List of Contributors. 1. The Development of Automated Diffraction in Scanning and Transmission Electron Microscopy D.J. Dingley. 2. Theoretical Framework for Electron Backscatter Diffraction V. Randle. 3. Representation of Texture in Orientation Space K. Rajan. 4. Rodriques-Frank Representations of Crystallographic Texture K. Rajan. 5. Fundamentals of Automated EBSD S.I. Wright. 6. Studies on the Accuracy of Electron Backscatter Diffraction Measurements M.C. Demirel, B.S. El-Dasher, B.L. Adams, A.D. Rollett. 7. Phase Identification Using Electron Backscatter Diffraction in the Scanning Electron Microscope J.R. Michael. 8. Three-Dimensional Orientation Imaging D.J. Jensen. 9. Automated Electron Backscatter Diffraction: Present State and Prospects R.A. Schwarzer. 10. EBSD: Buying a Systems A. Eades. 11. Hardware and Software Optimization for Orientation Mapping and Phase Identification P.P. Camus. 12. An Automated EBSD Acquisition and Processing System P. Rolland, K.G. Dicks. 13. Advanced Software Capabilities for Automated EBSD S.I. Wright, D.P. Field, D.J. Dingley. 14. Strategies for Analysis of EBSD Datasets W.E. King, J.S. Stolken, M. Kumar, A.J. Schwartz. 15. Structure-Property Relations: EBSD-Based Materials-Sensitive Design B.L. Adams, B.L. Henrie, L.L. Howell, R.J. Balling. 16. Use of EBSD Data in Mesoscale Numerical Analyses R. Becker, H. Weiland. 17. Characterization of Deformed Microstructures D.P. Field, H. Weiland. 18. Anisotropic Plasticity Modeling Incorporating EBSD Characterization of Tantalum and Zirconium J.F. Bingert, G.C. Kaschner, T.A. Mason, P.J. Maudlin, G.T. Gray III. 19. Measuring Strains Using Electron Backscatter Diffraction A.J. Wilkinson. 20. Mapping Residual Plastic Strain in Materials Using Electron Backscatter Diffraction E.M. Lehockey, Yang-Pi Lin, O.E. Lepik. 21.EBSD Contra TEM Characterization of a Deformed Aluminum Single Crystal Xiaoxu Huang, D.J. Jensen. 22. Continuous Recrystallization and Grain Boundaries in a Superplastic Aluminum Alloy T.R. McNelley. 23. Analysis of Facets and Other Surfaces Using Electron Backscatter Diffraction V. Randle. 24. EBSD of Ceramic Materials J.K. Farrer, J.R. Michael, C.B. Carter. 25. Grain Boundary Character Based Design of Polycrystalline High Temperature Superconducting Wires A. Goyal. Index.

Electron Backscatter Diffraction in Materials Science

Progress in Materials Science Vol. 9. Edited by Dr. Bruce Chalmers. (Incorporating “Progress in Metal Physics”, Volumes 1–8.) Pp. 389. (London and New York: Pergamon Press, 1961.) 120s. net; 20 dollars.

Progress in Materials Science

Image distortions in SEM and their influences on EBSD measurements.

Electron imaging with an EBSD detector.

Electron backscatter diffraction (EBSD), when employed as an additional characterization technique to a scanning electron microscope (SEM), enables individual grain orientations, local texture, point-to-point orientation correlations, and phase identification and distributions to be determined routinely on the surfaces of bulk polycrystals. The application has experienced rapid acceptance in metallurgical, materials, and geophysical laboratories within the past decade (Schwartz et al. 2000) due to the wide availability of SEMs, the ease of sample preparation from the bulk, the high speed of data acquisition, and the access to complementary information about the microstructure on a submicron scale. From the same specimen area, surface structure and morphology of the microstructure are characterized in great detail by the relief and orientation contrast in secondary and backscatter electron images, element distributions are accessed by energy dispersive spectroscopy (EDS), wavelength dispersive spectroscopy (WDS), or cathodoluminescence analysis, and the orientations of single grains and phases can now be determined, as a complement, by EBSD.

Present State of Electron Backscatter Diffraction and Prospective Developments

https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1524&context=facpub

Mapping the mesoscale interface structure in polycrystalline materials.

Microstructure controls the properties of most useful materials. Thus an ability to control microstructure through the processing of materials is a key to optimization of materials performance. Most materials are polycrystalline and their grain structure is a very important aspect of their microstructure. Thanks to their complexity there is a great variety of grain boundary types even in relatively isotropic materials such as the cubic metals. Simply describing the crystallography requires five (macroscopic) parameters (e.g. disorientation and inclination). Evidently, acquiring a knowledge of the variation of properties such as energy and mobility as a function of grain boundary type would be of great value in predicting properties and optimizing processing. This paper outlines the methods being employed to extract such properties from the geometry and crystallography of triple junctions between grain boundaries.

http://mimp.materials.cmu.edu/rohrer/papers/2001_12.pdf

Grain Boundary Property Determination through Measurement of Triple Junction Geometry and Crystallography

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1431927600014471

Extraction of Grain Boundary Energies from Triple Junction Geometry

A new experimental approach to the quantitative characterization of polycrystalline microstructure by scanning electron microscopy is described. Combining automated electron backscattering diffraction with conventional scanning contrast imaging and with calibrated serial sectioning, the new method (mesoscale interface mapping system) recovers precision estimates of the 3D idealized aggregate function G ( x ). This function embodies a description of lattice phase and orientation (limiting resolution∼1°) at each point x (limiting spatial resolution∼100 nm), and, therefore, contains a complete mesoscale description of the interfacial network. The principal challenges of the method, achieving precise spatial registry between adjacent images and adequate distortion correction, are described. A description algorithm for control of the various components of the system is also provided.

/pdf/mapping-the-mesoscale-interface-structure-in-polycrystalline-4o9buyuhwb.pdf

Mapping the Mesoscale Interface Structure in Polycrystalline Materials

A new algorithm based on scale-space median and gabor filtering is used to find boundaries in electron microscopy images under noise and low contrast. Boundary information from different scales are fused to find triple junctions and dihedral angles that are of use in material science. The proposed algorithm has been tested on various electron microscopy images and has been shown to be robust to changing imaging conditions, noise and contrast.

S. Ozdemir

Papers

Mapping the mesoscale interface structure in polycrystalline materials.

Grain Boundary Property Determination through Measurement of Triple Junction Geometry and Crystallography

Extraction of Grain Boundary Energies from Triple Junction Geometry

Mapping the Mesoscale Interface Structure in Polycrystalline Materials

Scale-space median and gabor filtering for boundary detection in electron microscopy images