Time-dependent dielectric breakdown (TDDB) is a key reliability concern for advanced back-end-of-line (BEOL) interconnect technologies. As BEOL dimensions continue to shrink and integration schemes become more complex, local variations in electric field, material composition, and nanoscale geometry can strongly influence the onset and evolution of dielectric breakdown.
The goal of this internship is to further develop a 3D BEOL TDDB simulator to investigate how local electric-field distribution and atomic-scale structural variations affect dielectric degradation and breakdown behavior. The project will focus on extending the simulation framework to better capture the impact of local field enhancement, impurity-related effects, and geometry-induced variations in the dielectric stack or interconnect environment.
The student will work on improving and applying the simulator to study different structural scenarios relevant to BEOL reliability. This may include evaluating the influence of local geometrical features, defect-prone regions, and impurity distributions on the predicted breakdown path or degradation probability. The work will combine physical understanding of dielectric reliability with numerical modeling and data analysis.
During the internship, the student is expected to:
- Become familiar with BEOL dielectric reliability and TDDB mechanisms.
- Understand the existing 3D TDDB simulation framework.
- Implement or improve simulation modules related to local electric-field effects and atomic-structure-dependent degradation.
- Analyze how impurities, local geometry, and field enhancement contribute to breakdown behavior.
- Compare simulation trends across different material or structural configurations.
- Document the methodology, results, and key physical insights.
This internship is suitable for a motivated Master student interested in semiconductor reliability, device physics, computational modeling, and advanced BEOL technology. The outcome of the project will contribute to a better understanding of nanoscale reliability risks in future interconnect technologies and support the development of more physics-aware TDDB prediction methodologies.