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Related Concept Videos

Atomic Force Microscopy01:08

Atomic Force Microscopy

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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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Sensitivity of viscoelastic characterization in multi-harmonic atomic force microscopy.

Abhilash Chandrashekar1, Arthur Givois1, Pierpaolo Belardinelli2

  • 1Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD, Delft, The Netherlands. arthur.givois@utc.fr.

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|November 9, 2022
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This study reveals that surface properties have minimal impact on multi-frequency atomic force microscopy (AFM) data for viscoelastic characterization. Simplifying models by removing surface dependency improves the accuracy and clarity of bulk property measurements.

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Physical Chemistry

Background:

  • Accurate nanomechanical property quantification of soft matter is vital for polymers, coatings, and biological systems.
  • Multi-frequency atomic force microscopy (AFM) utilizes cantilever spectral components for characterization.
  • Complex multi-parameter optimization in AFM can lead to over-determined estimations and unclear parameter-data relationships.

Purpose of the Study:

  • To investigate the sensitivity of viscoelastic characterization in polymers using multi-frequency intermodulation AFM.
  • To identify challenges in parameter estimation and their influence on experimental data.
  • To propose a refined approach for accurate nanoscale viscoelastic property mapping.

Main Methods:

  • Performed simulations and experimental studies on polymeric samples.
  • Analyzed the sensitivity of experimental observables to surface and bulk viscoelastic properties.
  • Investigated the impact of parameter estimation on objective function minimization (gradient and convexity).

Main Results:

  • Surface viscoelasticity was found to have a negligible effect on experimental data.
  • Including surface dependency led to inconsistent and non-physical parameter identification.
  • Removing surface dependency simplified the model, enabling unambiguous characterization of bulk properties.

Conclusions:

  • The study highlights sensitivity issues in AFM when optimizing numerous parameters and observables.
  • A simplified model focusing on bulk properties enhances characterization accuracy and reliability.
  • Development of advanced nanoscale viscoelastic models and computational methods is recommended for AFM applications.