Materials Science Forum Vols. 702-703

Abstract: Our recent work on EBSD-based characterization of incommensurate 7M modulated martensite in a polycrystalline Ni₅₀Mn₃₀Ga₂₀ alloy were summarized. The 7M martensitic plates were revealed to be self-accommodated in colonies, where each colony consisted of four types of variants that were twin related. All the pairs of variants can be categorized into three twinning modes, i.e. type-I, type-II and compound twins. The twin interface planes were in coincidence with the respective twinning planes. Using the measured orientations of adjacent martensitic variants, the orientations of parent austenite grains were calculated under the assumed orientation relationships for the austenite to martensite transformation. The energetically favorable orientation relationship between austenite and martenstie for the martensitic transformation was identified to be the Pitsch relation.

Abstract: A new method for reconstructing a High Resolution Orientation Distribution Function (HRODF) from X-ray diffraction data is presented. It is shown that the method is capable of accommodating very localized features, e.g. sharp peaks from recrystallized grains on a background of a texture component from the deformed material. The underlying mathematical formalism supports all crystallographic space groups and reduces the problem to solving a (large) set of linear equations. An implementation on multi-core CPUs and Graphical Processing Units (GPUs) is discussed along with an example on simulated data.

Abstract: For a wide variety of model calculations a hypothetical 3D microstructure is required as input. Although experimental data are frequently used to this purpose, 3D microstructures are difficult to measure experimentally. In order to circumvent these difficulties, a virtual microstructure generator to simulate a specific 3D material microstructure is proposed. Such a virtual microstructure could serve as input for different types of models, would allow a faster model prototyping, would help to explore the boundary conditions of models and reduces the number of unnecessary experimental measurements. In the current paper, the method to generate and to control the grain size distribution as well as texture are discussed.

Abstract: Due to crystal and sample symmetry, texture data can be presented uniquely in a smaller domain of Euler box or Rodrigues space. As these sub-domains are obtained by different criteria, a one-to-one relation does not always exist for conversion between Euler and Rodrigues coordinates. This work presents a methodology for finding the common region between the Euler sub-space and Rodrigues fundamental zone for the case of cubic crystal and orthotropy sample symmetry, and its size is found to be 0.0864068.

Abstract: Electron backscatter diffraction (EBSD) has become the preferred technique for characterizing the crystallographic orientation of individual grains in polycrystalline microstructures due to its ability to rapidly measure orientations at specific points in the microstructure at resolutions of approximately 20-50nm depending on the capabilities of the scanning electron microscope (SEM) and on the material being characterized. Various authors have studied the angular resolution of the orientations measured using automated EBSD. These studies have stated values ranging from approximately 0.1° to 2° [1-6]. Various factors influence the angular resolution achievable. The two primary factors are the accuracy of the detection of the bands in the EBSD patterns and the accuracy of the pattern center (PC) calibration. The band detection is commonly done using the Hough transform. The effect of varying the Hough transform parameters in order to optimize speed has been explored in a previous work [6]. The present work builds upon the earlier work but with the focus towards achieving the best angular resolution possible regardless of speed. This work first details the methodology used to characterize the angular precision then reports on various approaches to optimizing parameters to improve precision.

Abstract: As EBSD techniques improve, researchers are rapidly gaining access to quantities of high-caliber information previously unavailable. However, these benefits bring their own drawbacks. Engineers must either learn to cope with large amounts of data, or they must be more selective about which data is captured. In either case, machine learning techniques may play an important role. Data mining techniques can be used to extract knowledge from large databases, while other machine learning methods enable the identification of critical features, and the efficient search for such features at the data acquisition phase. One particular application of these techniques involves the investigation of fracture and fatigue mechanisms. Methods are required for finding and recording critical event inception. The development of in-situ test equipment, and high-resolution microscopy techniques (such as high-resolution EBSD: HREBSD) have placed invaluable tools into the hands of researchers. Nevertheless, practical considerations limit the volume of material that can be carefully monitored during a given testing regime. Machine learning techniques offer a promising framework for enhancing efficiency in the search for critical events. This paper presents initial efforts to develop an intelligent microscopy environment for EBSD users based upon machine learning methods. The test bed for the study will include ductility studies in magnesium, exploiting recent advances by the authors in the area of HREBSD.

Abstract: There are two opposing theories regarding the nature of aligned dislocation boundaries generated during plastic deformation of FCC metals: (i) they are oriented along crystallographic planes, and (ii) their alignment is dictated by the macroscopic stress state during plastic deformation. 3D crystallographic orientation data were collected on a volume containing microbands in commercial purity aluminum, and 3D boundaries were reconstructed. Both types of alignment were found in local surface features.

Abstract: Measurement of local strains in poly-crystalline materials, subjected to relatively large plastic deformation, is a challenging problem. In this paper we report a novel approach for the calculation of local strains at microscopic levels using Electron Backscattered Diffraction measurements, and subsequent use of digital image processing and a simple algorithm. Identical grains, of a fully recrystallized commercial AA1050 sheet, were indexed before and after a tensile strain of 0.262. Normal and shear strains were calculated by estimating the changes in grain shape and in plane rotation. An excellent correlation was obtained between measured in-grain misorientation developments and the estimated in-grain von-Mises equivalent strains.

Abstract: The relevance of EBSD-based investigations for statements on the macroscopic or mesoscopic behavior of materials is critically relying on the statistical representativeness of the data. Particularly, the statistical reliability of the EBSD-based results (e.g. texture, phase fraction or grain size) remains an open question since the areas observed by the EBSD technique are quite small compared to XRD techniques. It has already been shown that covering larger areas and probing more grains with the help of large step sizes is beneficial in terms of representativeness [1]. On the other hand, small step sizes are beneficial in terms of grain reconstruction and data clean-up. However, step sizes significantly smaller than the average grain size of the material lead to either covered areas or number of probed grains being too small to be representative or to very large datasets and correspondingly long measurement times. In this contribution, the benefits of a new mapping technique [1] that joins the advantages of large and small step size measurements will be demonstrated. The representativeness of the EBSD datasets obtained by classical and this new mapping techniques were compared by calculating the pole figure symmetries of a TRIP steel. The results show that the proposed mapping technique significantly improves the reliability and representativeness of EBSD-based texture measurements.

Abstract: The behaviour of a coating is directly related to its microstructure as well as the crystal structure and composition of different phases that are formed in the deposition process. A comprehensive study of the microstructure and local phase assembly in coatings would help in arriving at structure-property correlations that can help understand the coating behaviour. SEM-based diffraction techniques provide a simple method for obtaining local crystallographic information without the need for complex synchrotron sources. In this study, we present a method for characterization of coatings using SEM-based microdiffraction which involves the combined use of the EDS and EBSD capabilities, citing a Ti-Al-Cr-N multilayer coating as an example. The different layers in the coating were observed and the electron beam focused in each region to first obtain Energy Dispersive Spectra and electron backscatter patterns (EBSPs). The elemental constituents were identified from EDS maps and used to shortlist the possible phases present. The diffraction pattern for each possible phase was then calculated and the EBSPs of the observed and calculated patterns were compared for the closest match. The identified phase was then used as an input to set up EBSD scans across the coating. A qualitative picture of the compositional variation in multilayer coatings was obtained that could help in arriving at the exact stoichiometry of the different layers. Hence, SEM-based microdiffraction allows identification of local crystallographic phases and composition, permitting detailed microstructural studies that would find special application in the study of coatings.