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Time-frequency analysis of the tip motion in liquids using the wavelet transform in dynamic atomic force microscopy
Zhenyu Wang1,2, Jianqiang Qian1,2, Yingzi Li1,2
1School of Physics and Nuclear Energy Engineering, Beihang University, Beijing 100083, People's Republic of China.
Wavelet transform analysis reveals complex tip motion in dynamic atomic force microscopy (AFM) experiments conducted in liquids. This method clearly visualizes momentary cantilever mode excitation and multiple tip-sample impacts, aiding nanomechanical property characterization.
Area of Science:
- Physics
- Materials Science
- Nanotechnology
Background:
- Dynamic atomic force microscopy (AFM) in liquids presents challenges in analyzing complex tip-sample interactions.
- Low stiffness cantilevers exhibit transient behaviors, including momentary excitation of the second flexural mode and multiple impacts per oscillation cycle.
- Traditional Fourier transform methods lack the time-resolution necessary to capture these transient dynamics.
Purpose of the Study:
- To introduce and validate the wavelet transform for time-frequency analysis of dynamic AFM tip motion in liquids.
- To overcome the limitations of Fourier analysis in characterizing transient behaviors.
- To quantitatively assess the excitation of the second flexural mode and multiple impact events.
Main Methods:
- Application of wavelet transform for time-frequency analysis of dynamic AFM tip motion.
- Utilizing wavelet scalograms to visualize transient phenomena like second mode excitation and multiple impacts.
- Employing wavelet ridge analysis to extract instantaneous frequencies and magnitudes of the second mode.
Main Results:
- Wavelet scalograms clearly depict the momentary excitation of the second flexural mode and multiple tip-sample impacts.
- Wavelet ridge analysis enables quantitative estimation of the second mode's instantaneous frequencies and magnitudes.
- The maximum instantaneous magnitude (MIM) was found to correlate with the amplitude setpoint and sample Young's modulus.
Conclusions:
- Wavelet transform analysis provides superior time-frequency insights into dynamic AFM tip motion in liquids compared to Fourier methods.
- The study demonstrates the capability of wavelet analysis to identify and quantify complex transient events.
- Maximum instantaneous magnitude (MIM) shows potential as a metric for characterizing nanomechanical properties of sample surfaces, particularly at high amplitude setpoints.
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