Scientific instrument image representing atomic force microscopy surface analysis

AFM guide

AFM roughness is only meaningful after the surface is prepared correctly.

Plane leveling, line correction and scan-size selection can change Sa and Sq enough to reverse a materials comparison.

Sa

Mean absolute height deviation.

Sq

Root-mean-square height.

Scale

Scan area and spatial sampling.

Evidence summary

Evidence summary

Report AFM roughness only after checking tip and feedback artifacts, documenting leveling and line correction, defining the region and scale, and comparing multiple representative scans. Sa or Sq without preprocessing and scan-size context is not a reproducible surface claim.

Key takeaways

  1. 01Preserve the raw height map before flattening or line correction.
  2. 02Show how plane removal changes Sa and Sq.
  3. 03Compare equivalent scan sizes, pixel densities and regions.
  4. 04Inspect tip convolution, streaks, drift and feedback artifacts before statistics.
Scientific instrument image representing atomic force microscopy surface analysis
Editorial instrument image. AFM roughness must be calculated from the original calibrated height map with documented corrections.

Reject artifacts before calculating roughness

Repeated features, streaks, abrupt line offsets and feedback oscillations can dominate surface statistics. Review trace and retrace where available and inspect line profiles in both scan directions.

  • Look for tip duplication.
  • Check edge streaks and missing lines.
  • Review feedback and scan-speed context.

Document leveling as part of the result

Plane and line corrections are model choices. Compare the raw, plane-leveled and line-corrected surface, and exclude features from a fit only with a stated scientific reason.

  • Record polynomial order.
  • Show excluded masks.
  • Run a preprocessing sensitivity check.

Match the parameter to the scale

Sa and Sq summarize height deviations but do not describe spatial organization. Report scan size, pixel spacing and, where relevant, autocorrelation length or power spectral density.

  • Use equivalent scan dimensions across samples.
  • Acquire more than one region.
  • Keep units and parameter definitions explicit.

Make the comparison auditable

Export the processed map, raw map, correction settings, region mask and per-scan statistics. Group averages should retain between-region variability.

Methodology and scope

The guide aligns areal surface parameters with peer-reviewed evidence on leveling bias. It emphasizes a sensitivity check across reasonable preprocessing choices rather than a universal flattening recipe.

Limitations

  • Finite tip radius limits lateral feature dimensions.
  • A small scan may not represent a heterogeneous sample.
  • Removing tilt or bow can also remove real long-wavelength topography.
  • Roughness values from different scan sizes are not automatically comparable.

References

  1. [1]

    How levelling and scan line corrections ruin roughness measurement and how to prevent it

    Nečas, Valtr and Klapetek. Scientific Reports (2020).

    doi:10.1038/s41598-020-72171-8
  2. [2]

    Geometrical product specifications — Surface texture: Areal — Part 2

    International Organization for Standardization. ISO 25178-2:2021 (2021).

    Open source

Suggested citation

Suggested citation

SciPhys Research Team. “AFM Surface Roughness.” SciPhys, August 5, 2026. https://www.sciphys.com/blog/afm-surface-roughness

Apply the workflow

Inspect roughness on your AFM height map.

Upload a surface file and keep leveling, profiles, regions and roughness metrics visible together.

Analyze AFM data

Sign-in required · starts with an AFM upload

Review surface capabilities

What it does

Built around scientific evidence.

Reject artifacts before calculating roughness

Repeated features, streaks, abrupt line offsets and feedback oscillations can dominate surface statistics. Review trace and retrace where available and inspect line profiles in both scan directions.

  • Look for tip duplication.
  • Check edge streaks and missing lines.
  • Review feedback and scan-speed context.

Document leveling as part of the result

Plane and line corrections are model choices. Compare the raw, plane-leveled and line-corrected surface, and exclude features from a fit only with a stated scientific reason.

  • Record polynomial order.
  • Show excluded masks.
  • Run a preprocessing sensitivity check.

Match the parameter to the scale

Sa and Sq summarize height deviations but do not describe spatial organization. Report scan size, pixel spacing and, where relevant, autocorrelation length or power spectral density.

  • Use equivalent scan dimensions across samples.
  • Acquire more than one region.
  • Keep units and parameter definitions explicit.

Workflow

From raw files to research decisions.

01

Inspect

Confirm the file, units, acquisition settings and sample context before calculation.

02

Level

Apply a documented method while keeping parameters and intermediate evidence visible.

03

Compare

Inspect diagnostics, compare samples consistently and export the evidence with the result.

FAQ

Questions researchers ask first.

What is the difference between Sa and Sq?+

Sa is the mean absolute deviation from the mean plane; Sq is the root-mean-square deviation and weights large height excursions more strongly.

Should every AFM image be flattened?+

Not automatically. Correct known tilt or scanner background with a documented model and check that real long-wavelength structure is not removed.

Why does roughness change with scan size?+

Different scan sizes sample different spatial wavelengths and numbers of features, so roughness is scale-dependent for many real surfaces.