Robust methodology for the EBSD local misorientation analysis of surface cold work

Area of Science:

• Materials Science
• Surface Engineering
• Crystallography

Background:

• Cold work and its depth are critical in surface engineering for metallic materials.
• Surface hardening techniques induce significant cold work, affecting material properties.
• Accurate quantification of cold work is essential for predicting performance.

Purpose of the Study:

• To develop and detail a methodology for quantifying cold work depth and magnitude in surface-hardened materials.
• To analyze electron backscattered diffraction (EBSD) image datasets for reliable cold work estimation.
• To investigate the influence of scanning electron microscope (SEM) and post-acquisition parameters on EBSD analysis outcomes.

Main Methods:

• Utilized electron backscattered diffraction (EBSD) image datasets from surface-hardened nickel-based superalloy single crystals.
• Employed local misorientation analysis to establish estimates of cold work depth and magnitude.
• Systematically varied scanning electron microscope (SEM) acquisition and post-acquisition analysis parameters to assess their impact.

Main Results:

• Successfully established a reliable methodology for estimating cold work depth and magnitude from EBSD data.
• Detailed the effects of various SEM acquisition and post-acquisition parameters on the accuracy of cold work analysis.
• Published the Python script used for the analysis, ensuring reproducibility and adaptability.

Conclusions:

• The presented methodology provides accurate quantification of cold work in surface-hardened nickel-based superalloys.
• The findings highlight the importance of optimizing SEM and post-acquisition parameters for reliable EBSD analysis.
• The methodology and script are adaptable for diverse surface-hardened materials and techniques, advancing surface engineering research.