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Updated: May 18, 2026
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Functionalization of Atomic Force Microscope Cantilevers with Single-T Cells or Single-Particle for Immunological Single-Cell Force Spectroscopy
Published on: July 10, 2019
Atomic force microscopy as a tool applied to nano/biosensors
Clarice Steffens1, Fabio L Leite, Carolina C Bueno
1National Nanotechnology Laboratory for Agribusiness (LNNA), Embrapa Instrumentation, São Carlos, SP, Brazil. clarice@cnpdia.embrapa.br
Sensors (Basel, Switzerland)
|September 13, 2012
Summary
Chemical Force Microscopy (CFM) and nanomechanical cantilever sensors (NCS) enable sensitive, low-cost detection. These tools, including microcantilever-based biosensors (MC-B), are crucial for atomic-scale characterization in various fields.
Area of Science:
- Nanotechnology and Biosensing
- Surface Science and Materials Characterization
Background:
- Nano/biosensors are critical for in situ detection.
- Chemical Force Microscopy (CFM) studies molecular and polymer design.
- Atomic Force Microscopy (AFM) tip-sample interactions are key.
Purpose of the Study:
- To review basic concepts of nano/biosensors.
- To highlight the application of CFM, nanomechanical cantilever sensors (NCS), and microcantilever-based biosensors (MC-B).
- To demonstrate their importance in atomic-scale characterization.
Main Methods:
- Utilizing Chemical Force Microscopy (CFM) with Atomic Force Microscopy (AFM).
- Fabricating nanomechanical cantilever sensors (NCS) and microcantilever-based biosensors (MC-B).
- Reviewing applications in agriculture, biotechnology, and immunoassay.
Main Results:
- CFM, NCS, and MC-B offer rapid, sensitive, simple, and low-cost detection.
- These techniques provide high repeatability and reproducibility.
- Demonstrated utility in understanding chemical interactions at the atomic scale.
Conclusions:
- CFM, NCS, and MC-B are vital tools for detailed system characterization.
- These methods facilitate a deeper understanding of molecular and polymer interactions.
- The review provides methodological insights for reliable data acquisition.
