Reconstruction of Kelvin probe force microscopy image with experimentally calibrated point spread function

Area of Science:

• Surface Science
• Nanotechnology
• Materials Science

Background:

• Kelvin probe force microscopy (KPFM) images can be difficult to interpret due to blurring.
• This blurring arises from the long-range nature of electrostatic forces detected by KPFM.
• The KPFM imaging process is modeled as a convolution of the true surface potential (SP) with the system's point spread function (PSF).

Purpose of the Study:

• To develop a method for experimentally calibrating the KPFM system's point spread function (PSF).
• To improve the accuracy of KPFM surface potential (SP) measurements by addressing image blurring.
• To enhance the fidelity of SP signals and reduce noise in KPFM imaging.

Main Methods:

• Experimental calibration of the KPFM system's point spread function (PSF), considering probe shape and experimental parameters.
• Application of a nonlinear reconstruction algorithm utilizing total variation (TV) regularization.
• Reversing the blurring effect caused by the PSF during KPFM imaging.

Main Results:

• An experimentally calibrated PSF that is more accurate than simulated ones.
• Successful reversal of KPFM image blurring.
• Significant reduction in noise and improvement in the fidelity of surface potential (SP) signals.

Conclusions:

• Experimental PSF calibration provides a more accurate representation for KPFM systems.
• The developed method effectively restores true surface potential (SP) distributions from blurred KPFM images.
• This approach enhances the interpretability and reliability of KPFM measurements for materials analysis.