BAP: Video on SEM

SEM control - subgroup report

Bachelor Thesis (2025)
Author(s)

T.L.E. ten Berge (TU Delft - Electrical Engineering, Mathematics and Computer Science)

A.M. Spijker (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

S. Vollebregt – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Y. Zhang – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2025
Language
English
Graduation Date
17-12-2025
Awarding Institution
Delft University of Technology
Project
CSE3000 Research Project
Programme
Electrical Engineering
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

This report presents the design and implementation of an automated image-acquisition module for the FEI XL30 SFEG Scanning Electron Microscope (SEM). Older SEM models such as the XL30 lack built-in functionality for long-duration, unattended imaging, limiting researchers to manually capturing frames or taking only sparse images across an experiment. To address this limitation, a Python-based control subsystem was developed that communicates with the SEM via its RS232 serial interface and coordinates with an image-processing subsystem. Since samples may drift at high magnification levels during long-duration imaging, a drift correction feedback loop was implemented. The loop ensures that the region of interest is always kept in the centre of the frame, by both software stabilization and beam shift correction. A custom message protocol, robust error-handling framework, and graphical user interface were implemented to ensure reliable operation within the constraints of a legacy Windows 2000/Windows 7 environment. The resulting system enables stable, long-duration SEM video acquisition without the need for user supervision.

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