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Thickness Resonance Acoustic Microscopy for Nanomechanical Subsurface Imaging.
Gajendra S Shekhawat, Arvind K Srivastava1, Vinayak P Dravid
1Systron Donner Inertial , 2700 Systron Drive, Concord, California 94518, United States.
ACS Nano
|May 18, 2017
Summary
Scanning near-field thickness resonance acoustic microscopy (SNTRAM) offers high-resolution imaging of subsurface features. This nondestructive technique achieves nanometer-scale contrast and depth sensitivity by exciting samples at their thickness resonance.
Area of Science:
- Materials Science
- Nondestructive Testing
- Acoustic Microscopy
Background:
- Traditional acoustic microscopy methods struggle with high-resolution subsurface imaging and depth sensitivity.
- Detecting nanometer-scale subsurface features and defects non-destructively remains a significant challenge in materials characterization.
Purpose of the Study:
- To develop and demonstrate a nondestructive scanning near-field thickness resonance acoustic microscopy (SNTRAM) technique.
- To achieve high-resolution mechanical depth sensitivity and sharp phase contrast for subsurface features.
- To showcase the superior performance of SNTRAM compared to off-resonance and related acoustic techniques.
Main Methods:
- Excitation of the sample at its thickness resonance frequency using a sinusoidal elastic wave.
- Mapping the sharp phase change observed at resonance using a scanning probe microscopy stage in the near field.
- Utilizing the bulk longitudinal wave propagation through the sample thickness for signal generation.
Main Results:
- Achieved remarkable sub-subsurface phase contrast and sensitivity.
- Demonstrated nanometer-scale nanomechanical contrast of subsurface features and defects.
- Obtained a lateral resolution down to 5-8 nm for subsurface features using a standard sample.
- Showcased significantly higher phase contrast and depth sensitivity compared to off-resonance excitation and other acoustic techniques.
Conclusions:
- SNTRAM provides superior image contrast and signal-to-noise ratio for subsurface feature detection.
- The technique enables sensitive detection of local material property variations with enhanced resolution.
- SNTRAM is a promising nondestructive method for high-resolution subsurface characterization and defect analysis.

