Automatic Texture Alignment by Optimization Method.

Area of Science:

• Materials Science and Engineering
• Crystallography
• Computational Materials Science

Background:

• Electron backscatter diffraction (EBSD) is vital for microstructure analysis in materials science.
• Accurate texture assessment via pole figure diagrams requires precise alignment of sample axes with manufacturing directions.
• Manual alignment and postprocessing in EBSD are time-consuming and prone to operator error.

Purpose of the Study:

• To develop an automated method for calculating and correcting sample axis deviations in EBSD measurements.
• To objectively define and achieve axis symmetry in pole figure diagrams.
• To reduce operator dependency and improve the efficiency of texture analysis.

Main Methods:

• Utilizing the contour of crystal orientations to calculate deviations from ideal alignment.
• Implementing an objective function to define pole figure diagram symmetry.
• Employing minimization algorithms for symmetric alignment of textures.
• Validating the method with experimental textures from extruded profiles and synthetic data.

Main Results:

• The developed method accurately calculates deviations in sample orientation.
• Objective function-based minimization successfully aligns pole figure diagrams symmetrically.
• The technique demonstrates excellent performance for misalignments up to 5°, typical in careful manual setups.
• Effective results were achieved even for deviations up to 15°, showcasing robustness.

Conclusions:

• The proposed automated method offers a significant improvement over manual postprocessing in EBSD texture analysis.
• Accurate texture characterization and prediction of material anisotropy are enhanced by this objective alignment approach.
• This technique is broadly applicable to various crystalline materials and experimental conditions, improving reliability and efficiency.