Data Presentation Options - Postprocessing

Flexible Measurement Result Visualization

The analyst often faces the challenge of how to present data in a way that material properties of interest can easily be assessed. The ESPRIT software suite for EBSD offers a large number of data representation tools to fulfill that need.

Subset selection

ESPRIT provides the analyst with the option to create data subsets using different criteria, allowing to focus on specific features. Subset selections can be applied to many of the data and the presentation options described on this page: maps, histograms, pole figure and phase list. Subsets can be processed using multiple operations, among them union, subtraction, intersection and expansion. Masks can also be used.

Stainless steel pattern quality map

Pattern quality map

This is an important tool for judging the quality of a measurement. Pattern quality is influenced by acquisition parameters, sample properties; for example phases, boundaries, lattice strain and also by sample preparation. The pattern quality, sharpness of the Kikuchi pattern, at each point of the map is brightness coded to produce a gray scale image. These images are useful as a base for overlaying with other types of maps, as they show microstructural features like grain boundaries.

Stainless steel, pattern quality overlaid with phase map: ferrite (red), austenite (blue), titanium nitride (green), titanium sulfide (yellow)

Phase map

All identified phases are displayed in a color-coded phase distribution map.

High resolution pole figure

Pole figures

Pole figures are one of the most common representation tools for orientation data. They show the distributions of the selected poles {hkl} considering all orientation measurements. Pole figures provide important information on strength of texture and also on which texture components are dominant. ESPRIT for EBSD generates pole figures and their corresponding diffraction sphere (viewed in 3D) in high resolution and with unprecedented speed.

Inverse pole figures

Inverse pole figures (IPF)

While pole figures display crystal orientations with reference to the stage coordinate system, the IPFs describe a chosen stage system axis as a crystallographic vector. Since there are many symmetry-equivalent vectors, the IPFs are reduced to the symmetry-specific sub-spaces (as shown in the figure on the right).

ODF space visualization for a gold film deposited on a silicon wafer

Orientation distribution function

2D cuts and 3D visualization of the ODF space, using modern Open-GL technology for fast and interactive display.

Stainless steel, pattern quality map overlaid with the IPFX map

IPF map

An IPF map combines the locally detected orientation with the crystallographic description of a single reference direction. The color coding is scaled to the reduced size of the IPF.

Grain Average Misorientation maps showing the “accumulation of deformation” inside the ARMCO steel grains at different stages of the in-situ tensile testing experiment; colors show orientation changes from 0 to 7 degrees

Euler map
An Euler map displays the detected orientation at each point on the basis of the Euler angles which are encoded in RGB.

Grain analysis
Supports detection of grains using misorientation and size criteria, ∑3 boundaries can be ignored if desired. Grains can be analyzed with respect to shape, size and main axis inclination (in case of elongated grains). Detected grain maps can be produced with the grains in random colors.

Also included are misorientation distribution analysis features. A misorientation profile along a line as well as a misorientation distribution histogram can be calculated. Misorientation maps can be displayed in form a grain average misorientation map, a kernel average misorientation map and reference misorientation map.

Texture components
ESPRIT for EBSD supports the generation of texture component maps, allowing the definition of texture components and their spread from an "ideal" orientation using a rainbow palette. This feature can also be used for the creation of subsets.