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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: Mar 30, 2026

Force Spectroscopy of Single Protein Molecules Using an Atomic Force Microscope

Force Spectroscopy of Single Protein Molecules Using an Atomic Force Microscope

Published on: February 28, 2019

Dynamic behaviour in piezoresponse force microscopy.

Stephen Jesse¹, Arthur P Baddorf, Sergei V Kalinin

¹Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.

|November 13, 2015

Summary

This summary is machine-generated.

This study analyzes frequency-dependent dynamics in piezoresponse force microscopy (PFM) using atomic force microscopy (AFM). Understanding these dynamics is key for optimizing PFM imaging and interpreting results accurately.

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Last Updated: Mar 30, 2026

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Area of Science:

Materials Science
Nanotechnology
Surface Science

Background:

Piezoresponse Force Microscopy (PFM) is a powerful technique for probing electromechanical properties at the nanoscale.
Atomic Force Microscopy (AFM) provides high-resolution imaging capabilities.
Understanding the dynamic behavior of PFM is crucial for accurate interpretation of experimental data.

Purpose of the Study:

To analyze the frequency-dependent dynamic behavior of PFM on a beam-deflection AFM.
To investigate the contributions of various forces to the PFM signal.
To establish conditions for optimal PFM imaging.

Main Methods:

Combined approach of theoretical modeling and experimental measurements.
Analysis of PFM signal components, including electrostatic and electromechanical contributions.
Implementation of frequency-bias spectroscopy and deconvolution techniques.

Main Results:

The PFM signal is influenced by local electrostatic forces, distributed cantilever forces, and electromechanical response.
Flexural and torsional oscillations of the cantilever contribute to vertical and lateral PFM signals.
Signal contributions vary with geometric parameters, tip-surface junction properties, and operating frequency.

Conclusions:

The study provides a comprehensive analysis of dynamic signal formation in PFM.
Conditions for optimizing PFM imaging have been formulated.
An experimental method for deconvolution of electromechanical and electrostatic contrast was successfully implemented.