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Atomic Force Microscopy

Atomic Force Microscopy

Atomic force microscopy (AFM) is a type of scanning probe microscopy that can analyze topographic details of various specimens like ceramics, glass, polymers, and biological samples. AFM offers over 1000 times more resolution than the optical imaging system. Images generated from AFM are three-dimensional surface profiles, offering an advantage over the flat, two-dimensional images from other imaging techniques.
The AFM Probe
The probe is regarded as the heart of any AFM setup and comprises the...

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Height drift correction in non-raster atomic force microscopy.

Travis R Meyer¹, Dominik Ziegler², Christoph Brune³

¹Department of Mathematics, University of California Los Angeles, Los Angeles, CA 90095, USA.

Ultramicroscopy

|December 4, 2013

Summary

This summary is machine-generated.

This study introduces a new method for drift correction in scanning probe microscopy using self-intersecting scan paths. This approach accurately distinguishes drift from topography, improving data reliability.

Keywords:

Atomic force microscopy Drift correction Non-raster scan Self-intersecting scan

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Area of Science:

Surface science
Microscopy techniques
Metrology

Background:

Drift is a common artifact in scanning probe microscopy (SPM), particularly in non-raster scanning modes.
Conventional drift correction methods, like polynomial subtraction, can introduce artifacts due to sample tilt or complex topography.
Accurate drift correction is crucial for reliable nanoscale measurements and imaging.

Purpose of the Study:

To develop a novel method for detecting and correcting drift in non-raster scanning probe microscopy.
To overcome limitations of existing methods that are susceptible to topographic artifacts.
To provide a quantitative measure for assessing drift correctability.

Main Methods:

Utilizing self-intersecting scan paths to differentiate between drift and topographic features.
Reconstructing drift by analyzing height differences at repeatedly scanned positions.
Introducing a fitness function to evaluate the correctability of drift for various scan shapes.

Main Results:

Demonstrated that a minimal number of self-intersections are sufficient for robust drift correction.
Successfully distinguished drift from sample topography, reducing artifacts.
Developed a quantitative fitness function for drift correctability assessment.

Conclusions:

The proposed method offers automatic and reliable drift correction for non-raster SPM.
Self-intersecting scan paths provide a robust solution to artifacts caused by topography.
The developed fitness function aids in optimizing scan strategies for drift-prone samples.