Correction of Scanning Electron Microscope Imaging Artifacts in a Novel Digital Image Correlation Framework

Area of Science:

• Materials Science
• Mechanical Engineering
• Imaging Science

Background:

• Digital Image Correlation (DIC) combined with Scanning Electron Microscopy (SEM) offers high-resolution displacement data.
• SEM imaging artifacts like spatial distortion, drift, and scan line shifts can significantly reduce measurement accuracy.
• Accurate deformation measurement is crucial for understanding material behavior under stress.

Purpose of the Study:

• To develop a unified framework for correcting dominant SEM imaging artifacts.
• To integrate artifact correction into the Integrated DIC (IDIC) method for enhanced accuracy.
• To validate the proposed framework using virtual and real SEM experiments.

Main Methods:

• Extended Integrated DIC (IDIC) with hierarchical mapping functions to model imaging process-mechanics interaction.
• Developed a new IDIC formulation to simultaneously measure artifact fields and mechanical deformations.
• Conducted virtual experiments to assess the impact of noise and regularization on artifact correction.

Main Results:

• The proposed method accurately corrects spatial distortion, drift distortion, and scan line shifts in SEM images.
• Mechanical displacement errors were within the typical DIC accuracy range (under 5% noise).
• Ignoring artifacts led to errors exceeding 4 pixels, highlighting the necessity of the correction framework.

Conclusions:

• The developed framework accurately captures SEM artifact fields, significantly improving the reliability of DIC measurements.
• The methodology demonstrates robustness and accuracy in both virtual and real SEM experiments.
• This approach enhances the precision of full-field displacement and strain analysis in SEM-based studies.