Stitching accuracy in large area scanning probe microscopy
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Date
2024-10-04
Authors
Klapetek, Petr
Nečas, David
Heaps, Edward
Sauvet, Bruno
Klapetek, Vojtěch
Valtr, Miroslav
Korpelainen, Virpi
Yacoot, Andrew
0000-0001-5241-9178Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
IOP Publishing Ltd
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Abstract
Image stitching is a technique that can significantly enlarge the scan area of scanning probe microscope (SPM) images. It is also the most commonly used method to cover large areas in high-speed SPM. In this paper, we provide details on stitching algorithms developed specifically to mitigate the effects of SPM error sources, namely the presence of scanner non-flatness. Using both synthetic data and flat samples we analyse the potential uncertainty contributions related to stitching, showing that the drift and line mismatch are the dominant sources of uncertainty. We also present the 'flatten base' algorithm that can significantly improve the stitched data results, at the cost of losing the large area form information about the sample.
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Citation
Measurement Science and Technology. 2024, vol. 35, issue 12, p. 125026-125037.
https://iopscience.iop.org/article/10.1088/1361-6501/ad7a13
https://iopscience.iop.org/article/10.1088/1361-6501/ad7a13
Document type
Peer-reviewed
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Published version
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Language of document
en