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Area of Science:

  • Metrology
  • Surface science
  • Scanning probe microscopy

Background:

  • Maintaining sample levelness is critical in scanned probe microscopy for accurate measurements.
  • Sample tilt introduces errors in feature dimensions such as linewidth and step height.
  • Current line-by-line analysis for background subtraction is time-consuming and may not fully correct tilt effects.

Purpose of the Study:

  • To propose a novel coordinate transformation method for correcting sample tilts in scanned probe measurements.
  • To develop a method that mathematically derives and corrects tilts around x, y, and z axes.
  • To produce a leveled image simultaneously for enhanced data analysis.

Main Methods:

  • A coordinate transformation method is introduced.
  • A new coordinate system is established based on sample inclination and axis translations.
  • The method mathematically derives and corrects all tilts, leveling the image.

Main Results:

  • The coordinate transformation method was tested using simulated images.
  • Feature dimensions (width, height, sidewall angle, pitch) were calculated and compared.
  • The proposed method demonstrated advantages over existing techniques in correcting tilts and improving accuracy.

Conclusions:

  • The proposed coordinate transformation method effectively corrects sample tilts in scanned probe microscopy.
  • This leveling approach enhances the accuracy of critical feature dimension measurements.
  • The method offers a more efficient and accurate alternative to traditional line-by-line analysis for tilt correction.