Investigation on blind tip reconstruction errors caused by sample features.

Area of Science:

• Nanotechnology
• Surface Science
• Microscopy

Background:

• Accurate nanoscale surface measurements using atomic force microscopy (AFM) depend on precise 3D tip shape knowledge.
• Blind tip reconstruction (BTR) methods can introduce significant errors if the tip characterizer is unsuitable.

Purpose of the Study:

• To investigate the error sources in Villarrubia's blind tip reconstruction (BTR) method.
• To establish conditions for precise tip reconstruction in AFM.

Main Methods:

• Conducted a series of simulation experiments using a conical model to analyze BTR errors.
• Developed a local error model for BTR based on simulation results.
• Proposed simulated ideal structures and their corresponding real samples for BTR validation.

Main Results:

• Precise tip reconstruction necessitates a tip characterizer with a cone angle smaller than the tip's.
• Reconstruction errors decrease with decreasing tip cone angle and increase linearly with sample radius of curvature.
• For sharp and blunt tips, the tip characterizer radius of curvature must be less than 5 nm.

Conclusions:

• The established local error model quantitatively agrees with simulation results, with a maximum deviation of 1.22 nm.
• The study provides guidelines for selecting appropriate tip characterizers to improve BTR accuracy.
• Proposed ideal structures are suitable for validating BTR methods.