now commonly used to identify phases, grains, and their orientations using off-the-shelf software, although substantial additional information may be extracted. Due to the lack of commercially available software, advanced analyses are often done manually and provide only localised information, lacking statistical significance. Here we introduce novel automated methodologies for advanced analyses of microstructural features in Ni-based superalloys. Our methodologies provide additional insights into the characteristics of these features and their underlying physical phenomena. We showcase how to correct wrongly indexed γ/γ’ interface artefacts in combined EBSD and energy-dispersive X-ray spectroscopy (EDS) measurements, how to classify recrystallised grains based on their location, how to assess and visualise grain boundary planes, and how to study the evolution of Σ3 twins during hot deformation. We further demonstrate how phase fractions and grain sizes are more accurately determined in combined EBSD-EDS measurements. The classification of recrystallised grains into different groups enables individual analyses, facilitating the straightforward identification of the underlying recrystallisation mechanism. Our grain boundary plane analysis provides insights into the coherence of Σ3 twins and the potential boundary planes of incoherent Σ3 boundaries. The current paper is a tutorial-style guide for these methodologies. The algorithms are made freely available and, although demonstrated here on Ni-based superalloys, can also be applied to other systems.

A finite element method to calculate geometrically necessary dislocation density: Accounting for orientation discontinuities in polycrystals

Strain gradients have been used to link various microscale deformation phenomena to the mechanical response of a polycrystalline material, revealing sub-crystal deformation structures. The strain gradients are computed in terms of the orientation gradients and then converted to geometrically necessary dislocation densities, a quantity considered important to explain flow stress and strain hardening behaviour. In this study, a unique method has been developed to compute the orientation gradients by finite element method while enforcing orientation continuity inside the grains and allowing sharp gradients at the grain boundaries by a global minimization approach. The method is showcased on an exemplar electron backscatter diffraction datasets of a stainless type of steel. The energy minimization method (Demir et al., 2009) reveals geometrically necessary dislocation densities that are an order of magnitude lower than those calculated using the widely accepted Least-Squares minimization approach (Arsenlis et al., 1999). The proposed approach successfully eliminates sharp orientation gradients at grain boundaries, removing the artificially high dislocation densities near orientation discontinuities that is characteristic to the finite difference-based approaches.

Adaptable physics-based super-resolution for electron backscatter diffraction maps

In computer vision, single-image super-resolution (SISR) has been extensively explored using convolutional neural networks (CNNs) on optical images, but images outside this domain, such as those from scientific experiments, are not well investigated. Experimental data is often gathered using non-optical methods, which alters the metrics for image quality. One such example is electron backscatter diffraction (EBSD), a materials characterization technique that maps crystal arrangement in solid materials, which provides insight into processing, structure, and property relationships. We present a broadly adaptable approach for applying state-of-art SISR networks to generate super-resolved EBSD orientation maps. This approach includes quaternion-based orientation recognition, loss functions that consider rotational effects and crystallographic symmetry, and an inference pipeline to convert network output into established visualization formats for EBSD maps. The ability to generate physically accurate, high-resolution EBSD maps with super-resolution enables high-throughput characterization and broadens the capture capabilities for three-dimensional experimental EBSD datasets.

An automated procedure built on MTEX for reconstructing deformation twin hierarchies from electron backscattered diffraction datasets of heavily twinned microstructures

This paper presents a set of algorithms built on the MTEX and MATLAB graph toolboxes for automatic reconstruction of deformation twin hierarchies from Electron Backscatter Diffraction (EBSD) datasets with a focus on developing methods for heavily twinned microstructures (twin fractions >0.5). The algorithms address key issues arising at large strains, mainly: missing twin relationships, grouping of heavily deformed grain fragments into families of similar orientation originating from a single initial grain, identification of parent fragments for large twin volume fractions, and classification of families having twin relationships with multiple families. To facilitate the development of these algorithms, large-grained ultra-high purity α-Ti deformed in compression along two directions is investigated. Graphs are utilized to handle non-local geometric merging and to represent relationships throughout the reconstruction process. When determining if a grain fragment is from the undeformed microstructure, the combined metrics of the fragment's orientation volume fraction in the initial texture and the directed graph centrality measure of out-closeness (the number of nodes reached in a graph from a given node) are essential. To address automation in reconstructing the sequence of twinning and relating fragments originating from a single grain in the initial microstructure, the twin family tree is formulated as a minimum spanning tree emanating from the initial grain family. A scheme constructing the distances associated with twin relationship comprising the spanning tree is developed, and a novel quasi-directional Prim spanning tree algorithm is used to determine the twin family tree. The procedure is demonstrated to significantly improve the level of automation in reconstructing twin hierarchies in heavily twinned microstructure compared to other methodologies in literature. The procedure can readily be applied to analyses of twinning in metals, as well as provide an approach for routinely extracting twin statistics at larger deformation levels than previously possible. Significantly, the procedure is demonstrated to be capable of identifying third generation twinning in α-Ti microstructures.

