Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Atomic Force Microscopy01:08

Atomic Force Microscopy

4.7K
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...
4.7K
Discrete Fourier Transform01:15

Discrete Fourier Transform

1.1K
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
1.1K
Fast Fourier Transform01:10

Fast Fourier Transform

1.2K
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
1.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Molecular Dynamics Simulation of Adsorption and Friction of Constrained Lubricating Films on Rough Gold Substrates.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Postmastectomy radiotherapy in pN1 breast cancer: Survival outcomes and prognostic factors from a single-institution cohort.

PloS one·2026
Same author

MRI-based radiomics explainable model for predicting recurrence of limb chronic osteomyelitis in limb bones treated by Masquelet technique.

Bone & joint research·2026
Same author

Bioinspired aligned electroconductive hydrogel nanofiber patch enhances peripheral nerve repair through mechanosensitive calcium influx and focal adhesion kinase/protein kinase B pathway activation.

Acta biomaterialia·2026
Same author

Antibody Responses After BA.5/BF.7 Breakthrough Infection in People Living with HIV.

Vaccines·2026
Same author

A Reference-Free Algorithm Discovers Regulation in the Plant Transcriptome.

Plant direct·2026

Related Experiment Video

Updated: Mar 31, 2026

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
11:15

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

26.5K

AFM tip characterization by using FFT filtered images of step structures.

Yongda Yan1, Bo Xue1, Zhenjiang Hu2

  • 1Key Laboratory of Micro-systems and Micro-structures Manufacturing of Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, PR China; Center For Precision Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001, PR China.

Ultramicroscopy
|October 31, 2015
PubMed
Summary

This study introduces a new method to estimate the tip radius of atomic force microscopes (AFM) by analyzing simulated surface profiles. The approach accurately characterizes tip geometry, crucial for nanoscale surface analysis.

Keywords:
Atomic force microscopeSpectrum of imageStep structureTip characterization

More Related Videos

Sub-nanometer Resolution Imaging with Amplitude-modulation Atomic Force Microscopy in Liquid
10:25

Sub-nanometer Resolution Imaging with Amplitude-modulation Atomic Force Microscopy in Liquid

Published on: December 20, 2016

17.7K
A Multimodal Wide-Field Fourier-Transform Raman Microscope
06:48

A Multimodal Wide-Field Fourier-Transform Raman Microscope

Published on: December 30, 2025

750

Related Experiment Videos

Last Updated: Mar 31, 2026

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
11:15

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Published on: May 30, 2016

26.5K
Sub-nanometer Resolution Imaging with Amplitude-modulation Atomic Force Microscopy in Liquid
10:25

Sub-nanometer Resolution Imaging with Amplitude-modulation Atomic Force Microscopy in Liquid

Published on: December 20, 2016

17.7K
A Multimodal Wide-Field Fourier-Transform Raman Microscope
06:48

A Multimodal Wide-Field Fourier-Transform Raman Microscope

Published on: December 30, 2025

750

Area of Science:

  • Materials Science
  • Nanotechnology
  • Surface Science

Background:

  • Atomic Force Microscope (AFM) resolution is critically dependent on tip radius.
  • Accurate tip radius is essential for quantitative nanoscale surface property analysis using AFM.
  • Existing methods for tip radius estimation can be complex or indirect.

Purpose of the Study:

  • To develop a novel, reliable method for characterizing the tip radius of AFM probes.
  • To establish a relationship between tip radius and spectral analysis of scanned profiles.
  • To provide an alternative to existing tip characterization techniques.

Main Methods:

  • A geometrical model of an AFM tip with a hemispherical cone shape was developed.
  • Simulated surface profiles were generated using Fast Fourier Transform (FFT) for various tip radii.
  • The influence of tip radius on the low-frequency harmonics of simulated step structure spectra was analyzed.

Main Results:

  • Low-frequency harmonics in the spectra were found to be sensitive to tip radius variations.
  • A monotonic relationship was identified between tip radius and the amplitude of low-frequency harmonics.
  • The developed method provided tip radius estimations comparable to Scanning Electron Microscopy (SEM) and blind reconstruction.

Conclusions:

  • The new method offers an effective way to characterize hemispherical AFM tip radii.
  • This technique enhances the accuracy of nanoscale surface measurements obtained with AFM.
  • The findings contribute to more reliable interpretation of AFM data in materials science and nanotechnology.