unDrift: A versatile software for fast offline SPM image drift correction

Area of Science:

• Surface science
• Materials science
• Nanotechnology

Background:

• Scanning probe microscopy (SPM) is crucial for surface and interface analysis in physics and chemistry.
• Thermal drift is a significant artifact in SPM, distorting data and complicating analysis, especially for long image series.
• Existing offline drift correction methods are often time-consuming and tedious.

Purpose of the Study:

• To develop and present unDrift, an easy-to-use software for rapid and accurate drift correction of SPM images.
• To provide efficient offline drift correction solutions for SPM data analysis.
• To enable reliable analysis of extensive SPM image datasets.

Main Methods:

• unDrift employs three algorithms to determine drift velocity from consecutive SPM images.
• Algorithms include semi-automatic analysis of periodic structure distortion and automatic or manual evaluation of stationary feature movement.
• Correction can be performed without additional reference data or overlapping scan areas.

Main Results:

• unDrift successfully corrects SPM images even with high drift velocities, partial data usability, or weak contrast.
• The semi-automatic algorithm effectively corrects drift in long series of hundreds of images, demonstrated on calcite-water interface data.
• The software offers versatile drift correction capabilities for various SPM data challenges.

Conclusions:

• unDrift provides a fast, reliable, and user-friendly solution for SPM image drift correction.
• The software enhances the efficiency of analyzing extensive SPM datasets, overcoming limitations of existing tools.
• unDrift's algorithms are robust and applicable to challenging datasets, improving data quality and interpretability.