/Automated electron channeling-based defect metrology for beyond-Si semiconductors

Automated electron channeling-based defect metrology for beyond-Si semiconductors

Leuven | More than two weeks ago

Your programming efforts will help to improve the quality of crystal defect analysis in the area of nanoelectronics device technology.

Nanoelectronic and photonic devices such as transistors, lasers, light emitting diodes (LED) and optical sensors plays an important role in our daily life. Such devices are mainly based on the heterogeneous structures of (Si)Ge alloys, III-V (e.g. GaAs, InGaAs) and III-N (e.g. GaN) compounds integrated on Si substrates. During the epitaxial growth, the lattice and thermal mismatch between epitaxial layers and the underlying substrate can lead to high strain/stress. This can further generate different types of crystalline defects (e.g. threading dislocations, stacking faults) during the plastic relaxation. Such defects can strongly influence the surface/interface morphologies, electrical/optical properties and thus the performance of related devices. As a result, it is important to detect and monitor such defects. Nowadays the state-of-art hetero-epitaxy layer systems can reach a low defect density levels (<105/cm2), which significantly adds the difficulty during defect characterization. As a fast, reliable and non-destructive technique, electron channeling contrast imaging (ECCI) is promising to investigate large areas thereby facilitating a lower detection limit. To reduce the measurement time, automation in ECCI attracts more and more interest.


The goal of this internship is to find out the optimized imaging conditions and to apply such tool conditions for automated ECCI. Both manul and automated ECCI will be done for comparison. The student should have good knowledge in programming (Python) or have good knowledge in C, C++, or matlab programming and be willing to learn Python. The student should know or be willing to learn crystallography, scanning electron microscopy (SEM) and semiconductor characterizations.


For this topic, the student will mainly work in the SEM lab and carry out the required experimental steps. The student will characterize the imec-internal samples to assess the automated ECCI. The student will be part of imec’s materials and component and analysis group.

Type of project: Combination of internship and thesis, Internship

Duration: 6 months

Required degree: Master of Science, Master of Engineering Science, Master of Engineering Technology

Required background: Electrotechnics/Electrical Engineering, Materials Engineering, Physics, Computer Science

Supervising scientist(s): For further information or for application, please contact: Han Han (Han.Han@imec.be) and Eva Grieten (Eva.Grieten@imec.be) and Thomas Hantschel (Thomas.Hantschel@imec.be)

Imec allowance will be provided for students studying at a non-Belgian university.

Who we are
Accept marketing-cookies to view this content.
Cookie settings
imec's cleanroom
Accept marketing-cookies to view this content.
Cookie settings

Send this job to your email