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O: Fachverband Oberflächenphysik
O 66: Poster: Scanning Probe Microscopy with Quartz Sensors
O 66.2: Poster
Mittwoch, 29. März 2023, 18:00–20:00, P2/EG
Novel image interpretation methods for high-resolution STM — •Lauri Kurki1, Niko Oinonen1, Ondrej Krejci1, and Adam S. Foster1,2 — 1Department of Applied Physics, Aalto University, 00076, Espoo, Finland — 2WPI Nano Life Science Institute, Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan
Scanning tunnelling microscopy (STM) functionalized with a CO molecule on the probe apex is a method capable of capturing sub-molecular level detail of the electronic and physical structure of a sample[1]. However, the produced images are often difficult to interpret due to the convoluted nature of the signal. We propose image interpretation tools to extract physical and electronic information directly from STM images using machine learning.
In recent years, there has been rapid development in image analysis methods using machine learning, with particular impact in medical imaging. These concepts have been proven effective also in SPM in general and in particular for extracting physical features from atomic force microscopy (AFM) images[2]. We build upon these models and show that we can extract atomic positions and electrostatics directly from STM images. We further explore how the accuracy of these predictions varies with the use of a simultaneous AFM signal and ultimately establish the limits of the approach in an experimental context.
[1] Shuning Cai, Lauri Kurki, Chen Xu, Adam S. Foster, and Peter Liljeroth. JACS 144 (44), 20227-20231 (2022)
[2] Niko Oinonen, Lauri Kurki, Alexander Ilin, and Adam S. Foster. MRS Bulletin 47, 895-905 (2022)