Non-acid, alcohol-based electropolishing enables high-quality electron backscatter diffraction characterization of titanium and its alloys: Application to pure Ti and Ti-6Al-4V

This paper conceives an electropolishing sample preparation procedure aimed at characterization of titanium (Ti) and its alloys using electron backscatter diffraction (EBSD). Specifically, it is shown that a single non-acid, ethanol-ethylene glycol-NaCl electrolyte solution can be used to electropolish Ti and its alloys for obtaining high-quality EBSD datasets. As a result, the use of hazardous acids common in standard Ti metallographic preparation procedures, such as hydrofluoric, perchloric, and sulfuric acid, can be circumvented. Moreover, electropolishing Ti with an ethanol-ethylene glycol-NaCl electrolyte is performed at room temperature with low voltage, as opposed to the low temperatures and/or high voltages used when electropolishing Ti in traditional solutions. The utility of the novel procedure is demonstrated on samples of pure α-Ti before and after plastic deformation and on samples of alloy Ti-6Al-4V created by additive manufacturing (AM) in stress-relived and heat-treated conditions. EBSD scans performed on undeformed pure α-Ti had high-quality diffraction patterns, which allowed for large areas to be scanned at fast speeds without sacrificing indexing accuracy. The electropolishing created excellent surfaces on the deformed pure α-Ti sample despite elevated lattice strains and numerous deformation twins in its microstructure. It also allowed for detailed EBSD mapping of fine sub-grain features in AM Ti-6Al-4V despite the alloying additions of aluminum and vanadium, the inhomogeneous AM microstructure, and the different processing conditions. It is anticipated that the major breakthrough achieved in this work will streamline and make safer future metallographic studies of Ti and its alloys.

Estimation of geometrically necessary dislocation density from filtered EBSD data by a local linear adaptation of smoothing splines

An implementation of smoothing splines is proposed to reduce orientation noise in electron backscatter diffraction (EBSD) data, and subsequently estimate more accurate geometrically necessary dislocation (GND) densities. The local linear adaptation of smoothing splines (LLASS) filter has two advantages over classical implementations of smoothing splines: (1) it allows for an intuitive calibration of the fitting versus smoothing trade-off and (2) it can be applied directly and in the same manner to both square and hexagonal grids, and to 2D as well as to 3D EBSD data sets. Furthermore, the LLASS filter calculates the filtered orientation gradient, which is actually at the core of the method and which is subsequently used to calculate the GND density. The LLASS filter is applied on a simulated low-misorientation-angle boundary corrupted by artificial orientation noise (on a square grid), and on experimental EBSD data of a compressed Ni-base superalloy (acquired on a square grid) and of a dual austenitic/martensitic steel (acquired on an hexagonal grid). The LLASS filter leads to lower GND density values as compared to raw EBSD data sets, as a result of orientation noise being reduced, while preserving true GND structures. In addition, the results are compared with those of filters available in theMTEXtoolbox.

Accurate reconstruction of EBSD datasets by a multimodal data approach using an evolutionary algorithm

A new method has been developed for the correction of the distortions and/or enhanced phase differentiation in Electron Backscatter Diffraction (EBSD) data. Using a multi-modal data approach, the method uses segmented images of the phase of interest (laths, precipitates, voids, inclusions) on images gathered by backscattered or secondary electrons of the same area as the EBSD map. The proposed approach then searches for the best transformation to correct their relative distortions and recombines the data in a new EBSD file. Speckles of the features of interest are first segmented in both the EBSD and image data modes. The speckle extracted from the EBSD data is then meshed, and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is implemented to distort the mesh until the speckles superimpose. The quality of the matching is quantified via a score that is linked to the number of overlapping pixels in the speckles. The locations of the points of the distorted mesh are compared to those of the initial positions to create pairs of matching points that are used to calculate the polynomial function that describes the distortion the best. This function is then applied to un-distort the EBSD data, and the phase information is inferred using the data of the segmented speckle. Fast and versatile, this method does not require any human annotation and can be applied to large datasets and wide areas. Besides, this method requires very few assumptions concerning the shape of the distortion function. It can be used for the single compensation of the distortions or combined with the phase differentiation. The accuracy of this method is of the order of the pixel size. Some application examples in multiphase materials with feature sizes down to 1 μm are presented, including Ti-6Al-4 V Titanium alloy, Rene 65 and additive manufactured Inconel 718 Nickel-base superalloys.

