Optimization of TEM Chunk Preparation
Transmission Electron Microscopy (TEM) is one of the most powerful characterization techniques used in semiconductor research and manufacturing, providing detailed information on material structures and device features at the atomic scale. A critical first step in TEM analysis is the preparation of TEM lamella, which begins with extracting a chunk from a specific target region on a wafer.
This thesis focuses on optimizing the TEM chunk preparation process. The student will investigate the influence of key process parameters, including ion beam voltage, beam current, tool alignment, wafer composition, and feature dimensions. Through experimental work, the impact of these parameters on milling speed and preparation quality will be evaluated.
The quality of the ion beam process will be assessed by determining milling rates and quantifying damage introduced outside the intended pattern area. In addition, the student will optimize pattern dimensions and positioning to achieve the best balance between preparation speed and sample quality.
Based on the results, optimal process settings and preparation strategies will be defined to improve the efficiency and robustness of TEM sample preparation. This project combines hands-on work with advanced semiconductor equipment and a strong theoretical understanding of focused ion beam (FIB) processing, offering the opportunity to contribute directly to the optimization of TEM lamella preparation workflows in a state-of-the-art semiconductor environment.
Type of internship: Bachelor internship
Required educational background: Chemistry/Chemical Engineering, Bioscience Engineering, Materials Engineering
Supervising scientist(s): For further information or for application, please contact Felix Seidel (< email slettet af sikkerhedsmæssige årsager >)
The reference code for this position is 2026-INT-268. Mention this reference code in your application.
Applications should include the following information:
Incomplete applications will not be considered.
Transmission Electron Microscopy (TEM) is one of the most powerful characterization techniques used in semiconductor research and manufacturing, providing detailed information on material structures and device features at the atomic scale. A critical first step in TEM analysis is the preparation of TEM lamella, which begins with extracting a chunk from a specific target region on a wafer.
This thesis focuses on optimizing the TEM chunk preparation process. The student will investigate the influence of key process parameters, including ion beam voltage, beam current, tool alignment, wafer composition, and feature dimensions. Through experimental work, the impact of these parameters on milling speed and preparation quality will be evaluated.
The quality of the ion beam process will be assessed by determining milling rates and quantifying damage introduced outside the intended pattern area. In addition, the student will optimize pattern dimensions and positioning to achieve the best balance between preparation speed and sample quality.
Based on the results, optimal process settings and preparation strategies will be defined to improve the efficiency and robustness of TEM sample preparation. This project combines hands-on work with advanced semiconductor equipment and a strong theoretical understanding of focused ion beam (FIB) processing, offering the opportunity to contribute directly to the optimization of TEM lamella preparation workflows in a state-of-the-art semiconductor environment.
Type of internship: Bachelor internship
Required educational background: Chemistry/Chemical Engineering, Bioscience Engineering, Materials Engineering
Supervising scientist(s): For further information or for application, please contact Felix Seidel (< email slettet af sikkerhedsmæssige årsager >)
The reference code for this position is 2026-INT-268. Mention this reference code in your application.
Applications should include the following information:
- resume
- motivation
- current study
Incomplete applications will not be considered.
