Adaptive Drive as a Control Strategy for Fast Scanning in Dynamic Mode Atomic Force Microscopy.

Area of Science:

• Materials Science
• Nanotechnology
• Surface Science

Background:

• Atomic Force Microscopy (AFM) provides nanoscale resolution imaging under physiological conditions.
• Dynamic Mode AFM reduces tip-sample interaction but introduces a trade-off between speed, topography accuracy, and force.
• Parachuting artifacts, particularly in steep/deep sample features, degrade topography reconstruction at higher scanning speeds.

Purpose of the Study:

• To develop and present a novel adaptive driving strategy for AFM.
• To mitigate parachuting artifacts in dynamic mode AFM imaging.
• To improve the accuracy of topography reconstruction in AFM.

Main Methods:

• Implementation of an adaptive driving strategy as an add-on for commercial AFM systems.
• Testing the proposed method on grid samples to evaluate its performance.
• Analysis of topography reconstruction quality and artifact reduction.

Main Results:

• The adaptive driving strategy effectively reduces parachuting artifacts.
• Enhanced nano-imaging quality was observed on tested grid samples.
• The method demonstrates improved topography reconstruction, especially in challenging sample topographies.

Conclusions:

• The proposed adaptive driving strategy offers a practical solution to parachuting artifacts in AFM.
• This technique enhances the reliability and accuracy of nanoscale imaging.
• The method is easily integrable with existing commercial AFM systems.