Practical application of direct electron detectors to EBSD mapping in 2D and 3D

The use of a direct electron detector for the simple acquisition of 2D electron backscatter diffraction (EBSD) maps and 3D EBSD datasets with a static sample geometry has been demonstrated in a focused ion beam scanning electron microscope. The small size and flexible connection of the Medipix direct electron detector enabled the mounting of sample and detector on the same stage at the short working distance required for the FIB. Comparison of 3D EBSD datasets acquired by this means and with conventional phosphor based EBSD detectors requiring sample movement showed that the former method with a static sample gave improved slice registration. However, for this sample detector configuration, significant heating by the detector caused sample drift. This drift and ion beam reheating both necessitated the use of fiducial marks to maintain stability during data acquisition.

Segmentation of 3D EBSD data for subgrain boundary identification and feature characterization

Subgrain structures formed during plastic deformation of metals can be observed by electron backscatter diffraction (EBSD) but are challenging to identify automatically. We have adapted a 2D image segmentation technique, fast multiscale clustering (FMC), to 3D EBSD data using a novel variance function to accommodate quaternion data. This adaptation, which has been incorporated into the free open source texture analysis software package MTEX, is capable of segmenting based on subtle and gradual variation as well as on sharp boundaries within the data. FMC has been further modified to group the resulting closed 3D segment boundaries into distinct coherent surfaces based on local normals of a triangulated surface. We demonstrate the excellent capabilities of this technique with application to 3D EBSD data sets generated from cold rolled aluminum containing well-defined microbands, cold rolled and partly recrystallized extra low carbon steel microstructure containing three magnitudes of boundary misorientations, and channel-die plane strain compressed Goss-oriented nickel crystal containing microbands with very subtle changes in orientation.

Near-liquidus growth of feldspar spherulites in trachytic melts: 3D morphologies and implications in crystallization mechanisms

The nucleation and growth processes of spherulitic alkali feldspar have been investigated in this study through X-ray microtomography and electron backscatter diffraction (EBSD) data. Here we present the first data on Shape Preferred Orientation (SPO) and Crystal Preferred Orientation (CPO) of alkali feldspar within spherulites. The analysis of synchrotron X-ray microtomography and EBSD datasets allowed us to study the morphometric characteristics of spherulites in trachytic melts in quantitative fashion, highlighting the three-dimensional shape, preferred orientation, branching of lamellae and crystal twinning, providing insights about the nucleation mechanism involved in the crystallization of the spherulites. The nucleation starts with a heterogeneous nucleus (pre-existing crystal or bubble) and subsequently it evolves forming “bow tie” morphologies, reaching radially spherulitic shapes in few hours. Since each lamella within spherulite is also twinned, these synthetic spherulites cannot be considered as single nuclei but crystal aggregates originated by heterogeneous nucleation. A twin boundary may have a lower energy than general crystal–crystal boundaries and many of the twinned grains show evidence of strong local bending which, combined with twin plane, creates local sites for heterogeneous nucleation. This study shows that the growth rates of the lamellae (10− 6–10− 7 cm/s) in spherulites are either similar or slightly higher than that for single crystals by up to one order of magnitude. Furthermore, the highest volumetric growth rates (10− 11–10− 12 cm3/s) show that the alkali feldspar within spherulites can grow fast reaching a volumetric size of ~ 10 μm3 in 1 s.

Austenite–martensite/bainite orientation relationship: characterisation parameters and their application

Transformations from austenite to martensite or bainite in ferrous alloys have great technological importance, but some aspects remain elusive. The orientation relationship (OR), morphology and habit plane can vary considerably from one system to another. Much published work considers these OR in terms of their variation from named relationships such as Kurdjumov–Sachs and Nishiyama–Wassermann. We discuss here, instead, the use of a set of angular parameters based on the classic work of Kurdjumov and Sachs in the 1930s, that provide a unified and elegant description facilitating extraction and detailed statistical treatment of OR from large electron backscatter diffraction datasets, as well as straightforward comparison with named OR and with the predictions from the phenomenological theory. Spatially correlated mappings of OR parameters obtained using this approach suggest that the observed variations in OR are related to the martensitic morphology rather than being an experimental artefact.

