In this work, a new theoretical model for contact resonance atomic force microscopy, which incorporates the elastic dynamics of a long sensing tip is presented. The model is based on the Euler–Bernoulli beam theory and includes coupling effects from the two-beam structure, also known as an ‘L-shaped’ beam in the literature. Here, high-accuracy prediction of the sample stiffness, using several vibration modes with a relative error smaller than 10% for practical working ranges, is demonstrated. A discussion on the model’s capability to predict the dynamic phenomena of eigenmode veering and crossing, as the force applied to the sample increases, is presented. The L-shaped beam model presented here is also applicable for structural applications such as: micro-electro-mechanical systems, energy harvesting, and unmanned aerial vehicle landing gear.
Contact Resonance Atomic Force Microscopy Using Long, Massive Tips
In this work, we present a new theoretical model for use in contact resonance atomic force microscopy. This model incorporates the effects of a long, massive sensing tip and is especially useful to interpret operation in the so-called trolling mode. The model is based on traditional Euler–Bernoulli beam theory, whereby the effect of the tip as well as of the sample in contact, modeled as an elastic substrate, are captured by appropriate boundary conditions. A novel interpretation of the flexural and torsional modes of vibration of the cantilever, when not in contact with the sample, is used to estimate the inertia properties of the long, massive tip. Using this information, sample elastic properties are then estimated from the in-contact resonance frequencies of the system. The predictive capability of the proposed model is verified via finite element analysis. Different combinations of cantilever geometry, tip geometry, and sample stiffness are investigated. The model’s accurate predictive ranges are discussed and shown to outperform those of other popular models currently used in contact resonance atomic force microscopy.
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- Award ID(s):
- 1660448
- NSF-PAR ID:
- 10125492
- Date Published:
- Journal Name:
- Sensors
- Volume:
- 19
- Issue:
- 22
- ISSN:
- 1424-8220
- Page Range / eLocation ID:
- 4990
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/s19224990
