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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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Updated: Sep 9, 2025

Atomic Force Microscopy Cantilever-Based Nanoindentation: Mechanical Property Measurements at the Nanoscale in Air and Fluid

Atomic Force Microscopy Cantilever-Based Nanoindentation: Mechanical Property Measurements at the Nanoscale in Air and Fluid

Published on: December 2, 2022

Advances in nanomechanical property mapping by atomic force microscopy.

Ricardo Garcia¹, Jaime R Tejedor¹

¹Instituto de Ciencia de Materiales de Madrid, CSIC c/ Sor Juana Inés de la Cruz 3 28049 Madrid Spain r.garcia@csic.es.

Nanoscale Advances

|August 29, 2025

Summary

Atomic Force Microscopy (AFM) indentation modes map nanoscale mechanical properties. This review updates progress since 2019 on accuracy, speed, machine learning, and advanced applications like nanomechanical tomography.

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Last Updated: Sep 9, 2025

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Area of Science:

Materials Science
Nanotechnology
Biophysics

Background:

Atomic Force Microscopy (AFM) is crucial for measuring mechanical properties in diverse fields.
Nanomechanical mapping involves expressing experimental force via contact mechanics models.
Force spectroscopy includes adhesion and indentation modes for property analysis.

Purpose of the Study:

To review AFM-based indentation modes for nanoscale mechanical property mapping.
To update progress in nanomechanical mapping since 2019.
To highlight advancements in quantitative accuracy, spatial resolution, and data acquisition.

Main Methods:

Utilizing AFM indentation modes to generate spatially resolved mechanical property maps.
Focusing on quantitative accuracy and high-speed data acquisition.
Incorporating machine learning for enhanced analysis and viscoelastic property mapping.

Main Results:

Significant progress in quantitative accuracy and spatial resolution of nanomechanical mapping.
Advancements in high-speed data acquisition enabling rapid analysis.
Development of machine learning algorithms for improved mapping and viscoelastic characterization.

Conclusions:

AFM indentation modes are powerful tools for nanoscale mechanical characterization.
Recent advancements have improved the precision and speed of nanomechanical mapping.
Emerging applications include nanomechanical tomography and solid-liquid interface imaging.