Paper
22 May 2009 Kelvin probe force microscopy: measurement data reconstruction
Torsten Machleidt, Erik Sparrer, Tim Kubertschak, Rico Nestler, Karl-Heinz Franke
Author Affiliations +
Proceedings Volume 7378, Scanning Microscopy 2009; 73781C (2009) https://doi.org/10.1117/12.821787
Event: SPIE Scanning Microscopy, 2009, Monterey, California, United States
Abstract
The Kelvin Probe Force Microscopy (KPFM) is a method to detect the surface potential of micro- and nanostructured samples using a common Scanning Probe Microscope (SPM). The electrostatic force has a very long range compared to other surface forces. By using SPM systems the KPFM measurements are performed in the noncontact region at surface distances greater than 10 nm. In contrast to topography measurement, the measured data is blurred. The KPFM signal can be described as a convolution of an effective surface potential and a microscope intrinsic point spread function, which allows the restoration of the measured data by deconvolution. This paper deals with methods to deconvolute the measured KPFM data with the objective to increase the lateral resolution. An analytical and a practical way of obtaining the point spread function of the microscope was compared. In contrast to other papers a modern DoF-restricted deconvolution algorithm is applied to the measured data. The new method was demonstrated on a nanoscale test stripe pattern for lateral resolution and calibration of length scales (BAM-L200) made by German Federal Istitute for Materials Research and Testing.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Torsten Machleidt, Erik Sparrer, Tim Kubertschak, Rico Nestler, and Karl-Heinz Franke "Kelvin probe force microscopy: measurement data reconstruction", Proc. SPIE 7378, Scanning Microscopy 2009, 73781C (22 May 2009); https://doi.org/10.1117/12.821787
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Cited by 4 scholarly publications.
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KEYWORDS
Point spread functions

Deconvolution

Scanning probe microscopy

Microscopy

Convolution

Chemical elements

Data modeling

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