Boundary identification in EBSD data with a generalization of fast multiscale clustering

Electron backscatter diffraction (EBSD) studies of cellular or subgrain microstructures present problems beyond those in the study of coarse-grained polycrystalline aggregates. In particular, identification of boundaries delineating some subgrain structures, such as microbands, cannot be accomplished simply with pixel-to-pixel misorientation thresholding because many of the boundaries are gradual transitions in crystallographic orientation. Fast multiscale clustering (FMC) is an established data segmentation technique that is combined here with quaternion representation of orientation to segment EBSD data with gradual transitions. This implementation of FMC addresses a common problem with segmentation algorithms, handling data sets with both high and low magnitude boundaries, by using a novel distance function that is a modification of Mahalanobis distance. It accommodates data representations, such as quaternions, whose features are not necessarily linearly correlated but have known distance functions. To maintain the linear run time of FMC with such data, the method requires a novel variance update rule. Although FMC was originally an algorithm for two-dimensional data segmentation, it can be generalized to analyze three-dimensional data sets. As examples, several segmentations of quaternion EBSD data sets are presented.

Using cross‐correlation for automated stitching of two‐dimensional multi‐tile electron backscatter diffraction data

A method for automatically aligning consecutive data sets of large, two-dimensional multi-tile electron backscatter diffraction (EBSD) scans with high accuracy was developed. The method involved first locating grain and phase boundaries within search regions containing overlapping data in adjacent scan tiles, and subsequently using cross-correlation algorithms to determine the relative position of the individual scan tiles which maximizes the fraction of overlapping boundaries. Savitzky-Golay filtering in two dimensions was used to estimate the background, which was then subtracted from the cross-correlation to enhance the peak signal in samples with a high density of interfaces. The technique was demonstrated on data sets with a range of interface densities. The equations were implemented as enhancements to a recently published open source code for stitching of multi-tile EBSD data sets.

AnyStitch: a tool for combining electron backscatter diffraction data sets

Recent advances in electron backscatter diffraction equipment and software have permitted increased data acquisition rates on the order of hundreds of points per second with additional increases in the foreseeable future likely. This increase in speed allows users to collect data from statistically significant areas of samples by combining beam-control scans and automated stage movements. To facilitate data analysis, however, the individual tiles must be combined, or stitched, into a single data set. In this paper, we describe a matlab(®) (The Mathworks, Inc., Natick, MA, USA) program to facilitate stitching of electron backscatter diffraction data. The method offers users a wide range of controls for tile placement including independent overlaps for horizontal and vertical tiles and also includes a parameter to account for systematic stage positioning errors or improperly calibrated scan rotation. The code can stitch data collected on either square or hexagonal grids and contains a function to reduce the resolution of square grid data if the resulting file is too large (or has too many grains) to be opened by the analysis software. The software was primarily written to work with TSL(®) OIM™ data sets and includes a function to quickly read compressed *.osc files into a variable in the matlab(®) workspace as opposed to using slower, text-reading functions. The output file is in *.ang format and can be opened directly by TSL(®) OIM™ Analysis software. A set of functions to facilitate stitching of text-based *.ctf files produced by Oxford Instruments HKL systems are also included. Finally, the code can also be used to combine *.tif images to produce a montage. The source code, a graphical user interface and a compiled version of the software was made available in the online version of this paper.

Visualization of grain subdivision by analysing the misorientations within a grain using electron backscatter diffraction

The misorientation relative to the average orientation of a grain and the point-to-point relative misorientation along a line across a moderately cold deformed grain, calculated from an electron backscatter diffraction (EBSD) dataset, are analysed in detail by visualizing both the misorientation angle and the misorientation axis. The significance of monitoring the misorientation axis is illustrated by an example of a grain subdivided into a misorientation band structure. A new technique to visualize the subdivision structure by assigning colours to misorientations in such a way that the contrast is maximized within a grain is introduced and discussed. Furthermore, some methods for grain boundary reconstruction from EBSD datasets are compared with the map of the confidence index in order to provide a validation of the accuracy of these methods.